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Google Cloud Native v0.32.0 published on Wednesday, Nov 29, 2023 by Pulumi

google-native.monitoring/v1.Dashboard

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Google Cloud Native is in preview. Google Cloud Classic is fully supported.

Google Cloud Native v0.32.0 published on Wednesday, Nov 29, 2023 by Pulumi

    Creates a new custom dashboard. For examples on how you can use this API to create dashboards, see Managing dashboards by API (https://cloud.google.com/monitoring/dashboards/api-dashboard). This method requires the monitoring.dashboards.create permission on the specified project. For more information about permissions, see Cloud Identity and Access Management (https://cloud.google.com/iam).

    Create Dashboard Resource

    new Dashboard(name: string, args: DashboardArgs, opts?: CustomResourceOptions);
    @overload
    def Dashboard(resource_name: str,
                  opts: Optional[ResourceOptions] = None,
                  column_layout: Optional[ColumnLayoutArgs] = None,
                  dashboard_filters: Optional[Sequence[DashboardFilterArgs]] = None,
                  display_name: Optional[str] = None,
                  etag: Optional[str] = None,
                  grid_layout: Optional[GridLayoutArgs] = None,
                  labels: Optional[Mapping[str, str]] = None,
                  mosaic_layout: Optional[MosaicLayoutArgs] = None,
                  name: Optional[str] = None,
                  project: Optional[str] = None,
                  row_layout: Optional[RowLayoutArgs] = None)
    @overload
    def Dashboard(resource_name: str,
                  args: DashboardArgs,
                  opts: Optional[ResourceOptions] = None)
    func NewDashboard(ctx *Context, name string, args DashboardArgs, opts ...ResourceOption) (*Dashboard, error)
    public Dashboard(string name, DashboardArgs args, CustomResourceOptions? opts = null)
    public Dashboard(String name, DashboardArgs args)
    public Dashboard(String name, DashboardArgs args, CustomResourceOptions options)
    
    type: google-native:monitoring/v1:Dashboard
    properties: # The arguments to resource properties.
    options: # Bag of options to control resource's behavior.
    
    
    name string
    The unique name of the resource.
    args DashboardArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    resource_name str
    The unique name of the resource.
    args DashboardArgs
    The arguments to resource properties.
    opts ResourceOptions
    Bag of options to control resource's behavior.
    ctx Context
    Context object for the current deployment.
    name string
    The unique name of the resource.
    args DashboardArgs
    The arguments to resource properties.
    opts ResourceOption
    Bag of options to control resource's behavior.
    name string
    The unique name of the resource.
    args DashboardArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    name String
    The unique name of the resource.
    args DashboardArgs
    The arguments to resource properties.
    options CustomResourceOptions
    Bag of options to control resource's behavior.

    Dashboard Resource Properties

    To learn more about resource properties and how to use them, see Inputs and Outputs in the Architecture and Concepts docs.

    Inputs

    The Dashboard resource accepts the following input properties:

    DisplayName string
    The mutable, human-readable name.
    ColumnLayout Pulumi.GoogleNative.Monitoring.V1.Inputs.ColumnLayout
    The content is divided into equally spaced columns and the widgets are arranged vertically.
    DashboardFilters List<Pulumi.GoogleNative.Monitoring.V1.Inputs.DashboardFilter>
    Filters to reduce the amount of data charted based on the filter criteria.
    Etag string
    etag is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. An etag is returned in the response to GetDashboard, and users are expected to put that etag in the request to UpdateDashboard to ensure that their change will be applied to the same version of the Dashboard configuration. The field should not be passed during dashboard creation.
    GridLayout Pulumi.GoogleNative.Monitoring.V1.Inputs.GridLayout
    Content is arranged with a basic layout that re-flows a simple list of informational elements like widgets or tiles.
    Labels Dictionary<string, string>
    Labels applied to the dashboard
    MosaicLayout Pulumi.GoogleNative.Monitoring.V1.Inputs.MosaicLayout
    The content is arranged as a grid of tiles, with each content widget occupying one or more grid blocks.
    Name string
    Immutable. The resource name of the dashboard.
    Project string
    RowLayout Pulumi.GoogleNative.Monitoring.V1.Inputs.RowLayout
    The content is divided into equally spaced rows and the widgets are arranged horizontally.
    DisplayName string
    The mutable, human-readable name.
    ColumnLayout ColumnLayoutArgs
    The content is divided into equally spaced columns and the widgets are arranged vertically.
    DashboardFilters []DashboardFilterArgs
    Filters to reduce the amount of data charted based on the filter criteria.
    Etag string
    etag is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. An etag is returned in the response to GetDashboard, and users are expected to put that etag in the request to UpdateDashboard to ensure that their change will be applied to the same version of the Dashboard configuration. The field should not be passed during dashboard creation.
    GridLayout GridLayoutArgs
    Content is arranged with a basic layout that re-flows a simple list of informational elements like widgets or tiles.
    Labels map[string]string
    Labels applied to the dashboard
    MosaicLayout MosaicLayoutArgs
    The content is arranged as a grid of tiles, with each content widget occupying one or more grid blocks.
    Name string
    Immutable. The resource name of the dashboard.
    Project string
    RowLayout RowLayoutArgs
    The content is divided into equally spaced rows and the widgets are arranged horizontally.
    displayName String
    The mutable, human-readable name.
    columnLayout ColumnLayout
    The content is divided into equally spaced columns and the widgets are arranged vertically.
    dashboardFilters List<DashboardFilter>
    Filters to reduce the amount of data charted based on the filter criteria.
    etag String
    etag is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. An etag is returned in the response to GetDashboard, and users are expected to put that etag in the request to UpdateDashboard to ensure that their change will be applied to the same version of the Dashboard configuration. The field should not be passed during dashboard creation.
    gridLayout GridLayout
    Content is arranged with a basic layout that re-flows a simple list of informational elements like widgets or tiles.
    labels Map<String,String>
    Labels applied to the dashboard
    mosaicLayout MosaicLayout
    The content is arranged as a grid of tiles, with each content widget occupying one or more grid blocks.
    name String
    Immutable. The resource name of the dashboard.
    project String
    rowLayout RowLayout
    The content is divided into equally spaced rows and the widgets are arranged horizontally.
    displayName string
    The mutable, human-readable name.
    columnLayout ColumnLayout
    The content is divided into equally spaced columns and the widgets are arranged vertically.
    dashboardFilters DashboardFilter[]
    Filters to reduce the amount of data charted based on the filter criteria.
    etag string
    etag is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. An etag is returned in the response to GetDashboard, and users are expected to put that etag in the request to UpdateDashboard to ensure that their change will be applied to the same version of the Dashboard configuration. The field should not be passed during dashboard creation.
    gridLayout GridLayout
    Content is arranged with a basic layout that re-flows a simple list of informational elements like widgets or tiles.
    labels {[key: string]: string}
    Labels applied to the dashboard
    mosaicLayout MosaicLayout
    The content is arranged as a grid of tiles, with each content widget occupying one or more grid blocks.
    name string
    Immutable. The resource name of the dashboard.
    project string
    rowLayout RowLayout
    The content is divided into equally spaced rows and the widgets are arranged horizontally.
    display_name str
    The mutable, human-readable name.
    column_layout ColumnLayoutArgs
    The content is divided into equally spaced columns and the widgets are arranged vertically.
    dashboard_filters Sequence[DashboardFilterArgs]
    Filters to reduce the amount of data charted based on the filter criteria.
    etag str
    etag is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. An etag is returned in the response to GetDashboard, and users are expected to put that etag in the request to UpdateDashboard to ensure that their change will be applied to the same version of the Dashboard configuration. The field should not be passed during dashboard creation.
    grid_layout GridLayoutArgs
    Content is arranged with a basic layout that re-flows a simple list of informational elements like widgets or tiles.
    labels Mapping[str, str]
    Labels applied to the dashboard
    mosaic_layout MosaicLayoutArgs
    The content is arranged as a grid of tiles, with each content widget occupying one or more grid blocks.
    name str
    Immutable. The resource name of the dashboard.
    project str
    row_layout RowLayoutArgs
    The content is divided into equally spaced rows and the widgets are arranged horizontally.
    displayName String
    The mutable, human-readable name.
    columnLayout Property Map
    The content is divided into equally spaced columns and the widgets are arranged vertically.
    dashboardFilters List<Property Map>
    Filters to reduce the amount of data charted based on the filter criteria.
    etag String
    etag is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. An etag is returned in the response to GetDashboard, and users are expected to put that etag in the request to UpdateDashboard to ensure that their change will be applied to the same version of the Dashboard configuration. The field should not be passed during dashboard creation.
    gridLayout Property Map
    Content is arranged with a basic layout that re-flows a simple list of informational elements like widgets or tiles.
    labels Map<String>
    Labels applied to the dashboard
    mosaicLayout Property Map
    The content is arranged as a grid of tiles, with each content widget occupying one or more grid blocks.
    name String
    Immutable. The resource name of the dashboard.
    project String
    rowLayout Property Map
    The content is divided into equally spaced rows and the widgets are arranged horizontally.

    Outputs

    All input properties are implicitly available as output properties. Additionally, the Dashboard resource produces the following output properties:

    Id string
    The provider-assigned unique ID for this managed resource.
    Id string
    The provider-assigned unique ID for this managed resource.
    id String
    The provider-assigned unique ID for this managed resource.
    id string
    The provider-assigned unique ID for this managed resource.
    id str
    The provider-assigned unique ID for this managed resource.
    id String
    The provider-assigned unique ID for this managed resource.

    Supporting Types

    Aggregation, AggregationArgs

    AlignmentPeriod string
    The alignment_period specifies a time interval, in seconds, that is used to divide the data in all the time series into consistent blocks of time. This will be done before the per-series aligner can be applied to the data.The value must be at least 60 seconds. If a per-series aligner other than ALIGN_NONE is specified, this field is required or an error is returned. If no per-series aligner is specified, or the aligner ALIGN_NONE is specified, then this field is ignored.The maximum value of the alignment_period is 2 years, or 104 weeks.
    CrossSeriesReducer Pulumi.GoogleNative.Monitoring.V1.AggregationCrossSeriesReducer
    The reduction operation to be used to combine time series into a single time series, where the value of each data point in the resulting series is a function of all the already aligned values in the input time series.Not all reducer operations can be applied to all time series. The valid choices depend on the metric_kind and the value_type of the original time series. Reduction can yield a time series with a different metric_kind or value_type than the input time series.Time series data must first be aligned (see per_series_aligner) in order to perform cross-time series reduction. If cross_series_reducer is specified, then per_series_aligner must be specified, and must not be ALIGN_NONE. An alignment_period must also be specified; otherwise, an error is returned.
    GroupByFields List<string>
    The set of fields to preserve when cross_series_reducer is specified. The group_by_fields determine how the time series are partitioned into subsets prior to applying the aggregation operation. Each subset contains time series that have the same value for each of the grouping fields. Each individual time series is a member of exactly one subset. The cross_series_reducer is applied to each subset of time series. It is not possible to reduce across different resource types, so this field implicitly contains resource.type. Fields not specified in group_by_fields are aggregated away. If group_by_fields is not specified and all the time series have the same resource type, then the time series are aggregated into a single output time series. If cross_series_reducer is not defined, this field is ignored.
    PerSeriesAligner Pulumi.GoogleNative.Monitoring.V1.AggregationPerSeriesAligner
    An Aligner describes how to bring the data points in a single time series into temporal alignment. Except for ALIGN_NONE, all alignments cause all the data points in an alignment_period to be mathematically grouped together, resulting in a single data point for each alignment_period with end timestamp at the end of the period.Not all alignment operations may be applied to all time series. The valid choices depend on the metric_kind and value_type of the original time series. Alignment can change the metric_kind or the value_type of the time series.Time series data must be aligned in order to perform cross-time series reduction. If cross_series_reducer is specified, then per_series_aligner must be specified and not equal to ALIGN_NONE and alignment_period must be specified; otherwise, an error is returned.
    AlignmentPeriod string
    The alignment_period specifies a time interval, in seconds, that is used to divide the data in all the time series into consistent blocks of time. This will be done before the per-series aligner can be applied to the data.The value must be at least 60 seconds. If a per-series aligner other than ALIGN_NONE is specified, this field is required or an error is returned. If no per-series aligner is specified, or the aligner ALIGN_NONE is specified, then this field is ignored.The maximum value of the alignment_period is 2 years, or 104 weeks.
    CrossSeriesReducer AggregationCrossSeriesReducer
    The reduction operation to be used to combine time series into a single time series, where the value of each data point in the resulting series is a function of all the already aligned values in the input time series.Not all reducer operations can be applied to all time series. The valid choices depend on the metric_kind and the value_type of the original time series. Reduction can yield a time series with a different metric_kind or value_type than the input time series.Time series data must first be aligned (see per_series_aligner) in order to perform cross-time series reduction. If cross_series_reducer is specified, then per_series_aligner must be specified, and must not be ALIGN_NONE. An alignment_period must also be specified; otherwise, an error is returned.
    GroupByFields []string
    The set of fields to preserve when cross_series_reducer is specified. The group_by_fields determine how the time series are partitioned into subsets prior to applying the aggregation operation. Each subset contains time series that have the same value for each of the grouping fields. Each individual time series is a member of exactly one subset. The cross_series_reducer is applied to each subset of time series. It is not possible to reduce across different resource types, so this field implicitly contains resource.type. Fields not specified in group_by_fields are aggregated away. If group_by_fields is not specified and all the time series have the same resource type, then the time series are aggregated into a single output time series. If cross_series_reducer is not defined, this field is ignored.
    PerSeriesAligner AggregationPerSeriesAligner
    An Aligner describes how to bring the data points in a single time series into temporal alignment. Except for ALIGN_NONE, all alignments cause all the data points in an alignment_period to be mathematically grouped together, resulting in a single data point for each alignment_period with end timestamp at the end of the period.Not all alignment operations may be applied to all time series. The valid choices depend on the metric_kind and value_type of the original time series. Alignment can change the metric_kind or the value_type of the time series.Time series data must be aligned in order to perform cross-time series reduction. If cross_series_reducer is specified, then per_series_aligner must be specified and not equal to ALIGN_NONE and alignment_period must be specified; otherwise, an error is returned.
    alignmentPeriod String
    The alignment_period specifies a time interval, in seconds, that is used to divide the data in all the time series into consistent blocks of time. This will be done before the per-series aligner can be applied to the data.The value must be at least 60 seconds. If a per-series aligner other than ALIGN_NONE is specified, this field is required or an error is returned. If no per-series aligner is specified, or the aligner ALIGN_NONE is specified, then this field is ignored.The maximum value of the alignment_period is 2 years, or 104 weeks.
    crossSeriesReducer AggregationCrossSeriesReducer
    The reduction operation to be used to combine time series into a single time series, where the value of each data point in the resulting series is a function of all the already aligned values in the input time series.Not all reducer operations can be applied to all time series. The valid choices depend on the metric_kind and the value_type of the original time series. Reduction can yield a time series with a different metric_kind or value_type than the input time series.Time series data must first be aligned (see per_series_aligner) in order to perform cross-time series reduction. If cross_series_reducer is specified, then per_series_aligner must be specified, and must not be ALIGN_NONE. An alignment_period must also be specified; otherwise, an error is returned.
    groupByFields List<String>
    The set of fields to preserve when cross_series_reducer is specified. The group_by_fields determine how the time series are partitioned into subsets prior to applying the aggregation operation. Each subset contains time series that have the same value for each of the grouping fields. Each individual time series is a member of exactly one subset. The cross_series_reducer is applied to each subset of time series. It is not possible to reduce across different resource types, so this field implicitly contains resource.type. Fields not specified in group_by_fields are aggregated away. If group_by_fields is not specified and all the time series have the same resource type, then the time series are aggregated into a single output time series. If cross_series_reducer is not defined, this field is ignored.
    perSeriesAligner AggregationPerSeriesAligner
    An Aligner describes how to bring the data points in a single time series into temporal alignment. Except for ALIGN_NONE, all alignments cause all the data points in an alignment_period to be mathematically grouped together, resulting in a single data point for each alignment_period with end timestamp at the end of the period.Not all alignment operations may be applied to all time series. The valid choices depend on the metric_kind and value_type of the original time series. Alignment can change the metric_kind or the value_type of the time series.Time series data must be aligned in order to perform cross-time series reduction. If cross_series_reducer is specified, then per_series_aligner must be specified and not equal to ALIGN_NONE and alignment_period must be specified; otherwise, an error is returned.
    alignmentPeriod string
    The alignment_period specifies a time interval, in seconds, that is used to divide the data in all the time series into consistent blocks of time. This will be done before the per-series aligner can be applied to the data.The value must be at least 60 seconds. If a per-series aligner other than ALIGN_NONE is specified, this field is required or an error is returned. If no per-series aligner is specified, or the aligner ALIGN_NONE is specified, then this field is ignored.The maximum value of the alignment_period is 2 years, or 104 weeks.
    crossSeriesReducer AggregationCrossSeriesReducer
    The reduction operation to be used to combine time series into a single time series, where the value of each data point in the resulting series is a function of all the already aligned values in the input time series.Not all reducer operations can be applied to all time series. The valid choices depend on the metric_kind and the value_type of the original time series. Reduction can yield a time series with a different metric_kind or value_type than the input time series.Time series data must first be aligned (see per_series_aligner) in order to perform cross-time series reduction. If cross_series_reducer is specified, then per_series_aligner must be specified, and must not be ALIGN_NONE. An alignment_period must also be specified; otherwise, an error is returned.
    groupByFields string[]
    The set of fields to preserve when cross_series_reducer is specified. The group_by_fields determine how the time series are partitioned into subsets prior to applying the aggregation operation. Each subset contains time series that have the same value for each of the grouping fields. Each individual time series is a member of exactly one subset. The cross_series_reducer is applied to each subset of time series. It is not possible to reduce across different resource types, so this field implicitly contains resource.type. Fields not specified in group_by_fields are aggregated away. If group_by_fields is not specified and all the time series have the same resource type, then the time series are aggregated into a single output time series. If cross_series_reducer is not defined, this field is ignored.
    perSeriesAligner AggregationPerSeriesAligner
    An Aligner describes how to bring the data points in a single time series into temporal alignment. Except for ALIGN_NONE, all alignments cause all the data points in an alignment_period to be mathematically grouped together, resulting in a single data point for each alignment_period with end timestamp at the end of the period.Not all alignment operations may be applied to all time series. The valid choices depend on the metric_kind and value_type of the original time series. Alignment can change the metric_kind or the value_type of the time series.Time series data must be aligned in order to perform cross-time series reduction. If cross_series_reducer is specified, then per_series_aligner must be specified and not equal to ALIGN_NONE and alignment_period must be specified; otherwise, an error is returned.
    alignment_period str
    The alignment_period specifies a time interval, in seconds, that is used to divide the data in all the time series into consistent blocks of time. This will be done before the per-series aligner can be applied to the data.The value must be at least 60 seconds. If a per-series aligner other than ALIGN_NONE is specified, this field is required or an error is returned. If no per-series aligner is specified, or the aligner ALIGN_NONE is specified, then this field is ignored.The maximum value of the alignment_period is 2 years, or 104 weeks.
    cross_series_reducer AggregationCrossSeriesReducer
    The reduction operation to be used to combine time series into a single time series, where the value of each data point in the resulting series is a function of all the already aligned values in the input time series.Not all reducer operations can be applied to all time series. The valid choices depend on the metric_kind and the value_type of the original time series. Reduction can yield a time series with a different metric_kind or value_type than the input time series.Time series data must first be aligned (see per_series_aligner) in order to perform cross-time series reduction. If cross_series_reducer is specified, then per_series_aligner must be specified, and must not be ALIGN_NONE. An alignment_period must also be specified; otherwise, an error is returned.
    group_by_fields Sequence[str]
    The set of fields to preserve when cross_series_reducer is specified. The group_by_fields determine how the time series are partitioned into subsets prior to applying the aggregation operation. Each subset contains time series that have the same value for each of the grouping fields. Each individual time series is a member of exactly one subset. The cross_series_reducer is applied to each subset of time series. It is not possible to reduce across different resource types, so this field implicitly contains resource.type. Fields not specified in group_by_fields are aggregated away. If group_by_fields is not specified and all the time series have the same resource type, then the time series are aggregated into a single output time series. If cross_series_reducer is not defined, this field is ignored.
    per_series_aligner AggregationPerSeriesAligner
    An Aligner describes how to bring the data points in a single time series into temporal alignment. Except for ALIGN_NONE, all alignments cause all the data points in an alignment_period to be mathematically grouped together, resulting in a single data point for each alignment_period with end timestamp at the end of the period.Not all alignment operations may be applied to all time series. The valid choices depend on the metric_kind and value_type of the original time series. Alignment can change the metric_kind or the value_type of the time series.Time series data must be aligned in order to perform cross-time series reduction. If cross_series_reducer is specified, then per_series_aligner must be specified and not equal to ALIGN_NONE and alignment_period must be specified; otherwise, an error is returned.
    alignmentPeriod String
    The alignment_period specifies a time interval, in seconds, that is used to divide the data in all the time series into consistent blocks of time. This will be done before the per-series aligner can be applied to the data.The value must be at least 60 seconds. If a per-series aligner other than ALIGN_NONE is specified, this field is required or an error is returned. If no per-series aligner is specified, or the aligner ALIGN_NONE is specified, then this field is ignored.The maximum value of the alignment_period is 2 years, or 104 weeks.
    crossSeriesReducer "REDUCE_NONE" | "REDUCE_MEAN" | "REDUCE_MIN" | "REDUCE_MAX" | "REDUCE_SUM" | "REDUCE_STDDEV" | "REDUCE_COUNT" | "REDUCE_COUNT_TRUE" | "REDUCE_COUNT_FALSE" | "REDUCE_FRACTION_TRUE" | "REDUCE_PERCENTILE_99" | "REDUCE_PERCENTILE_95" | "REDUCE_PERCENTILE_50" | "REDUCE_PERCENTILE_05"
    The reduction operation to be used to combine time series into a single time series, where the value of each data point in the resulting series is a function of all the already aligned values in the input time series.Not all reducer operations can be applied to all time series. The valid choices depend on the metric_kind and the value_type of the original time series. Reduction can yield a time series with a different metric_kind or value_type than the input time series.Time series data must first be aligned (see per_series_aligner) in order to perform cross-time series reduction. If cross_series_reducer is specified, then per_series_aligner must be specified, and must not be ALIGN_NONE. An alignment_period must also be specified; otherwise, an error is returned.
    groupByFields List<String>
    The set of fields to preserve when cross_series_reducer is specified. The group_by_fields determine how the time series are partitioned into subsets prior to applying the aggregation operation. Each subset contains time series that have the same value for each of the grouping fields. Each individual time series is a member of exactly one subset. The cross_series_reducer is applied to each subset of time series. It is not possible to reduce across different resource types, so this field implicitly contains resource.type. Fields not specified in group_by_fields are aggregated away. If group_by_fields is not specified and all the time series have the same resource type, then the time series are aggregated into a single output time series. If cross_series_reducer is not defined, this field is ignored.
    perSeriesAligner "ALIGN_NONE" | "ALIGN_DELTA" | "ALIGN_RATE" | "ALIGN_INTERPOLATE" | "ALIGN_NEXT_OLDER" | "ALIGN_MIN" | "ALIGN_MAX" | "ALIGN_MEAN" | "ALIGN_COUNT" | "ALIGN_SUM" | "ALIGN_STDDEV" | "ALIGN_COUNT_TRUE" | "ALIGN_COUNT_FALSE" | "ALIGN_FRACTION_TRUE" | "ALIGN_PERCENTILE_99" | "ALIGN_PERCENTILE_95" | "ALIGN_PERCENTILE_50" | "ALIGN_PERCENTILE_05" | "ALIGN_PERCENT_CHANGE"
    An Aligner describes how to bring the data points in a single time series into temporal alignment. Except for ALIGN_NONE, all alignments cause all the data points in an alignment_period to be mathematically grouped together, resulting in a single data point for each alignment_period with end timestamp at the end of the period.Not all alignment operations may be applied to all time series. The valid choices depend on the metric_kind and value_type of the original time series. Alignment can change the metric_kind or the value_type of the time series.Time series data must be aligned in order to perform cross-time series reduction. If cross_series_reducer is specified, then per_series_aligner must be specified and not equal to ALIGN_NONE and alignment_period must be specified; otherwise, an error is returned.

    AggregationCrossSeriesReducer, AggregationCrossSeriesReducerArgs

    ReduceNone
    REDUCE_NONENo cross-time series reduction. The output of the Aligner is returned.
    ReduceMean
    REDUCE_MEANReduce by computing the mean value across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics with numeric or distribution values. The value_type of the output is DOUBLE.
    ReduceMin
    REDUCE_MINReduce by computing the minimum value across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics with numeric values. The value_type of the output is the same as the value_type of the input.
    ReduceMax
    REDUCE_MAXReduce by computing the maximum value across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics with numeric values. The value_type of the output is the same as the value_type of the input.
    ReduceSum
    REDUCE_SUMReduce by computing the sum across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics with numeric and distribution values. The value_type of the output is the same as the value_type of the input.
    ReduceStddev
    REDUCE_STDDEVReduce by computing the standard deviation across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics with numeric or distribution values. The value_type of the output is DOUBLE.
    ReduceCount
    REDUCE_COUNTReduce by computing the number of data points across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics of numeric, Boolean, distribution, and string value_type. The value_type of the output is INT64.
    ReduceCountTrue
    REDUCE_COUNT_TRUEReduce by computing the number of True-valued data points across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics of Boolean value_type. The value_type of the output is INT64.
    ReduceCountFalse
    REDUCE_COUNT_FALSEReduce by computing the number of False-valued data points across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics of Boolean value_type. The value_type of the output is INT64.
    ReduceFractionTrue
    REDUCE_FRACTION_TRUEReduce by computing the ratio of the number of True-valued data points to the total number of data points for each alignment period. This reducer is valid for DELTA and GAUGE metrics of Boolean value_type. The output value is in the range 0.0, 1.0 and has value_type DOUBLE.
    ReducePercentile99
    REDUCE_PERCENTILE_99Reduce by computing the 99th percentile (https://en.wikipedia.org/wiki/Percentile) of data points across time series for each alignment period. This reducer is valid for GAUGE and DELTA metrics of numeric and distribution type. The value of the output is DOUBLE.
    ReducePercentile95
    REDUCE_PERCENTILE_95Reduce by computing the 95th percentile (https://en.wikipedia.org/wiki/Percentile) of data points across time series for each alignment period. This reducer is valid for GAUGE and DELTA metrics of numeric and distribution type. The value of the output is DOUBLE.
    ReducePercentile50
    REDUCE_PERCENTILE_50Reduce by computing the 50th percentile (https://en.wikipedia.org/wiki/Percentile) of data points across time series for each alignment period. This reducer is valid for GAUGE and DELTA metrics of numeric and distribution type. The value of the output is DOUBLE.
    ReducePercentile05
    REDUCE_PERCENTILE_05Reduce by computing the 5th percentile (https://en.wikipedia.org/wiki/Percentile) of data points across time series for each alignment period. This reducer is valid for GAUGE and DELTA metrics of numeric and distribution type. The value of the output is DOUBLE.
    AggregationCrossSeriesReducerReduceNone
    REDUCE_NONENo cross-time series reduction. The output of the Aligner is returned.
    AggregationCrossSeriesReducerReduceMean
    REDUCE_MEANReduce by computing the mean value across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics with numeric or distribution values. The value_type of the output is DOUBLE.
    AggregationCrossSeriesReducerReduceMin
    REDUCE_MINReduce by computing the minimum value across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics with numeric values. The value_type of the output is the same as the value_type of the input.
    AggregationCrossSeriesReducerReduceMax
    REDUCE_MAXReduce by computing the maximum value across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics with numeric values. The value_type of the output is the same as the value_type of the input.
    AggregationCrossSeriesReducerReduceSum
    REDUCE_SUMReduce by computing the sum across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics with numeric and distribution values. The value_type of the output is the same as the value_type of the input.
    AggregationCrossSeriesReducerReduceStddev
    REDUCE_STDDEVReduce by computing the standard deviation across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics with numeric or distribution values. The value_type of the output is DOUBLE.
    AggregationCrossSeriesReducerReduceCount
    REDUCE_COUNTReduce by computing the number of data points across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics of numeric, Boolean, distribution, and string value_type. The value_type of the output is INT64.
    AggregationCrossSeriesReducerReduceCountTrue
    REDUCE_COUNT_TRUEReduce by computing the number of True-valued data points across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics of Boolean value_type. The value_type of the output is INT64.
    AggregationCrossSeriesReducerReduceCountFalse
    REDUCE_COUNT_FALSEReduce by computing the number of False-valued data points across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics of Boolean value_type. The value_type of the output is INT64.
    AggregationCrossSeriesReducerReduceFractionTrue
    REDUCE_FRACTION_TRUEReduce by computing the ratio of the number of True-valued data points to the total number of data points for each alignment period. This reducer is valid for DELTA and GAUGE metrics of Boolean value_type. The output value is in the range 0.0, 1.0 and has value_type DOUBLE.
    AggregationCrossSeriesReducerReducePercentile99
    REDUCE_PERCENTILE_99Reduce by computing the 99th percentile (https://en.wikipedia.org/wiki/Percentile) of data points across time series for each alignment period. This reducer is valid for GAUGE and DELTA metrics of numeric and distribution type. The value of the output is DOUBLE.
    AggregationCrossSeriesReducerReducePercentile95
    REDUCE_PERCENTILE_95Reduce by computing the 95th percentile (https://en.wikipedia.org/wiki/Percentile) of data points across time series for each alignment period. This reducer is valid for GAUGE and DELTA metrics of numeric and distribution type. The value of the output is DOUBLE.
    AggregationCrossSeriesReducerReducePercentile50
    REDUCE_PERCENTILE_50Reduce by computing the 50th percentile (https://en.wikipedia.org/wiki/Percentile) of data points across time series for each alignment period. This reducer is valid for GAUGE and DELTA metrics of numeric and distribution type. The value of the output is DOUBLE.
    AggregationCrossSeriesReducerReducePercentile05
    REDUCE_PERCENTILE_05Reduce by computing the 5th percentile (https://en.wikipedia.org/wiki/Percentile) of data points across time series for each alignment period. This reducer is valid for GAUGE and DELTA metrics of numeric and distribution type. The value of the output is DOUBLE.
    ReduceNone
    REDUCE_NONENo cross-time series reduction. The output of the Aligner is returned.
    ReduceMean
    REDUCE_MEANReduce by computing the mean value across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics with numeric or distribution values. The value_type of the output is DOUBLE.
    ReduceMin
    REDUCE_MINReduce by computing the minimum value across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics with numeric values. The value_type of the output is the same as the value_type of the input.
    ReduceMax
    REDUCE_MAXReduce by computing the maximum value across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics with numeric values. The value_type of the output is the same as the value_type of the input.
    ReduceSum
    REDUCE_SUMReduce by computing the sum across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics with numeric and distribution values. The value_type of the output is the same as the value_type of the input.
    ReduceStddev
    REDUCE_STDDEVReduce by computing the standard deviation across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics with numeric or distribution values. The value_type of the output is DOUBLE.
    ReduceCount
    REDUCE_COUNTReduce by computing the number of data points across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics of numeric, Boolean, distribution, and string value_type. The value_type of the output is INT64.
    ReduceCountTrue
    REDUCE_COUNT_TRUEReduce by computing the number of True-valued data points across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics of Boolean value_type. The value_type of the output is INT64.
    ReduceCountFalse
    REDUCE_COUNT_FALSEReduce by computing the number of False-valued data points across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics of Boolean value_type. The value_type of the output is INT64.
    ReduceFractionTrue
    REDUCE_FRACTION_TRUEReduce by computing the ratio of the number of True-valued data points to the total number of data points for each alignment period. This reducer is valid for DELTA and GAUGE metrics of Boolean value_type. The output value is in the range 0.0, 1.0 and has value_type DOUBLE.
    ReducePercentile99
    REDUCE_PERCENTILE_99Reduce by computing the 99th percentile (https://en.wikipedia.org/wiki/Percentile) of data points across time series for each alignment period. This reducer is valid for GAUGE and DELTA metrics of numeric and distribution type. The value of the output is DOUBLE.
    ReducePercentile95
    REDUCE_PERCENTILE_95Reduce by computing the 95th percentile (https://en.wikipedia.org/wiki/Percentile) of data points across time series for each alignment period. This reducer is valid for GAUGE and DELTA metrics of numeric and distribution type. The value of the output is DOUBLE.
    ReducePercentile50
    REDUCE_PERCENTILE_50Reduce by computing the 50th percentile (https://en.wikipedia.org/wiki/Percentile) of data points across time series for each alignment period. This reducer is valid for GAUGE and DELTA metrics of numeric and distribution type. The value of the output is DOUBLE.
    ReducePercentile05
    REDUCE_PERCENTILE_05Reduce by computing the 5th percentile (https://en.wikipedia.org/wiki/Percentile) of data points across time series for each alignment period. This reducer is valid for GAUGE and DELTA metrics of numeric and distribution type. The value of the output is DOUBLE.
    ReduceNone
    REDUCE_NONENo cross-time series reduction. The output of the Aligner is returned.
    ReduceMean
    REDUCE_MEANReduce by computing the mean value across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics with numeric or distribution values. The value_type of the output is DOUBLE.
    ReduceMin
    REDUCE_MINReduce by computing the minimum value across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics with numeric values. The value_type of the output is the same as the value_type of the input.
    ReduceMax
    REDUCE_MAXReduce by computing the maximum value across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics with numeric values. The value_type of the output is the same as the value_type of the input.
    ReduceSum
    REDUCE_SUMReduce by computing the sum across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics with numeric and distribution values. The value_type of the output is the same as the value_type of the input.
    ReduceStddev
    REDUCE_STDDEVReduce by computing the standard deviation across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics with numeric or distribution values. The value_type of the output is DOUBLE.
    ReduceCount
    REDUCE_COUNTReduce by computing the number of data points across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics of numeric, Boolean, distribution, and string value_type. The value_type of the output is INT64.
    ReduceCountTrue
    REDUCE_COUNT_TRUEReduce by computing the number of True-valued data points across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics of Boolean value_type. The value_type of the output is INT64.
    ReduceCountFalse
    REDUCE_COUNT_FALSEReduce by computing the number of False-valued data points across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics of Boolean value_type. The value_type of the output is INT64.
    ReduceFractionTrue
    REDUCE_FRACTION_TRUEReduce by computing the ratio of the number of True-valued data points to the total number of data points for each alignment period. This reducer is valid for DELTA and GAUGE metrics of Boolean value_type. The output value is in the range 0.0, 1.0 and has value_type DOUBLE.
    ReducePercentile99
    REDUCE_PERCENTILE_99Reduce by computing the 99th percentile (https://en.wikipedia.org/wiki/Percentile) of data points across time series for each alignment period. This reducer is valid for GAUGE and DELTA metrics of numeric and distribution type. The value of the output is DOUBLE.
    ReducePercentile95
    REDUCE_PERCENTILE_95Reduce by computing the 95th percentile (https://en.wikipedia.org/wiki/Percentile) of data points across time series for each alignment period. This reducer is valid for GAUGE and DELTA metrics of numeric and distribution type. The value of the output is DOUBLE.
    ReducePercentile50
    REDUCE_PERCENTILE_50Reduce by computing the 50th percentile (https://en.wikipedia.org/wiki/Percentile) of data points across time series for each alignment period. This reducer is valid for GAUGE and DELTA metrics of numeric and distribution type. The value of the output is DOUBLE.
    ReducePercentile05
    REDUCE_PERCENTILE_05Reduce by computing the 5th percentile (https://en.wikipedia.org/wiki/Percentile) of data points across time series for each alignment period. This reducer is valid for GAUGE and DELTA metrics of numeric and distribution type. The value of the output is DOUBLE.
    REDUCE_NONE
    REDUCE_NONENo cross-time series reduction. The output of the Aligner is returned.
    REDUCE_MEAN
    REDUCE_MEANReduce by computing the mean value across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics with numeric or distribution values. The value_type of the output is DOUBLE.
    REDUCE_MIN
    REDUCE_MINReduce by computing the minimum value across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics with numeric values. The value_type of the output is the same as the value_type of the input.
    REDUCE_MAX
    REDUCE_MAXReduce by computing the maximum value across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics with numeric values. The value_type of the output is the same as the value_type of the input.
    REDUCE_SUM
    REDUCE_SUMReduce by computing the sum across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics with numeric and distribution values. The value_type of the output is the same as the value_type of the input.
    REDUCE_STDDEV
    REDUCE_STDDEVReduce by computing the standard deviation across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics with numeric or distribution values. The value_type of the output is DOUBLE.
    REDUCE_COUNT
    REDUCE_COUNTReduce by computing the number of data points across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics of numeric, Boolean, distribution, and string value_type. The value_type of the output is INT64.
    REDUCE_COUNT_TRUE
    REDUCE_COUNT_TRUEReduce by computing the number of True-valued data points across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics of Boolean value_type. The value_type of the output is INT64.
    REDUCE_COUNT_FALSE
    REDUCE_COUNT_FALSEReduce by computing the number of False-valued data points across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics of Boolean value_type. The value_type of the output is INT64.
    REDUCE_FRACTION_TRUE
    REDUCE_FRACTION_TRUEReduce by computing the ratio of the number of True-valued data points to the total number of data points for each alignment period. This reducer is valid for DELTA and GAUGE metrics of Boolean value_type. The output value is in the range 0.0, 1.0 and has value_type DOUBLE.
    REDUCE_PERCENTILE99
    REDUCE_PERCENTILE_99Reduce by computing the 99th percentile (https://en.wikipedia.org/wiki/Percentile) of data points across time series for each alignment period. This reducer is valid for GAUGE and DELTA metrics of numeric and distribution type. The value of the output is DOUBLE.
    REDUCE_PERCENTILE95
    REDUCE_PERCENTILE_95Reduce by computing the 95th percentile (https://en.wikipedia.org/wiki/Percentile) of data points across time series for each alignment period. This reducer is valid for GAUGE and DELTA metrics of numeric and distribution type. The value of the output is DOUBLE.
    REDUCE_PERCENTILE50
    REDUCE_PERCENTILE_50Reduce by computing the 50th percentile (https://en.wikipedia.org/wiki/Percentile) of data points across time series for each alignment period. This reducer is valid for GAUGE and DELTA metrics of numeric and distribution type. The value of the output is DOUBLE.
    REDUCE_PERCENTILE05
    REDUCE_PERCENTILE_05Reduce by computing the 5th percentile (https://en.wikipedia.org/wiki/Percentile) of data points across time series for each alignment period. This reducer is valid for GAUGE and DELTA metrics of numeric and distribution type. The value of the output is DOUBLE.
    "REDUCE_NONE"
    REDUCE_NONENo cross-time series reduction. The output of the Aligner is returned.
    "REDUCE_MEAN"
    REDUCE_MEANReduce by computing the mean value across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics with numeric or distribution values. The value_type of the output is DOUBLE.
    "REDUCE_MIN"
    REDUCE_MINReduce by computing the minimum value across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics with numeric values. The value_type of the output is the same as the value_type of the input.
    "REDUCE_MAX"
    REDUCE_MAXReduce by computing the maximum value across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics with numeric values. The value_type of the output is the same as the value_type of the input.
    "REDUCE_SUM"
    REDUCE_SUMReduce by computing the sum across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics with numeric and distribution values. The value_type of the output is the same as the value_type of the input.
    "REDUCE_STDDEV"
    REDUCE_STDDEVReduce by computing the standard deviation across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics with numeric or distribution values. The value_type of the output is DOUBLE.
    "REDUCE_COUNT"
    REDUCE_COUNTReduce by computing the number of data points across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics of numeric, Boolean, distribution, and string value_type. The value_type of the output is INT64.
    "REDUCE_COUNT_TRUE"
    REDUCE_COUNT_TRUEReduce by computing the number of True-valued data points across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics of Boolean value_type. The value_type of the output is INT64.
    "REDUCE_COUNT_FALSE"
    REDUCE_COUNT_FALSEReduce by computing the number of False-valued data points across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics of Boolean value_type. The value_type of the output is INT64.
    "REDUCE_FRACTION_TRUE"
    REDUCE_FRACTION_TRUEReduce by computing the ratio of the number of True-valued data points to the total number of data points for each alignment period. This reducer is valid for DELTA and GAUGE metrics of Boolean value_type. The output value is in the range 0.0, 1.0 and has value_type DOUBLE.
    "REDUCE_PERCENTILE_99"
    REDUCE_PERCENTILE_99Reduce by computing the 99th percentile (https://en.wikipedia.org/wiki/Percentile) of data points across time series for each alignment period. This reducer is valid for GAUGE and DELTA metrics of numeric and distribution type. The value of the output is DOUBLE.
    "REDUCE_PERCENTILE_95"
    REDUCE_PERCENTILE_95Reduce by computing the 95th percentile (https://en.wikipedia.org/wiki/Percentile) of data points across time series for each alignment period. This reducer is valid for GAUGE and DELTA metrics of numeric and distribution type. The value of the output is DOUBLE.
    "REDUCE_PERCENTILE_50"
    REDUCE_PERCENTILE_50Reduce by computing the 50th percentile (https://en.wikipedia.org/wiki/Percentile) of data points across time series for each alignment period. This reducer is valid for GAUGE and DELTA metrics of numeric and distribution type. The value of the output is DOUBLE.
    "REDUCE_PERCENTILE_05"
    REDUCE_PERCENTILE_05Reduce by computing the 5th percentile (https://en.wikipedia.org/wiki/Percentile) of data points across time series for each alignment period. This reducer is valid for GAUGE and DELTA metrics of numeric and distribution type. The value of the output is DOUBLE.

    AggregationFunction, AggregationFunctionArgs

    Type string
    The type of aggregation function, must be one of the following: "none" - no function. "percentile" - APPROX_QUANTILES() - 1 parameter numeric value "average" - AVG() "count" - COUNT() "count-distinct" - COUNT(DISTINCT) "count-distinct-approx" - APPROX_COUNT_DISTINCT() "max" - MAX() "min" - MIN() "sum" - SUM()
    Parameters List<Pulumi.GoogleNative.Monitoring.V1.Inputs.Parameter>
    Optional. Parameters applied to the aggregation function. Only used for functions that require them.
    Type string
    The type of aggregation function, must be one of the following: "none" - no function. "percentile" - APPROX_QUANTILES() - 1 parameter numeric value "average" - AVG() "count" - COUNT() "count-distinct" - COUNT(DISTINCT) "count-distinct-approx" - APPROX_COUNT_DISTINCT() "max" - MAX() "min" - MIN() "sum" - SUM()
    Parameters []Parameter
    Optional. Parameters applied to the aggregation function. Only used for functions that require them.
    type String
    The type of aggregation function, must be one of the following: "none" - no function. "percentile" - APPROX_QUANTILES() - 1 parameter numeric value "average" - AVG() "count" - COUNT() "count-distinct" - COUNT(DISTINCT) "count-distinct-approx" - APPROX_COUNT_DISTINCT() "max" - MAX() "min" - MIN() "sum" - SUM()
    parameters List<Parameter>
    Optional. Parameters applied to the aggregation function. Only used for functions that require them.
    type string
    The type of aggregation function, must be one of the following: "none" - no function. "percentile" - APPROX_QUANTILES() - 1 parameter numeric value "average" - AVG() "count" - COUNT() "count-distinct" - COUNT(DISTINCT) "count-distinct-approx" - APPROX_COUNT_DISTINCT() "max" - MAX() "min" - MIN() "sum" - SUM()
    parameters Parameter[]
    Optional. Parameters applied to the aggregation function. Only used for functions that require them.
    type str
    The type of aggregation function, must be one of the following: "none" - no function. "percentile" - APPROX_QUANTILES() - 1 parameter numeric value "average" - AVG() "count" - COUNT() "count-distinct" - COUNT(DISTINCT) "count-distinct-approx" - APPROX_COUNT_DISTINCT() "max" - MAX() "min" - MIN() "sum" - SUM()
    parameters Sequence[Parameter]
    Optional. Parameters applied to the aggregation function. Only used for functions that require them.
    type String
    The type of aggregation function, must be one of the following: "none" - no function. "percentile" - APPROX_QUANTILES() - 1 parameter numeric value "average" - AVG() "count" - COUNT() "count-distinct" - COUNT(DISTINCT) "count-distinct-approx" - APPROX_COUNT_DISTINCT() "max" - MAX() "min" - MIN() "sum" - SUM()
    parameters List<Property Map>
    Optional. Parameters applied to the aggregation function. Only used for functions that require them.

    AggregationFunctionResponse, AggregationFunctionResponseArgs

    Parameters List<Pulumi.GoogleNative.Monitoring.V1.Inputs.ParameterResponse>
    Optional. Parameters applied to the aggregation function. Only used for functions that require them.
    Type string
    The type of aggregation function, must be one of the following: "none" - no function. "percentile" - APPROX_QUANTILES() - 1 parameter numeric value "average" - AVG() "count" - COUNT() "count-distinct" - COUNT(DISTINCT) "count-distinct-approx" - APPROX_COUNT_DISTINCT() "max" - MAX() "min" - MIN() "sum" - SUM()
    Parameters []ParameterResponse
    Optional. Parameters applied to the aggregation function. Only used for functions that require them.
    Type string
    The type of aggregation function, must be one of the following: "none" - no function. "percentile" - APPROX_QUANTILES() - 1 parameter numeric value "average" - AVG() "count" - COUNT() "count-distinct" - COUNT(DISTINCT) "count-distinct-approx" - APPROX_COUNT_DISTINCT() "max" - MAX() "min" - MIN() "sum" - SUM()
    parameters List<ParameterResponse>
    Optional. Parameters applied to the aggregation function. Only used for functions that require them.
    type String
    The type of aggregation function, must be one of the following: "none" - no function. "percentile" - APPROX_QUANTILES() - 1 parameter numeric value "average" - AVG() "count" - COUNT() "count-distinct" - COUNT(DISTINCT) "count-distinct-approx" - APPROX_COUNT_DISTINCT() "max" - MAX() "min" - MIN() "sum" - SUM()
    parameters ParameterResponse[]
    Optional. Parameters applied to the aggregation function. Only used for functions that require them.
    type string
    The type of aggregation function, must be one of the following: "none" - no function. "percentile" - APPROX_QUANTILES() - 1 parameter numeric value "average" - AVG() "count" - COUNT() "count-distinct" - COUNT(DISTINCT) "count-distinct-approx" - APPROX_COUNT_DISTINCT() "max" - MAX() "min" - MIN() "sum" - SUM()
    parameters Sequence[ParameterResponse]
    Optional. Parameters applied to the aggregation function. Only used for functions that require them.
    type str
    The type of aggregation function, must be one of the following: "none" - no function. "percentile" - APPROX_QUANTILES() - 1 parameter numeric value "average" - AVG() "count" - COUNT() "count-distinct" - COUNT(DISTINCT) "count-distinct-approx" - APPROX_COUNT_DISTINCT() "max" - MAX() "min" - MIN() "sum" - SUM()
    parameters List<Property Map>
    Optional. Parameters applied to the aggregation function. Only used for functions that require them.
    type String
    The type of aggregation function, must be one of the following: "none" - no function. "percentile" - APPROX_QUANTILES() - 1 parameter numeric value "average" - AVG() "count" - COUNT() "count-distinct" - COUNT(DISTINCT) "count-distinct-approx" - APPROX_COUNT_DISTINCT() "max" - MAX() "min" - MIN() "sum" - SUM()

    AggregationPerSeriesAligner, AggregationPerSeriesAlignerArgs

    AlignNone
    ALIGN_NONENo alignment. Raw data is returned. Not valid if cross-series reduction is requested. The value_type of the result is the same as the value_type of the input.
    AlignDelta
    ALIGN_DELTAAlign and convert to DELTA. The output is delta = y1 - y0.This alignment is valid for CUMULATIVE and DELTA metrics. If the selected alignment period results in periods with no data, then the aligned value for such a period is created by interpolation. The value_type of the aligned result is the same as the value_type of the input.
    AlignRate
    ALIGN_RATEAlign and convert to a rate. The result is computed as rate = (y1 - y0)/(t1 - t0), or "delta over time". Think of this aligner as providing the slope of the line that passes through the value at the start and at the end of the alignment_period.This aligner is valid for CUMULATIVE and DELTA metrics with numeric values. If the selected alignment period results in periods with no data, then the aligned value for such a period is created by interpolation. The output is a GAUGE metric with value_type DOUBLE.If, by "rate", you mean "percentage change", see the ALIGN_PERCENT_CHANGE aligner instead.
    AlignInterpolate
    ALIGN_INTERPOLATEAlign by interpolating between adjacent points around the alignment period boundary. This aligner is valid for GAUGE metrics with numeric values. The value_type of the aligned result is the same as the value_type of the input.
    AlignNextOlder
    ALIGN_NEXT_OLDERAlign by moving the most recent data point before the end of the alignment period to the boundary at the end of the alignment period. This aligner is valid for GAUGE metrics. The value_type of the aligned result is the same as the value_type of the input.
    AlignMin
    ALIGN_MINAlign the time series by returning the minimum value in each alignment period. This aligner is valid for GAUGE and DELTA metrics with numeric values. The value_type of the aligned result is the same as the value_type of the input.
    AlignMax
    ALIGN_MAXAlign the time series by returning the maximum value in each alignment period. This aligner is valid for GAUGE and DELTA metrics with numeric values. The value_type of the aligned result is the same as the value_type of the input.
    AlignMean
    ALIGN_MEANAlign the time series by returning the mean value in each alignment period. This aligner is valid for GAUGE and DELTA metrics with numeric values. The value_type of the aligned result is DOUBLE.
    AlignCount
    ALIGN_COUNTAlign the time series by returning the number of values in each alignment period. This aligner is valid for GAUGE and DELTA metrics with numeric or Boolean values. The value_type of the aligned result is INT64.
    AlignSum
    ALIGN_SUMAlign the time series by returning the sum of the values in each alignment period. This aligner is valid for GAUGE and DELTA metrics with numeric and distribution values. The value_type of the aligned result is the same as the value_type of the input.
    AlignStddev
    ALIGN_STDDEVAlign the time series by returning the standard deviation of the values in each alignment period. This aligner is valid for GAUGE and DELTA metrics with numeric values. The value_type of the output is DOUBLE.
    AlignCountTrue
    ALIGN_COUNT_TRUEAlign the time series by returning the number of True values in each alignment period. This aligner is valid for GAUGE metrics with Boolean values. The value_type of the output is INT64.
    AlignCountFalse
    ALIGN_COUNT_FALSEAlign the time series by returning the number of False values in each alignment period. This aligner is valid for GAUGE metrics with Boolean values. The value_type of the output is INT64.
    AlignFractionTrue
    ALIGN_FRACTION_TRUEAlign the time series by returning the ratio of the number of True values to the total number of values in each alignment period. This aligner is valid for GAUGE metrics with Boolean values. The output value is in the range 0.0, 1.0 and has value_type DOUBLE.
    AlignPercentile99
    ALIGN_PERCENTILE_99Align the time series by using percentile aggregation (https://en.wikipedia.org/wiki/Percentile). The resulting data point in each alignment period is the 99th percentile of all data points in the period. This aligner is valid for GAUGE and DELTA metrics with distribution values. The output is a GAUGE metric with value_type DOUBLE.
    AlignPercentile95
    ALIGN_PERCENTILE_95Align the time series by using percentile aggregation (https://en.wikipedia.org/wiki/Percentile). The resulting data point in each alignment period is the 95th percentile of all data points in the period. This aligner is valid for GAUGE and DELTA metrics with distribution values. The output is a GAUGE metric with value_type DOUBLE.
    AlignPercentile50
    ALIGN_PERCENTILE_50Align the time series by using percentile aggregation (https://en.wikipedia.org/wiki/Percentile). The resulting data point in each alignment period is the 50th percentile of all data points in the period. This aligner is valid for GAUGE and DELTA metrics with distribution values. The output is a GAUGE metric with value_type DOUBLE.
    AlignPercentile05
    ALIGN_PERCENTILE_05Align the time series by using percentile aggregation (https://en.wikipedia.org/wiki/Percentile). The resulting data point in each alignment period is the 5th percentile of all data points in the period. This aligner is valid for GAUGE and DELTA metrics with distribution values. The output is a GAUGE metric with value_type DOUBLE.
    AlignPercentChange
    ALIGN_PERCENT_CHANGEAlign and convert to a percentage change. This aligner is valid for GAUGE and DELTA metrics with numeric values. This alignment returns ((current - previous)/previous) * 100, where the value of previous is determined based on the alignment_period.If the values of current and previous are both 0, then the returned value is 0. If only previous is 0, the returned value is infinity.A 10-minute moving mean is computed at each point of the alignment period prior to the above calculation to smooth the metric and prevent false positives from very short-lived spikes. The moving mean is only applicable for data whose values are >= 0. Any values < 0 are treated as a missing datapoint, and are ignored. While DELTA metrics are accepted by this alignment, special care should be taken that the values for the metric will always be positive. The output is a GAUGE metric with value_type DOUBLE.
    AggregationPerSeriesAlignerAlignNone
    ALIGN_NONENo alignment. Raw data is returned. Not valid if cross-series reduction is requested. The value_type of the result is the same as the value_type of the input.
    AggregationPerSeriesAlignerAlignDelta
    ALIGN_DELTAAlign and convert to DELTA. The output is delta = y1 - y0.This alignment is valid for CUMULATIVE and DELTA metrics. If the selected alignment period results in periods with no data, then the aligned value for such a period is created by interpolation. The value_type of the aligned result is the same as the value_type of the input.
    AggregationPerSeriesAlignerAlignRate
    ALIGN_RATEAlign and convert to a rate. The result is computed as rate = (y1 - y0)/(t1 - t0), or "delta over time". Think of this aligner as providing the slope of the line that passes through the value at the start and at the end of the alignment_period.This aligner is valid for CUMULATIVE and DELTA metrics with numeric values. If the selected alignment period results in periods with no data, then the aligned value for such a period is created by interpolation. The output is a GAUGE metric with value_type DOUBLE.If, by "rate", you mean "percentage change", see the ALIGN_PERCENT_CHANGE aligner instead.
    AggregationPerSeriesAlignerAlignInterpolate
    ALIGN_INTERPOLATEAlign by interpolating between adjacent points around the alignment period boundary. This aligner is valid for GAUGE metrics with numeric values. The value_type of the aligned result is the same as the value_type of the input.
    AggregationPerSeriesAlignerAlignNextOlder
    ALIGN_NEXT_OLDERAlign by moving the most recent data point before the end of the alignment period to the boundary at the end of the alignment period. This aligner is valid for GAUGE metrics. The value_type of the aligned result is the same as the value_type of the input.
    AggregationPerSeriesAlignerAlignMin
    ALIGN_MINAlign the time series by returning the minimum value in each alignment period. This aligner is valid for GAUGE and DELTA metrics with numeric values. The value_type of the aligned result is the same as the value_type of the input.
    AggregationPerSeriesAlignerAlignMax
    ALIGN_MAXAlign the time series by returning the maximum value in each alignment period. This aligner is valid for GAUGE and DELTA metrics with numeric values. The value_type of the aligned result is the same as the value_type of the input.
    AggregationPerSeriesAlignerAlignMean
    ALIGN_MEANAlign the time series by returning the mean value in each alignment period. This aligner is valid for GAUGE and DELTA metrics with numeric values. The value_type of the aligned result is DOUBLE.
    AggregationPerSeriesAlignerAlignCount
    ALIGN_COUNTAlign the time series by returning the number of values in each alignment period. This aligner is valid for GAUGE and DELTA metrics with numeric or Boolean values. The value_type of the aligned result is INT64.
    AggregationPerSeriesAlignerAlignSum
    ALIGN_SUMAlign the time series by returning the sum of the values in each alignment period. This aligner is valid for GAUGE and DELTA metrics with numeric and distribution values. The value_type of the aligned result is the same as the value_type of the input.
    AggregationPerSeriesAlignerAlignStddev
    ALIGN_STDDEVAlign the time series by returning the standard deviation of the values in each alignment period. This aligner is valid for GAUGE and DELTA metrics with numeric values. The value_type of the output is DOUBLE.
    AggregationPerSeriesAlignerAlignCountTrue
    ALIGN_COUNT_TRUEAlign the time series by returning the number of True values in each alignment period. This aligner is valid for GAUGE metrics with Boolean values. The value_type of the output is INT64.
    AggregationPerSeriesAlignerAlignCountFalse
    ALIGN_COUNT_FALSEAlign the time series by returning the number of False values in each alignment period. This aligner is valid for GAUGE metrics with Boolean values. The value_type of the output is INT64.
    AggregationPerSeriesAlignerAlignFractionTrue
    ALIGN_FRACTION_TRUEAlign the time series by returning the ratio of the number of True values to the total number of values in each alignment period. This aligner is valid for GAUGE metrics with Boolean values. The output value is in the range 0.0, 1.0 and has value_type DOUBLE.
    AggregationPerSeriesAlignerAlignPercentile99
    ALIGN_PERCENTILE_99Align the time series by using percentile aggregation (https://en.wikipedia.org/wiki/Percentile). The resulting data point in each alignment period is the 99th percentile of all data points in the period. This aligner is valid for GAUGE and DELTA metrics with distribution values. The output is a GAUGE metric with value_type DOUBLE.
    AggregationPerSeriesAlignerAlignPercentile95
    ALIGN_PERCENTILE_95Align the time series by using percentile aggregation (https://en.wikipedia.org/wiki/Percentile). The resulting data point in each alignment period is the 95th percentile of all data points in the period. This aligner is valid for GAUGE and DELTA metrics with distribution values. The output is a GAUGE metric with value_type DOUBLE.
    AggregationPerSeriesAlignerAlignPercentile50
    ALIGN_PERCENTILE_50Align the time series by using percentile aggregation (https://en.wikipedia.org/wiki/Percentile). The resulting data point in each alignment period is the 50th percentile of all data points in the period. This aligner is valid for GAUGE and DELTA metrics with distribution values. The output is a GAUGE metric with value_type DOUBLE.
    AggregationPerSeriesAlignerAlignPercentile05
    ALIGN_PERCENTILE_05Align the time series by using percentile aggregation (https://en.wikipedia.org/wiki/Percentile). The resulting data point in each alignment period is the 5th percentile of all data points in the period. This aligner is valid for GAUGE and DELTA metrics with distribution values. The output is a GAUGE metric with value_type DOUBLE.
    AggregationPerSeriesAlignerAlignPercentChange
    ALIGN_PERCENT_CHANGEAlign and convert to a percentage change. This aligner is valid for GAUGE and DELTA metrics with numeric values. This alignment returns ((current - previous)/previous) * 100, where the value of previous is determined based on the alignment_period.If the values of current and previous are both 0, then the returned value is 0. If only previous is 0, the returned value is infinity.A 10-minute moving mean is computed at each point of the alignment period prior to the above calculation to smooth the metric and prevent false positives from very short-lived spikes. The moving mean is only applicable for data whose values are >= 0. Any values < 0 are treated as a missing datapoint, and are ignored. While DELTA metrics are accepted by this alignment, special care should be taken that the values for the metric will always be positive. The output is a GAUGE metric with value_type DOUBLE.
    AlignNone
    ALIGN_NONENo alignment. Raw data is returned. Not valid if cross-series reduction is requested. The value_type of the result is the same as the value_type of the input.
    AlignDelta
    ALIGN_DELTAAlign and convert to DELTA. The output is delta = y1 - y0.This alignment is valid for CUMULATIVE and DELTA metrics. If the selected alignment period results in periods with no data, then the aligned value for such a period is created by interpolation. The value_type of the aligned result is the same as the value_type of the input.
    AlignRate
    ALIGN_RATEAlign and convert to a rate. The result is computed as rate = (y1 - y0)/(t1 - t0), or "delta over time". Think of this aligner as providing the slope of the line that passes through the value at the start and at the end of the alignment_period.This aligner is valid for CUMULATIVE and DELTA metrics with numeric values. If the selected alignment period results in periods with no data, then the aligned value for such a period is created by interpolation. The output is a GAUGE metric with value_type DOUBLE.If, by "rate", you mean "percentage change", see the ALIGN_PERCENT_CHANGE aligner instead.
    AlignInterpolate
    ALIGN_INTERPOLATEAlign by interpolating between adjacent points around the alignment period boundary. This aligner is valid for GAUGE metrics with numeric values. The value_type of the aligned result is the same as the value_type of the input.
    AlignNextOlder
    ALIGN_NEXT_OLDERAlign by moving the most recent data point before the end of the alignment period to the boundary at the end of the alignment period. This aligner is valid for GAUGE metrics. The value_type of the aligned result is the same as the value_type of the input.
    AlignMin
    ALIGN_MINAlign the time series by returning the minimum value in each alignment period. This aligner is valid for GAUGE and DELTA metrics with numeric values. The value_type of the aligned result is the same as the value_type of the input.
    AlignMax
    ALIGN_MAXAlign the time series by returning the maximum value in each alignment period. This aligner is valid for GAUGE and DELTA metrics with numeric values. The value_type of the aligned result is the same as the value_type of the input.
    AlignMean
    ALIGN_MEANAlign the time series by returning the mean value in each alignment period. This aligner is valid for GAUGE and DELTA metrics with numeric values. The value_type of the aligned result is DOUBLE.
    AlignCount
    ALIGN_COUNTAlign the time series by returning the number of values in each alignment period. This aligner is valid for GAUGE and DELTA metrics with numeric or Boolean values. The value_type of the aligned result is INT64.
    AlignSum
    ALIGN_SUMAlign the time series by returning the sum of the values in each alignment period. This aligner is valid for GAUGE and DELTA metrics with numeric and distribution values. The value_type of the aligned result is the same as the value_type of the input.
    AlignStddev
    ALIGN_STDDEVAlign the time series by returning the standard deviation of the values in each alignment period. This aligner is valid for GAUGE and DELTA metrics with numeric values. The value_type of the output is DOUBLE.
    AlignCountTrue
    ALIGN_COUNT_TRUEAlign the time series by returning the number of True values in each alignment period. This aligner is valid for GAUGE metrics with Boolean values. The value_type of the output is INT64.
    AlignCountFalse
    ALIGN_COUNT_FALSEAlign the time series by returning the number of False values in each alignment period. This aligner is valid for GAUGE metrics with Boolean values. The value_type of the output is INT64.
    AlignFractionTrue
    ALIGN_FRACTION_TRUEAlign the time series by returning the ratio of the number of True values to the total number of values in each alignment period. This aligner is valid for GAUGE metrics with Boolean values. The output value is in the range 0.0, 1.0 and has value_type DOUBLE.
    AlignPercentile99
    ALIGN_PERCENTILE_99Align the time series by using percentile aggregation (https://en.wikipedia.org/wiki/Percentile). The resulting data point in each alignment period is the 99th percentile of all data points in the period. This aligner is valid for GAUGE and DELTA metrics with distribution values. The output is a GAUGE metric with value_type DOUBLE.
    AlignPercentile95
    ALIGN_PERCENTILE_95Align the time series by using percentile aggregation (https://en.wikipedia.org/wiki/Percentile). The resulting data point in each alignment period is the 95th percentile of all data points in the period. This aligner is valid for GAUGE and DELTA metrics with distribution values. The output is a GAUGE metric with value_type DOUBLE.
    AlignPercentile50
    ALIGN_PERCENTILE_50Align the time series by using percentile aggregation (https://en.wikipedia.org/wiki/Percentile). The resulting data point in each alignment period is the 50th percentile of all data points in the period. This aligner is valid for GAUGE and DELTA metrics with distribution values. The output is a GAUGE metric with value_type DOUBLE.
    AlignPercentile05
    ALIGN_PERCENTILE_05Align the time series by using percentile aggregation (https://en.wikipedia.org/wiki/Percentile). The resulting data point in each alignment period is the 5th percentile of all data points in the period. This aligner is valid for GAUGE and DELTA metrics with distribution values. The output is a GAUGE metric with value_type DOUBLE.
    AlignPercentChange
    ALIGN_PERCENT_CHANGEAlign and convert to a percentage change. This aligner is valid for GAUGE and DELTA metrics with numeric values. This alignment returns ((current - previous)/previous) * 100, where the value of previous is determined based on the alignment_period.If the values of current and previous are both 0, then the returned value is 0. If only previous is 0, the returned value is infinity.A 10-minute moving mean is computed at each point of the alignment period prior to the above calculation to smooth the metric and prevent false positives from very short-lived spikes. The moving mean is only applicable for data whose values are >= 0. Any values < 0 are treated as a missing datapoint, and are ignored. While DELTA metrics are accepted by this alignment, special care should be taken that the values for the metric will always be positive. The output is a GAUGE metric with value_type DOUBLE.
    AlignNone
    ALIGN_NONENo alignment. Raw data is returned. Not valid if cross-series reduction is requested. The value_type of the result is the same as the value_type of the input.
    AlignDelta
    ALIGN_DELTAAlign and convert to DELTA. The output is delta = y1 - y0.This alignment is valid for CUMULATIVE and DELTA metrics. If the selected alignment period results in periods with no data, then the aligned value for such a period is created by interpolation. The value_type of the aligned result is the same as the value_type of the input.
    AlignRate
    ALIGN_RATEAlign and convert to a rate. The result is computed as rate = (y1 - y0)/(t1 - t0), or "delta over time". Think of this aligner as providing the slope of the line that passes through the value at the start and at the end of the alignment_period.This aligner is valid for CUMULATIVE and DELTA metrics with numeric values. If the selected alignment period results in periods with no data, then the aligned value for such a period is created by interpolation. The output is a GAUGE metric with value_type DOUBLE.If, by "rate", you mean "percentage change", see the ALIGN_PERCENT_CHANGE aligner instead.
    AlignInterpolate
    ALIGN_INTERPOLATEAlign by interpolating between adjacent points around the alignment period boundary. This aligner is valid for GAUGE metrics with numeric values. The value_type of the aligned result is the same as the value_type of the input.
    AlignNextOlder
    ALIGN_NEXT_OLDERAlign by moving the most recent data point before the end of the alignment period to the boundary at the end of the alignment period. This aligner is valid for GAUGE metrics. The value_type of the aligned result is the same as the value_type of the input.
    AlignMin
    ALIGN_MINAlign the time series by returning the minimum value in each alignment period. This aligner is valid for GAUGE and DELTA metrics with numeric values. The value_type of the aligned result is the same as the value_type of the input.
    AlignMax
    ALIGN_MAXAlign the time series by returning the maximum value in each alignment period. This aligner is valid for GAUGE and DELTA metrics with numeric values. The value_type of the aligned result is the same as the value_type of the input.
    AlignMean
    ALIGN_MEANAlign the time series by returning the mean value in each alignment period. This aligner is valid for GAUGE and DELTA metrics with numeric values. The value_type of the aligned result is DOUBLE.
    AlignCount
    ALIGN_COUNTAlign the time series by returning the number of values in each alignment period. This aligner is valid for GAUGE and DELTA metrics with numeric or Boolean values. The value_type of the aligned result is INT64.
    AlignSum
    ALIGN_SUMAlign the time series by returning the sum of the values in each alignment period. This aligner is valid for GAUGE and DELTA metrics with numeric and distribution values. The value_type of the aligned result is the same as the value_type of the input.
    AlignStddev
    ALIGN_STDDEVAlign the time series by returning the standard deviation of the values in each alignment period. This aligner is valid for GAUGE and DELTA metrics with numeric values. The value_type of the output is DOUBLE.
    AlignCountTrue
    ALIGN_COUNT_TRUEAlign the time series by returning the number of True values in each alignment period. This aligner is valid for GAUGE metrics with Boolean values. The value_type of the output is INT64.
    AlignCountFalse
    ALIGN_COUNT_FALSEAlign the time series by returning the number of False values in each alignment period. This aligner is valid for GAUGE metrics with Boolean values. The value_type of the output is INT64.
    AlignFractionTrue
    ALIGN_FRACTION_TRUEAlign the time series by returning the ratio of the number of True values to the total number of values in each alignment period. This aligner is valid for GAUGE metrics with Boolean values. The output value is in the range 0.0, 1.0 and has value_type DOUBLE.
    AlignPercentile99
    ALIGN_PERCENTILE_99Align the time series by using percentile aggregation (https://en.wikipedia.org/wiki/Percentile). The resulting data point in each alignment period is the 99th percentile of all data points in the period. This aligner is valid for GAUGE and DELTA metrics with distribution values. The output is a GAUGE metric with value_type DOUBLE.
    AlignPercentile95
    ALIGN_PERCENTILE_95Align the time series by using percentile aggregation (https://en.wikipedia.org/wiki/Percentile). The resulting data point in each alignment period is the 95th percentile of all data points in the period. This aligner is valid for GAUGE and DELTA metrics with distribution values. The output is a GAUGE metric with value_type DOUBLE.
    AlignPercentile50
    ALIGN_PERCENTILE_50Align the time series by using percentile aggregation (https://en.wikipedia.org/wiki/Percentile). The resulting data point in each alignment period is the 50th percentile of all data points in the period. This aligner is valid for GAUGE and DELTA metrics with distribution values. The output is a GAUGE metric with value_type DOUBLE.
    AlignPercentile05
    ALIGN_PERCENTILE_05Align the time series by using percentile aggregation (https://en.wikipedia.org/wiki/Percentile). The resulting data point in each alignment period is the 5th percentile of all data points in the period. This aligner is valid for GAUGE and DELTA metrics with distribution values. The output is a GAUGE metric with value_type DOUBLE.
    AlignPercentChange
    ALIGN_PERCENT_CHANGEAlign and convert to a percentage change. This aligner is valid for GAUGE and DELTA metrics with numeric values. This alignment returns ((current - previous)/previous) * 100, where the value of previous is determined based on the alignment_period.If the values of current and previous are both 0, then the returned value is 0. If only previous is 0, the returned value is infinity.A 10-minute moving mean is computed at each point of the alignment period prior to the above calculation to smooth the metric and prevent false positives from very short-lived spikes. The moving mean is only applicable for data whose values are >= 0. Any values < 0 are treated as a missing datapoint, and are ignored. While DELTA metrics are accepted by this alignment, special care should be taken that the values for the metric will always be positive. The output is a GAUGE metric with value_type DOUBLE.
    ALIGN_NONE
    ALIGN_NONENo alignment. Raw data is returned. Not valid if cross-series reduction is requested. The value_type of the result is the same as the value_type of the input.
    ALIGN_DELTA
    ALIGN_DELTAAlign and convert to DELTA. The output is delta = y1 - y0.This alignment is valid for CUMULATIVE and DELTA metrics. If the selected alignment period results in periods with no data, then the aligned value for such a period is created by interpolation. The value_type of the aligned result is the same as the value_type of the input.
    ALIGN_RATE
    ALIGN_RATEAlign and convert to a rate. The result is computed as rate = (y1 - y0)/(t1 - t0), or "delta over time". Think of this aligner as providing the slope of the line that passes through the value at the start and at the end of the alignment_period.This aligner is valid for CUMULATIVE and DELTA metrics with numeric values. If the selected alignment period results in periods with no data, then the aligned value for such a period is created by interpolation. The output is a GAUGE metric with value_type DOUBLE.If, by "rate", you mean "percentage change", see the ALIGN_PERCENT_CHANGE aligner instead.
    ALIGN_INTERPOLATE
    ALIGN_INTERPOLATEAlign by interpolating between adjacent points around the alignment period boundary. This aligner is valid for GAUGE metrics with numeric values. The value_type of the aligned result is the same as the value_type of the input.
    ALIGN_NEXT_OLDER
    ALIGN_NEXT_OLDERAlign by moving the most recent data point before the end of the alignment period to the boundary at the end of the alignment period. This aligner is valid for GAUGE metrics. The value_type of the aligned result is the same as the value_type of the input.
    ALIGN_MIN
    ALIGN_MINAlign the time series by returning the minimum value in each alignment period. This aligner is valid for GAUGE and DELTA metrics with numeric values. The value_type of the aligned result is the same as the value_type of the input.
    ALIGN_MAX
    ALIGN_MAXAlign the time series by returning the maximum value in each alignment period. This aligner is valid for GAUGE and DELTA metrics with numeric values. The value_type of the aligned result is the same as the value_type of the input.
    ALIGN_MEAN
    ALIGN_MEANAlign the time series by returning the mean value in each alignment period. This aligner is valid for GAUGE and DELTA metrics with numeric values. The value_type of the aligned result is DOUBLE.
    ALIGN_COUNT
    ALIGN_COUNTAlign the time series by returning the number of values in each alignment period. This aligner is valid for GAUGE and DELTA metrics with numeric or Boolean values. The value_type of the aligned result is INT64.
    ALIGN_SUM
    ALIGN_SUMAlign the time series by returning the sum of the values in each alignment period. This aligner is valid for GAUGE and DELTA metrics with numeric and distribution values. The value_type of the aligned result is the same as the value_type of the input.
    ALIGN_STDDEV
    ALIGN_STDDEVAlign the time series by returning the standard deviation of the values in each alignment period. This aligner is valid for GAUGE and DELTA metrics with numeric values. The value_type of the output is DOUBLE.
    ALIGN_COUNT_TRUE
    ALIGN_COUNT_TRUEAlign the time series by returning the number of True values in each alignment period. This aligner is valid for GAUGE metrics with Boolean values. The value_type of the output is INT64.
    ALIGN_COUNT_FALSE
    ALIGN_COUNT_FALSEAlign the time series by returning the number of False values in each alignment period. This aligner is valid for GAUGE metrics with Boolean values. The value_type of the output is INT64.
    ALIGN_FRACTION_TRUE
    ALIGN_FRACTION_TRUEAlign the time series by returning the ratio of the number of True values to the total number of values in each alignment period. This aligner is valid for GAUGE metrics with Boolean values. The output value is in the range 0.0, 1.0 and has value_type DOUBLE.
    ALIGN_PERCENTILE99
    ALIGN_PERCENTILE_99Align the time series by using percentile aggregation (https://en.wikipedia.org/wiki/Percentile). The resulting data point in each alignment period is the 99th percentile of all data points in the period. This aligner is valid for GAUGE and DELTA metrics with distribution values. The output is a GAUGE metric with value_type DOUBLE.
    ALIGN_PERCENTILE95
    ALIGN_PERCENTILE_95Align the time series by using percentile aggregation (https://en.wikipedia.org/wiki/Percentile). The resulting data point in each alignment period is the 95th percentile of all data points in the period. This aligner is valid for GAUGE and DELTA metrics with distribution values. The output is a GAUGE metric with value_type DOUBLE.
    ALIGN_PERCENTILE50
    ALIGN_PERCENTILE_50Align the time series by using percentile aggregation (https://en.wikipedia.org/wiki/Percentile). The resulting data point in each alignment period is the 50th percentile of all data points in the period. This aligner is valid for GAUGE and DELTA metrics with distribution values. The output is a GAUGE metric with value_type DOUBLE.
    ALIGN_PERCENTILE05
    ALIGN_PERCENTILE_05Align the time series by using percentile aggregation (https://en.wikipedia.org/wiki/Percentile). The resulting data point in each alignment period is the 5th percentile of all data points in the period. This aligner is valid for GAUGE and DELTA metrics with distribution values. The output is a GAUGE metric with value_type DOUBLE.
    ALIGN_PERCENT_CHANGE
    ALIGN_PERCENT_CHANGEAlign and convert to a percentage change. This aligner is valid for GAUGE and DELTA metrics with numeric values. This alignment returns ((current - previous)/previous) * 100, where the value of previous is determined based on the alignment_period.If the values of current and previous are both 0, then the returned value is 0. If only previous is 0, the returned value is infinity.A 10-minute moving mean is computed at each point of the alignment period prior to the above calculation to smooth the metric and prevent false positives from very short-lived spikes. The moving mean is only applicable for data whose values are >= 0. Any values < 0 are treated as a missing datapoint, and are ignored. While DELTA metrics are accepted by this alignment, special care should be taken that the values for the metric will always be positive. The output is a GAUGE metric with value_type DOUBLE.
    "ALIGN_NONE"
    ALIGN_NONENo alignment. Raw data is returned. Not valid if cross-series reduction is requested. The value_type of the result is the same as the value_type of the input.
    "ALIGN_DELTA"
    ALIGN_DELTAAlign and convert to DELTA. The output is delta = y1 - y0.This alignment is valid for CUMULATIVE and DELTA metrics. If the selected alignment period results in periods with no data, then the aligned value for such a period is created by interpolation. The value_type of the aligned result is the same as the value_type of the input.
    "ALIGN_RATE"
    ALIGN_RATEAlign and convert to a rate. The result is computed as rate = (y1 - y0)/(t1 - t0), or "delta over time". Think of this aligner as providing the slope of the line that passes through the value at the start and at the end of the alignment_period.This aligner is valid for CUMULATIVE and DELTA metrics with numeric values. If the selected alignment period results in periods with no data, then the aligned value for such a period is created by interpolation. The output is a GAUGE metric with value_type DOUBLE.If, by "rate", you mean "percentage change", see the ALIGN_PERCENT_CHANGE aligner instead.
    "ALIGN_INTERPOLATE"
    ALIGN_INTERPOLATEAlign by interpolating between adjacent points around the alignment period boundary. This aligner is valid for GAUGE metrics with numeric values. The value_type of the aligned result is the same as the value_type of the input.
    "ALIGN_NEXT_OLDER"
    ALIGN_NEXT_OLDERAlign by moving the most recent data point before the end of the alignment period to the boundary at the end of the alignment period. This aligner is valid for GAUGE metrics. The value_type of the aligned result is the same as the value_type of the input.
    "ALIGN_MIN"
    ALIGN_MINAlign the time series by returning the minimum value in each alignment period. This aligner is valid for GAUGE and DELTA metrics with numeric values. The value_type of the aligned result is the same as the value_type of the input.
    "ALIGN_MAX"
    ALIGN_MAXAlign the time series by returning the maximum value in each alignment period. This aligner is valid for GAUGE and DELTA metrics with numeric values. The value_type of the aligned result is the same as the value_type of the input.
    "ALIGN_MEAN"
    ALIGN_MEANAlign the time series by returning the mean value in each alignment period. This aligner is valid for GAUGE and DELTA metrics with numeric values. The value_type of the aligned result is DOUBLE.
    "ALIGN_COUNT"
    ALIGN_COUNTAlign the time series by returning the number of values in each alignment period. This aligner is valid for GAUGE and DELTA metrics with numeric or Boolean values. The value_type of the aligned result is INT64.
    "ALIGN_SUM"
    ALIGN_SUMAlign the time series by returning the sum of the values in each alignment period. This aligner is valid for GAUGE and DELTA metrics with numeric and distribution values. The value_type of the aligned result is the same as the value_type of the input.
    "ALIGN_STDDEV"
    ALIGN_STDDEVAlign the time series by returning the standard deviation of the values in each alignment period. This aligner is valid for GAUGE and DELTA metrics with numeric values. The value_type of the output is DOUBLE.
    "ALIGN_COUNT_TRUE"
    ALIGN_COUNT_TRUEAlign the time series by returning the number of True values in each alignment period. This aligner is valid for GAUGE metrics with Boolean values. The value_type of the output is INT64.
    "ALIGN_COUNT_FALSE"
    ALIGN_COUNT_FALSEAlign the time series by returning the number of False values in each alignment period. This aligner is valid for GAUGE metrics with Boolean values. The value_type of the output is INT64.
    "ALIGN_FRACTION_TRUE"
    ALIGN_FRACTION_TRUEAlign the time series by returning the ratio of the number of True values to the total number of values in each alignment period. This aligner is valid for GAUGE metrics with Boolean values. The output value is in the range 0.0, 1.0 and has value_type DOUBLE.
    "ALIGN_PERCENTILE_99"
    ALIGN_PERCENTILE_99Align the time series by using percentile aggregation (https://en.wikipedia.org/wiki/Percentile). The resulting data point in each alignment period is the 99th percentile of all data points in the period. This aligner is valid for GAUGE and DELTA metrics with distribution values. The output is a GAUGE metric with value_type DOUBLE.
    "ALIGN_PERCENTILE_95"
    ALIGN_PERCENTILE_95Align the time series by using percentile aggregation (https://en.wikipedia.org/wiki/Percentile). The resulting data point in each alignment period is the 95th percentile of all data points in the period. This aligner is valid for GAUGE and DELTA metrics with distribution values. The output is a GAUGE metric with value_type DOUBLE.
    "ALIGN_PERCENTILE_50"
    ALIGN_PERCENTILE_50Align the time series by using percentile aggregation (https://en.wikipedia.org/wiki/Percentile). The resulting data point in each alignment period is the 50th percentile of all data points in the period. This aligner is valid for GAUGE and DELTA metrics with distribution values. The output is a GAUGE metric with value_type DOUBLE.
    "ALIGN_PERCENTILE_05"
    ALIGN_PERCENTILE_05Align the time series by using percentile aggregation (https://en.wikipedia.org/wiki/Percentile). The resulting data point in each alignment period is the 5th percentile of all data points in the period. This aligner is valid for GAUGE and DELTA metrics with distribution values. The output is a GAUGE metric with value_type DOUBLE.
    "ALIGN_PERCENT_CHANGE"
    ALIGN_PERCENT_CHANGEAlign and convert to a percentage change. This aligner is valid for GAUGE and DELTA metrics with numeric values. This alignment returns ((current - previous)/previous) * 100, where the value of previous is determined based on the alignment_period.If the values of current and previous are both 0, then the returned value is 0. If only previous is 0, the returned value is infinity.A 10-minute moving mean is computed at each point of the alignment period prior to the above calculation to smooth the metric and prevent false positives from very short-lived spikes. The moving mean is only applicable for data whose values are >= 0. Any values < 0 are treated as a missing datapoint, and are ignored. While DELTA metrics are accepted by this alignment, special care should be taken that the values for the metric will always be positive. The output is a GAUGE metric with value_type DOUBLE.

    AggregationResponse, AggregationResponseArgs

    AlignmentPeriod string
    The alignment_period specifies a time interval, in seconds, that is used to divide the data in all the time series into consistent blocks of time. This will be done before the per-series aligner can be applied to the data.The value must be at least 60 seconds. If a per-series aligner other than ALIGN_NONE is specified, this field is required or an error is returned. If no per-series aligner is specified, or the aligner ALIGN_NONE is specified, then this field is ignored.The maximum value of the alignment_period is 2 years, or 104 weeks.
    CrossSeriesReducer string
    The reduction operation to be used to combine time series into a single time series, where the value of each data point in the resulting series is a function of all the already aligned values in the input time series.Not all reducer operations can be applied to all time series. The valid choices depend on the metric_kind and the value_type of the original time series. Reduction can yield a time series with a different metric_kind or value_type than the input time series.Time series data must first be aligned (see per_series_aligner) in order to perform cross-time series reduction. If cross_series_reducer is specified, then per_series_aligner must be specified, and must not be ALIGN_NONE. An alignment_period must also be specified; otherwise, an error is returned.
    GroupByFields List<string>
    The set of fields to preserve when cross_series_reducer is specified. The group_by_fields determine how the time series are partitioned into subsets prior to applying the aggregation operation. Each subset contains time series that have the same value for each of the grouping fields. Each individual time series is a member of exactly one subset. The cross_series_reducer is applied to each subset of time series. It is not possible to reduce across different resource types, so this field implicitly contains resource.type. Fields not specified in group_by_fields are aggregated away. If group_by_fields is not specified and all the time series have the same resource type, then the time series are aggregated into a single output time series. If cross_series_reducer is not defined, this field is ignored.
    PerSeriesAligner string
    An Aligner describes how to bring the data points in a single time series into temporal alignment. Except for ALIGN_NONE, all alignments cause all the data points in an alignment_period to be mathematically grouped together, resulting in a single data point for each alignment_period with end timestamp at the end of the period.Not all alignment operations may be applied to all time series. The valid choices depend on the metric_kind and value_type of the original time series. Alignment can change the metric_kind or the value_type of the time series.Time series data must be aligned in order to perform cross-time series reduction. If cross_series_reducer is specified, then per_series_aligner must be specified and not equal to ALIGN_NONE and alignment_period must be specified; otherwise, an error is returned.
    AlignmentPeriod string
    The alignment_period specifies a time interval, in seconds, that is used to divide the data in all the time series into consistent blocks of time. This will be done before the per-series aligner can be applied to the data.The value must be at least 60 seconds. If a per-series aligner other than ALIGN_NONE is specified, this field is required or an error is returned. If no per-series aligner is specified, or the aligner ALIGN_NONE is specified, then this field is ignored.The maximum value of the alignment_period is 2 years, or 104 weeks.
    CrossSeriesReducer string
    The reduction operation to be used to combine time series into a single time series, where the value of each data point in the resulting series is a function of all the already aligned values in the input time series.Not all reducer operations can be applied to all time series. The valid choices depend on the metric_kind and the value_type of the original time series. Reduction can yield a time series with a different metric_kind or value_type than the input time series.Time series data must first be aligned (see per_series_aligner) in order to perform cross-time series reduction. If cross_series_reducer is specified, then per_series_aligner must be specified, and must not be ALIGN_NONE. An alignment_period must also be specified; otherwise, an error is returned.
    GroupByFields []string
    The set of fields to preserve when cross_series_reducer is specified. The group_by_fields determine how the time series are partitioned into subsets prior to applying the aggregation operation. Each subset contains time series that have the same value for each of the grouping fields. Each individual time series is a member of exactly one subset. The cross_series_reducer is applied to each subset of time series. It is not possible to reduce across different resource types, so this field implicitly contains resource.type. Fields not specified in group_by_fields are aggregated away. If group_by_fields is not specified and all the time series have the same resource type, then the time series are aggregated into a single output time series. If cross_series_reducer is not defined, this field is ignored.
    PerSeriesAligner string
    An Aligner describes how to bring the data points in a single time series into temporal alignment. Except for ALIGN_NONE, all alignments cause all the data points in an alignment_period to be mathematically grouped together, resulting in a single data point for each alignment_period with end timestamp at the end of the period.Not all alignment operations may be applied to all time series. The valid choices depend on the metric_kind and value_type of the original time series. Alignment can change the metric_kind or the value_type of the time series.Time series data must be aligned in order to perform cross-time series reduction. If cross_series_reducer is specified, then per_series_aligner must be specified and not equal to ALIGN_NONE and alignment_period must be specified; otherwise, an error is returned.
    alignmentPeriod String
    The alignment_period specifies a time interval, in seconds, that is used to divide the data in all the time series into consistent blocks of time. This will be done before the per-series aligner can be applied to the data.The value must be at least 60 seconds. If a per-series aligner other than ALIGN_NONE is specified, this field is required or an error is returned. If no per-series aligner is specified, or the aligner ALIGN_NONE is specified, then this field is ignored.The maximum value of the alignment_period is 2 years, or 104 weeks.
    crossSeriesReducer String
    The reduction operation to be used to combine time series into a single time series, where the value of each data point in the resulting series is a function of all the already aligned values in the input time series.Not all reducer operations can be applied to all time series. The valid choices depend on the metric_kind and the value_type of the original time series. Reduction can yield a time series with a different metric_kind or value_type than the input time series.Time series data must first be aligned (see per_series_aligner) in order to perform cross-time series reduction. If cross_series_reducer is specified, then per_series_aligner must be specified, and must not be ALIGN_NONE. An alignment_period must also be specified; otherwise, an error is returned.
    groupByFields List<String>
    The set of fields to preserve when cross_series_reducer is specified. The group_by_fields determine how the time series are partitioned into subsets prior to applying the aggregation operation. Each subset contains time series that have the same value for each of the grouping fields. Each individual time series is a member of exactly one subset. The cross_series_reducer is applied to each subset of time series. It is not possible to reduce across different resource types, so this field implicitly contains resource.type. Fields not specified in group_by_fields are aggregated away. If group_by_fields is not specified and all the time series have the same resource type, then the time series are aggregated into a single output time series. If cross_series_reducer is not defined, this field is ignored.
    perSeriesAligner String
    An Aligner describes how to bring the data points in a single time series into temporal alignment. Except for ALIGN_NONE, all alignments cause all the data points in an alignment_period to be mathematically grouped together, resulting in a single data point for each alignment_period with end timestamp at the end of the period.Not all alignment operations may be applied to all time series. The valid choices depend on the metric_kind and value_type of the original time series. Alignment can change the metric_kind or the value_type of the time series.Time series data must be aligned in order to perform cross-time series reduction. If cross_series_reducer is specified, then per_series_aligner must be specified and not equal to ALIGN_NONE and alignment_period must be specified; otherwise, an error is returned.
    alignmentPeriod string
    The alignment_period specifies a time interval, in seconds, that is used to divide the data in all the time series into consistent blocks of time. This will be done before the per-series aligner can be applied to the data.The value must be at least 60 seconds. If a per-series aligner other than ALIGN_NONE is specified, this field is required or an error is returned. If no per-series aligner is specified, or the aligner ALIGN_NONE is specified, then this field is ignored.The maximum value of the alignment_period is 2 years, or 104 weeks.
    crossSeriesReducer string
    The reduction operation to be used to combine time series into a single time series, where the value of each data point in the resulting series is a function of all the already aligned values in the input time series.Not all reducer operations can be applied to all time series. The valid choices depend on the metric_kind and the value_type of the original time series. Reduction can yield a time series with a different metric_kind or value_type than the input time series.Time series data must first be aligned (see per_series_aligner) in order to perform cross-time series reduction. If cross_series_reducer is specified, then per_series_aligner must be specified, and must not be ALIGN_NONE. An alignment_period must also be specified; otherwise, an error is returned.
    groupByFields string[]
    The set of fields to preserve when cross_series_reducer is specified. The group_by_fields determine how the time series are partitioned into subsets prior to applying the aggregation operation. Each subset contains time series that have the same value for each of the grouping fields. Each individual time series is a member of exactly one subset. The cross_series_reducer is applied to each subset of time series. It is not possible to reduce across different resource types, so this field implicitly contains resource.type. Fields not specified in group_by_fields are aggregated away. If group_by_fields is not specified and all the time series have the same resource type, then the time series are aggregated into a single output time series. If cross_series_reducer is not defined, this field is ignored.
    perSeriesAligner string
    An Aligner describes how to bring the data points in a single time series into temporal alignment. Except for ALIGN_NONE, all alignments cause all the data points in an alignment_period to be mathematically grouped together, resulting in a single data point for each alignment_period with end timestamp at the end of the period.Not all alignment operations may be applied to all time series. The valid choices depend on the metric_kind and value_type of the original time series. Alignment can change the metric_kind or the value_type of the time series.Time series data must be aligned in order to perform cross-time series reduction. If cross_series_reducer is specified, then per_series_aligner must be specified and not equal to ALIGN_NONE and alignment_period must be specified; otherwise, an error is returned.
    alignment_period str
    The alignment_period specifies a time interval, in seconds, that is used to divide the data in all the time series into consistent blocks of time. This will be done before the per-series aligner can be applied to the data.The value must be at least 60 seconds. If a per-series aligner other than ALIGN_NONE is specified, this field is required or an error is returned. If no per-series aligner is specified, or the aligner ALIGN_NONE is specified, then this field is ignored.The maximum value of the alignment_period is 2 years, or 104 weeks.
    cross_series_reducer str
    The reduction operation to be used to combine time series into a single time series, where the value of each data point in the resulting series is a function of all the already aligned values in the input time series.Not all reducer operations can be applied to all time series. The valid choices depend on the metric_kind and the value_type of the original time series. Reduction can yield a time series with a different metric_kind or value_type than the input time series.Time series data must first be aligned (see per_series_aligner) in order to perform cross-time series reduction. If cross_series_reducer is specified, then per_series_aligner must be specified, and must not be ALIGN_NONE. An alignment_period must also be specified; otherwise, an error is returned.
    group_by_fields Sequence[str]
    The set of fields to preserve when cross_series_reducer is specified. The group_by_fields determine how the time series are partitioned into subsets prior to applying the aggregation operation. Each subset contains time series that have the same value for each of the grouping fields. Each individual time series is a member of exactly one subset. The cross_series_reducer is applied to each subset of time series. It is not possible to reduce across different resource types, so this field implicitly contains resource.type. Fields not specified in group_by_fields are aggregated away. If group_by_fields is not specified and all the time series have the same resource type, then the time series are aggregated into a single output time series. If cross_series_reducer is not defined, this field is ignored.
    per_series_aligner str
    An Aligner describes how to bring the data points in a single time series into temporal alignment. Except for ALIGN_NONE, all alignments cause all the data points in an alignment_period to be mathematically grouped together, resulting in a single data point for each alignment_period with end timestamp at the end of the period.Not all alignment operations may be applied to all time series. The valid choices depend on the metric_kind and value_type of the original time series. Alignment can change the metric_kind or the value_type of the time series.Time series data must be aligned in order to perform cross-time series reduction. If cross_series_reducer is specified, then per_series_aligner must be specified and not equal to ALIGN_NONE and alignment_period must be specified; otherwise, an error is returned.
    alignmentPeriod String
    The alignment_period specifies a time interval, in seconds, that is used to divide the data in all the time series into consistent blocks of time. This will be done before the per-series aligner can be applied to the data.The value must be at least 60 seconds. If a per-series aligner other than ALIGN_NONE is specified, this field is required or an error is returned. If no per-series aligner is specified, or the aligner ALIGN_NONE is specified, then this field is ignored.The maximum value of the alignment_period is 2 years, or 104 weeks.
    crossSeriesReducer String
    The reduction operation to be used to combine time series into a single time series, where the value of each data point in the resulting series is a function of all the already aligned values in the input time series.Not all reducer operations can be applied to all time series. The valid choices depend on the metric_kind and the value_type of the original time series. Reduction can yield a time series with a different metric_kind or value_type than the input time series.Time series data must first be aligned (see per_series_aligner) in order to perform cross-time series reduction. If cross_series_reducer is specified, then per_series_aligner must be specified, and must not be ALIGN_NONE. An alignment_period must also be specified; otherwise, an error is returned.
    groupByFields List<String>
    The set of fields to preserve when cross_series_reducer is specified. The group_by_fields determine how the time series are partitioned into subsets prior to applying the aggregation operation. Each subset contains time series that have the same value for each of the grouping fields. Each individual time series is a member of exactly one subset. The cross_series_reducer is applied to each subset of time series. It is not possible to reduce across different resource types, so this field implicitly contains resource.type. Fields not specified in group_by_fields are aggregated away. If group_by_fields is not specified and all the time series have the same resource type, then the time series are aggregated into a single output time series. If cross_series_reducer is not defined, this field is ignored.
    perSeriesAligner String
    An Aligner describes how to bring the data points in a single time series into temporal alignment. Except for ALIGN_NONE, all alignments cause all the data points in an alignment_period to be mathematically grouped together, resulting in a single data point for each alignment_period with end timestamp at the end of the period.Not all alignment operations may be applied to all time series. The valid choices depend on the metric_kind and value_type of the original time series. Alignment can change the metric_kind or the value_type of the time series.Time series data must be aligned in order to perform cross-time series reduction. If cross_series_reducer is specified, then per_series_aligner must be specified and not equal to ALIGN_NONE and alignment_period must be specified; otherwise, an error is returned.

    AlertChart, AlertChartArgs

    Name string
    The resource name of the alert policy. The format is: projects/[PROJECT_ID_OR_NUMBER]/alertPolicies/[ALERT_POLICY_ID]
    Name string
    The resource name of the alert policy. The format is: projects/[PROJECT_ID_OR_NUMBER]/alertPolicies/[ALERT_POLICY_ID]
    name String
    The resource name of the alert policy. The format is: projects/[PROJECT_ID_OR_NUMBER]/alertPolicies/[ALERT_POLICY_ID]
    name string
    The resource name of the alert policy. The format is: projects/[PROJECT_ID_OR_NUMBER]/alertPolicies/[ALERT_POLICY_ID]
    name str
    The resource name of the alert policy. The format is: projects/[PROJECT_ID_OR_NUMBER]/alertPolicies/[ALERT_POLICY_ID]
    name String
    The resource name of the alert policy. The format is: projects/[PROJECT_ID_OR_NUMBER]/alertPolicies/[ALERT_POLICY_ID]

    AlertChartResponse, AlertChartResponseArgs

    Name string
    The resource name of the alert policy. The format is: projects/[PROJECT_ID_OR_NUMBER]/alertPolicies/[ALERT_POLICY_ID]
    Name string
    The resource name of the alert policy. The format is: projects/[PROJECT_ID_OR_NUMBER]/alertPolicies/[ALERT_POLICY_ID]
    name String
    The resource name of the alert policy. The format is: projects/[PROJECT_ID_OR_NUMBER]/alertPolicies/[ALERT_POLICY_ID]
    name string
    The resource name of the alert policy. The format is: projects/[PROJECT_ID_OR_NUMBER]/alertPolicies/[ALERT_POLICY_ID]
    name str
    The resource name of the alert policy. The format is: projects/[PROJECT_ID_OR_NUMBER]/alertPolicies/[ALERT_POLICY_ID]
    name String
    The resource name of the alert policy. The format is: projects/[PROJECT_ID_OR_NUMBER]/alertPolicies/[ALERT_POLICY_ID]

    Axis, AxisArgs

    Label string
    The label of the axis.
    Scale Pulumi.GoogleNative.Monitoring.V1.AxisScale
    The axis scale. By default, a linear scale is used.
    Label string
    The label of the axis.
    Scale AxisScale
    The axis scale. By default, a linear scale is used.
    label String
    The label of the axis.
    scale AxisScale
    The axis scale. By default, a linear scale is used.
    label string
    The label of the axis.
    scale AxisScale
    The axis scale. By default, a linear scale is used.
    label str
    The label of the axis.
    scale AxisScale
    The axis scale. By default, a linear scale is used.
    label String
    The label of the axis.
    scale "SCALE_UNSPECIFIED" | "LINEAR" | "LOG10"
    The axis scale. By default, a linear scale is used.

    AxisResponse, AxisResponseArgs

    Label string
    The label of the axis.
    Scale string
    The axis scale. By default, a linear scale is used.
    Label string
    The label of the axis.
    Scale string
    The axis scale. By default, a linear scale is used.
    label String
    The label of the axis.
    scale String
    The axis scale. By default, a linear scale is used.
    label string
    The label of the axis.
    scale string
    The axis scale. By default, a linear scale is used.
    label str
    The label of the axis.
    scale str
    The axis scale. By default, a linear scale is used.
    label String
    The label of the axis.
    scale String
    The axis scale. By default, a linear scale is used.

    AxisScale, AxisScaleArgs

    ScaleUnspecified
    SCALE_UNSPECIFIEDScale is unspecified. The view will default to LINEAR.
    Linear
    LINEARLinear scale.
    Log10
    LOG10Logarithmic scale (base 10).
    AxisScaleScaleUnspecified
    SCALE_UNSPECIFIEDScale is unspecified. The view will default to LINEAR.
    AxisScaleLinear
    LINEARLinear scale.
    AxisScaleLog10
    LOG10Logarithmic scale (base 10).
    ScaleUnspecified
    SCALE_UNSPECIFIEDScale is unspecified. The view will default to LINEAR.
    Linear
    LINEARLinear scale.
    Log10
    LOG10Logarithmic scale (base 10).
    ScaleUnspecified
    SCALE_UNSPECIFIEDScale is unspecified. The view will default to LINEAR.
    Linear
    LINEARLinear scale.
    Log10
    LOG10Logarithmic scale (base 10).
    SCALE_UNSPECIFIED
    SCALE_UNSPECIFIEDScale is unspecified. The view will default to LINEAR.
    LINEAR
    LINEARLinear scale.
    LOG10
    LOG10Logarithmic scale (base 10).
    "SCALE_UNSPECIFIED"
    SCALE_UNSPECIFIEDScale is unspecified. The view will default to LINEAR.
    "LINEAR"
    LINEARLinear scale.
    "LOG10"
    LOG10Logarithmic scale (base 10).

    Breakdown, BreakdownArgs

    AggregationFunction Pulumi.GoogleNative.Monitoring.V1.Inputs.AggregationFunction
    The Aggregation function is applied across all data in each breakdown created.
    Column string
    The name of the column in the dataset containing the breakdown values.
    Limit int
    A limit to the number of breakdowns. If set to zero then all possible breakdowns are applied. The list of breakdowns is dependent on the value of the sort_order field.
    SortOrder Pulumi.GoogleNative.Monitoring.V1.BreakdownSortOrder
    The sort order is applied to the values of the breakdown column.
    AggregationFunction AggregationFunction
    The Aggregation function is applied across all data in each breakdown created.
    Column string
    The name of the column in the dataset containing the breakdown values.
    Limit int
    A limit to the number of breakdowns. If set to zero then all possible breakdowns are applied. The list of breakdowns is dependent on the value of the sort_order field.
    SortOrder BreakdownSortOrder
    The sort order is applied to the values of the breakdown column.
    aggregationFunction AggregationFunction
    The Aggregation function is applied across all data in each breakdown created.
    column String
    The name of the column in the dataset containing the breakdown values.
    limit Integer
    A limit to the number of breakdowns. If set to zero then all possible breakdowns are applied. The list of breakdowns is dependent on the value of the sort_order field.
    sortOrder BreakdownSortOrder
    The sort order is applied to the values of the breakdown column.
    aggregationFunction AggregationFunction
    The Aggregation function is applied across all data in each breakdown created.
    column string
    The name of the column in the dataset containing the breakdown values.
    limit number
    A limit to the number of breakdowns. If set to zero then all possible breakdowns are applied. The list of breakdowns is dependent on the value of the sort_order field.
    sortOrder BreakdownSortOrder
    The sort order is applied to the values of the breakdown column.
    aggregation_function AggregationFunction
    The Aggregation function is applied across all data in each breakdown created.
    column str
    The name of the column in the dataset containing the breakdown values.
    limit int
    A limit to the number of breakdowns. If set to zero then all possible breakdowns are applied. The list of breakdowns is dependent on the value of the sort_order field.
    sort_order BreakdownSortOrder
    The sort order is applied to the values of the breakdown column.
    aggregationFunction Property Map
    The Aggregation function is applied across all data in each breakdown created.
    column String
    The name of the column in the dataset containing the breakdown values.
    limit Number
    A limit to the number of breakdowns. If set to zero then all possible breakdowns are applied. The list of breakdowns is dependent on the value of the sort_order field.
    sortOrder "SORT_ORDER_UNSPECIFIED" | "SORT_ORDER_NONE" | "SORT_ORDER_ASCENDING" | "SORT_ORDER_DESCENDING"
    The sort order is applied to the values of the breakdown column.

    BreakdownResponse, BreakdownResponseArgs

    AggregationFunction Pulumi.GoogleNative.Monitoring.V1.Inputs.AggregationFunctionResponse
    The Aggregation function is applied across all data in each breakdown created.
    Column string
    The name of the column in the dataset containing the breakdown values.
    Limit int
    A limit to the number of breakdowns. If set to zero then all possible breakdowns are applied. The list of breakdowns is dependent on the value of the sort_order field.
    SortOrder string
    The sort order is applied to the values of the breakdown column.
    AggregationFunction AggregationFunctionResponse
    The Aggregation function is applied across all data in each breakdown created.
    Column string
    The name of the column in the dataset containing the breakdown values.
    Limit int
    A limit to the number of breakdowns. If set to zero then all possible breakdowns are applied. The list of breakdowns is dependent on the value of the sort_order field.
    SortOrder string
    The sort order is applied to the values of the breakdown column.
    aggregationFunction AggregationFunctionResponse
    The Aggregation function is applied across all data in each breakdown created.
    column String
    The name of the column in the dataset containing the breakdown values.
    limit Integer
    A limit to the number of breakdowns. If set to zero then all possible breakdowns are applied. The list of breakdowns is dependent on the value of the sort_order field.
    sortOrder String
    The sort order is applied to the values of the breakdown column.
    aggregationFunction AggregationFunctionResponse
    The Aggregation function is applied across all data in each breakdown created.
    column string
    The name of the column in the dataset containing the breakdown values.
    limit number
    A limit to the number of breakdowns. If set to zero then all possible breakdowns are applied. The list of breakdowns is dependent on the value of the sort_order field.
    sortOrder string
    The sort order is applied to the values of the breakdown column.
    aggregation_function AggregationFunctionResponse
    The Aggregation function is applied across all data in each breakdown created.
    column str
    The name of the column in the dataset containing the breakdown values.
    limit int
    A limit to the number of breakdowns. If set to zero then all possible breakdowns are applied. The list of breakdowns is dependent on the value of the sort_order field.
    sort_order str
    The sort order is applied to the values of the breakdown column.
    aggregationFunction Property Map
    The Aggregation function is applied across all data in each breakdown created.
    column String
    The name of the column in the dataset containing the breakdown values.
    limit Number
    A limit to the number of breakdowns. If set to zero then all possible breakdowns are applied. The list of breakdowns is dependent on the value of the sort_order field.
    sortOrder String
    The sort order is applied to the values of the breakdown column.

    BreakdownSortOrder, BreakdownSortOrderArgs

    SortOrderUnspecified
    SORT_ORDER_UNSPECIFIEDAn unspecified sort order. This option is invalid when sorting is required.
    SortOrderNone
    SORT_ORDER_NONENo sorting is applied.
    SortOrderAscending
    SORT_ORDER_ASCENDINGThe lowest-valued entries are selected first.
    SortOrderDescending
    SORT_ORDER_DESCENDINGThe highest-valued entries are selected first.
    BreakdownSortOrderSortOrderUnspecified
    SORT_ORDER_UNSPECIFIEDAn unspecified sort order. This option is invalid when sorting is required.
    BreakdownSortOrderSortOrderNone
    SORT_ORDER_NONENo sorting is applied.
    BreakdownSortOrderSortOrderAscending
    SORT_ORDER_ASCENDINGThe lowest-valued entries are selected first.
    BreakdownSortOrderSortOrderDescending
    SORT_ORDER_DESCENDINGThe highest-valued entries are selected first.
    SortOrderUnspecified
    SORT_ORDER_UNSPECIFIEDAn unspecified sort order. This option is invalid when sorting is required.
    SortOrderNone
    SORT_ORDER_NONENo sorting is applied.
    SortOrderAscending
    SORT_ORDER_ASCENDINGThe lowest-valued entries are selected first.
    SortOrderDescending
    SORT_ORDER_DESCENDINGThe highest-valued entries are selected first.
    SortOrderUnspecified
    SORT_ORDER_UNSPECIFIEDAn unspecified sort order. This option is invalid when sorting is required.
    SortOrderNone
    SORT_ORDER_NONENo sorting is applied.
    SortOrderAscending
    SORT_ORDER_ASCENDINGThe lowest-valued entries are selected first.
    SortOrderDescending
    SORT_ORDER_DESCENDINGThe highest-valued entries are selected first.
    SORT_ORDER_UNSPECIFIED
    SORT_ORDER_UNSPECIFIEDAn unspecified sort order. This option is invalid when sorting is required.
    SORT_ORDER_NONE
    SORT_ORDER_NONENo sorting is applied.
    SORT_ORDER_ASCENDING
    SORT_ORDER_ASCENDINGThe lowest-valued entries are selected first.
    SORT_ORDER_DESCENDING
    SORT_ORDER_DESCENDINGThe highest-valued entries are selected first.
    "SORT_ORDER_UNSPECIFIED"
    SORT_ORDER_UNSPECIFIEDAn unspecified sort order. This option is invalid when sorting is required.
    "SORT_ORDER_NONE"
    SORT_ORDER_NONENo sorting is applied.
    "SORT_ORDER_ASCENDING"
    SORT_ORDER_ASCENDINGThe lowest-valued entries are selected first.
    "SORT_ORDER_DESCENDING"
    SORT_ORDER_DESCENDINGThe highest-valued entries are selected first.

    ChartOptions, ChartOptionsArgs

    DisplayHorizontal bool
    Preview: Configures whether the charted values are shown on the horizontal or vertical axis. By default, values are represented the vertical axis. This is a preview feature and may be subject to change before final release.
    Mode Pulumi.GoogleNative.Monitoring.V1.ChartOptionsMode
    The chart mode.
    DisplayHorizontal bool
    Preview: Configures whether the charted values are shown on the horizontal or vertical axis. By default, values are represented the vertical axis. This is a preview feature and may be subject to change before final release.
    Mode ChartOptionsMode
    The chart mode.
    displayHorizontal Boolean
    Preview: Configures whether the charted values are shown on the horizontal or vertical axis. By default, values are represented the vertical axis. This is a preview feature and may be subject to change before final release.
    mode ChartOptionsMode
    The chart mode.
    displayHorizontal boolean
    Preview: Configures whether the charted values are shown on the horizontal or vertical axis. By default, values are represented the vertical axis. This is a preview feature and may be subject to change before final release.
    mode ChartOptionsMode
    The chart mode.
    display_horizontal bool
    Preview: Configures whether the charted values are shown on the horizontal or vertical axis. By default, values are represented the vertical axis. This is a preview feature and may be subject to change before final release.
    mode ChartOptionsMode
    The chart mode.
    displayHorizontal Boolean
    Preview: Configures whether the charted values are shown on the horizontal or vertical axis. By default, values are represented the vertical axis. This is a preview feature and may be subject to change before final release.
    mode "MODE_UNSPECIFIED" | "COLOR" | "X_RAY" | "STATS"
    The chart mode.

    ChartOptionsMode, ChartOptionsModeArgs

    ModeUnspecified
    MODE_UNSPECIFIEDMode is unspecified. The view will default to COLOR.
    Color
    COLORThe chart distinguishes data series using different color. Line colors may get reused when there are many lines in the chart.
    XRay
    X_RAYThe chart uses the Stackdriver x-ray mode, in which each data set is plotted using the same semi-transparent color.
    Stats
    STATSThe chart displays statistics such as average, median, 95th percentile, and more.
    ChartOptionsModeModeUnspecified
    MODE_UNSPECIFIEDMode is unspecified. The view will default to COLOR.
    ChartOptionsModeColor
    COLORThe chart distinguishes data series using different color. Line colors may get reused when there are many lines in the chart.
    ChartOptionsModeXRay
    X_RAYThe chart uses the Stackdriver x-ray mode, in which each data set is plotted using the same semi-transparent color.
    ChartOptionsModeStats
    STATSThe chart displays statistics such as average, median, 95th percentile, and more.
    ModeUnspecified
    MODE_UNSPECIFIEDMode is unspecified. The view will default to COLOR.
    Color
    COLORThe chart distinguishes data series using different color. Line colors may get reused when there are many lines in the chart.
    XRay
    X_RAYThe chart uses the Stackdriver x-ray mode, in which each data set is plotted using the same semi-transparent color.
    Stats
    STATSThe chart displays statistics such as average, median, 95th percentile, and more.
    ModeUnspecified
    MODE_UNSPECIFIEDMode is unspecified. The view will default to COLOR.
    Color
    COLORThe chart distinguishes data series using different color. Line colors may get reused when there are many lines in the chart.
    XRay
    X_RAYThe chart uses the Stackdriver x-ray mode, in which each data set is plotted using the same semi-transparent color.
    Stats
    STATSThe chart displays statistics such as average, median, 95th percentile, and more.
    MODE_UNSPECIFIED
    MODE_UNSPECIFIEDMode is unspecified. The view will default to COLOR.
    COLOR
    COLORThe chart distinguishes data series using different color. Line colors may get reused when there are many lines in the chart.
    X_RAY
    X_RAYThe chart uses the Stackdriver x-ray mode, in which each data set is plotted using the same semi-transparent color.
    STATS
    STATSThe chart displays statistics such as average, median, 95th percentile, and more.
    "MODE_UNSPECIFIED"
    MODE_UNSPECIFIEDMode is unspecified. The view will default to COLOR.
    "COLOR"
    COLORThe chart distinguishes data series using different color. Line colors may get reused when there are many lines in the chart.
    "X_RAY"
    X_RAYThe chart uses the Stackdriver x-ray mode, in which each data set is plotted using the same semi-transparent color.
    "STATS"
    STATSThe chart displays statistics such as average, median, 95th percentile, and more.

    ChartOptionsResponse, ChartOptionsResponseArgs

    DisplayHorizontal bool
    Preview: Configures whether the charted values are shown on the horizontal or vertical axis. By default, values are represented the vertical axis. This is a preview feature and may be subject to change before final release.
    Mode string
    The chart mode.
    DisplayHorizontal bool
    Preview: Configures whether the charted values are shown on the horizontal or vertical axis. By default, values are represented the vertical axis. This is a preview feature and may be subject to change before final release.
    Mode string
    The chart mode.
    displayHorizontal Boolean
    Preview: Configures whether the charted values are shown on the horizontal or vertical axis. By default, values are represented the vertical axis. This is a preview feature and may be subject to change before final release.
    mode String
    The chart mode.
    displayHorizontal boolean
    Preview: Configures whether the charted values are shown on the horizontal or vertical axis. By default, values are represented the vertical axis. This is a preview feature and may be subject to change before final release.
    mode string
    The chart mode.
    display_horizontal bool
    Preview: Configures whether the charted values are shown on the horizontal or vertical axis. By default, values are represented the vertical axis. This is a preview feature and may be subject to change before final release.
    mode str
    The chart mode.
    displayHorizontal Boolean
    Preview: Configures whether the charted values are shown on the horizontal or vertical axis. By default, values are represented the vertical axis. This is a preview feature and may be subject to change before final release.
    mode String
    The chart mode.

    CollapsibleGroup, CollapsibleGroupArgs

    Collapsed bool
    The collapsed state of the widget on first page load.
    Collapsed bool
    The collapsed state of the widget on first page load.
    collapsed Boolean
    The collapsed state of the widget on first page load.
    collapsed boolean
    The collapsed state of the widget on first page load.
    collapsed bool
    The collapsed state of the widget on first page load.
    collapsed Boolean
    The collapsed state of the widget on first page load.

    CollapsibleGroupResponse, CollapsibleGroupResponseArgs

    Collapsed bool
    The collapsed state of the widget on first page load.
    Collapsed bool
    The collapsed state of the widget on first page load.
    collapsed Boolean
    The collapsed state of the widget on first page load.
    collapsed boolean
    The collapsed state of the widget on first page load.
    collapsed bool
    The collapsed state of the widget on first page load.
    collapsed Boolean
    The collapsed state of the widget on first page load.

    Column, ColumnArgs

    Weight string
    The relative weight of this column. The column weight is used to adjust the width of columns on the screen (relative to peers). Greater the weight, greater the width of the column on the screen. If omitted, a value of 1 is used while rendering.
    Widgets List<Pulumi.GoogleNative.Monitoring.V1.Inputs.Widget>
    The display widgets arranged vertically in this column.
    Weight string
    The relative weight of this column. The column weight is used to adjust the width of columns on the screen (relative to peers). Greater the weight, greater the width of the column on the screen. If omitted, a value of 1 is used while rendering.
    Widgets []Widget
    The display widgets arranged vertically in this column.
    weight String
    The relative weight of this column. The column weight is used to adjust the width of columns on the screen (relative to peers). Greater the weight, greater the width of the column on the screen. If omitted, a value of 1 is used while rendering.
    widgets List<Widget>
    The display widgets arranged vertically in this column.
    weight string
    The relative weight of this column. The column weight is used to adjust the width of columns on the screen (relative to peers). Greater the weight, greater the width of the column on the screen. If omitted, a value of 1 is used while rendering.
    widgets Widget[]
    The display widgets arranged vertically in this column.
    weight str
    The relative weight of this column. The column weight is used to adjust the width of columns on the screen (relative to peers). Greater the weight, greater the width of the column on the screen. If omitted, a value of 1 is used while rendering.
    widgets Sequence[Widget]
    The display widgets arranged vertically in this column.
    weight String
    The relative weight of this column. The column weight is used to adjust the width of columns on the screen (relative to peers). Greater the weight, greater the width of the column on the screen. If omitted, a value of 1 is used while rendering.
    widgets List<Property Map>
    The display widgets arranged vertically in this column.

    ColumnLayout, ColumnLayoutArgs

    Columns []Column
    The columns of content to display.
    columns List<Column>
    The columns of content to display.
    columns Column[]
    The columns of content to display.
    columns Sequence[Column]
    The columns of content to display.
    columns List<Property Map>
    The columns of content to display.

    ColumnLayoutResponse, ColumnLayoutResponseArgs

    Columns []ColumnResponse
    The columns of content to display.
    columns List<ColumnResponse>
    The columns of content to display.
    columns ColumnResponse[]
    The columns of content to display.
    columns Sequence[ColumnResponse]
    The columns of content to display.
    columns List<Property Map>
    The columns of content to display.

    ColumnResponse, ColumnResponseArgs

    Weight string
    The relative weight of this column. The column weight is used to adjust the width of columns on the screen (relative to peers). Greater the weight, greater the width of the column on the screen. If omitted, a value of 1 is used while rendering.
    Widgets List<Pulumi.GoogleNative.Monitoring.V1.Inputs.WidgetResponse>
    The display widgets arranged vertically in this column.
    Weight string
    The relative weight of this column. The column weight is used to adjust the width of columns on the screen (relative to peers). Greater the weight, greater the width of the column on the screen. If omitted, a value of 1 is used while rendering.
    Widgets []WidgetResponse
    The display widgets arranged vertically in this column.
    weight String
    The relative weight of this column. The column weight is used to adjust the width of columns on the screen (relative to peers). Greater the weight, greater the width of the column on the screen. If omitted, a value of 1 is used while rendering.
    widgets List<WidgetResponse>
    The display widgets arranged vertically in this column.
    weight string
    The relative weight of this column. The column weight is used to adjust the width of columns on the screen (relative to peers). Greater the weight, greater the width of the column on the screen. If omitted, a value of 1 is used while rendering.
    widgets WidgetResponse[]
    The display widgets arranged vertically in this column.
    weight str
    The relative weight of this column. The column weight is used to adjust the width of columns on the screen (relative to peers). Greater the weight, greater the width of the column on the screen. If omitted, a value of 1 is used while rendering.
    widgets Sequence[WidgetResponse]
    The display widgets arranged vertically in this column.
    weight String
    The relative weight of this column. The column weight is used to adjust the width of columns on the screen (relative to peers). Greater the weight, greater the width of the column on the screen. If omitted, a value of 1 is used while rendering.
    widgets List<Property Map>
    The display widgets arranged vertically in this column.

    ColumnSettings, ColumnSettingsArgs

    Column string
    The id of the column.
    Visible bool
    Whether the column should be visible on page load.
    Column string
    The id of the column.
    Visible bool
    Whether the column should be visible on page load.
    column String
    The id of the column.
    visible Boolean
    Whether the column should be visible on page load.
    column string
    The id of the column.
    visible boolean
    Whether the column should be visible on page load.
    column str
    The id of the column.
    visible bool
    Whether the column should be visible on page load.
    column String
    The id of the column.
    visible Boolean
    Whether the column should be visible on page load.

    ColumnSettingsResponse, ColumnSettingsResponseArgs

    Column string
    The id of the column.
    Visible bool
    Whether the column should be visible on page load.
    Column string
    The id of the column.
    Visible bool
    Whether the column should be visible on page load.
    column String
    The id of the column.
    visible Boolean
    Whether the column should be visible on page load.
    column string
    The id of the column.
    visible boolean
    Whether the column should be visible on page load.
    column str
    The id of the column.
    visible bool
    Whether the column should be visible on page load.
    column String
    The id of the column.
    visible Boolean
    Whether the column should be visible on page load.

    DashboardFilter, DashboardFilterArgs

    LabelKey string
    The key for the label
    FilterType Pulumi.GoogleNative.Monitoring.V1.DashboardFilterFilterType
    The specified filter type
    StringValue string
    A variable-length string value.
    TemplateVariable string
    The placeholder text that can be referenced in a filter string or MQL query. If omitted, the dashboard filter will be applied to all relevant widgets in the dashboard.
    LabelKey string
    The key for the label
    FilterType DashboardFilterFilterType
    The specified filter type
    StringValue string
    A variable-length string value.
    TemplateVariable string
    The placeholder text that can be referenced in a filter string or MQL query. If omitted, the dashboard filter will be applied to all relevant widgets in the dashboard.
    labelKey String
    The key for the label
    filterType DashboardFilterFilterType
    The specified filter type
    stringValue String
    A variable-length string value.
    templateVariable String
    The placeholder text that can be referenced in a filter string or MQL query. If omitted, the dashboard filter will be applied to all relevant widgets in the dashboard.
    labelKey string
    The key for the label
    filterType DashboardFilterFilterType
    The specified filter type
    stringValue string
    A variable-length string value.
    templateVariable string
    The placeholder text that can be referenced in a filter string or MQL query. If omitted, the dashboard filter will be applied to all relevant widgets in the dashboard.
    label_key str
    The key for the label
    filter_type DashboardFilterFilterType
    The specified filter type
    string_value str
    A variable-length string value.
    template_variable str
    The placeholder text that can be referenced in a filter string or MQL query. If omitted, the dashboard filter will be applied to all relevant widgets in the dashboard.
    labelKey String
    The key for the label
    filterType "FILTER_TYPE_UNSPECIFIED" | "RESOURCE_LABEL" | "METRIC_LABEL" | "USER_METADATA_LABEL" | "SYSTEM_METADATA_LABEL" | "GROUP"
    The specified filter type
    stringValue String
    A variable-length string value.
    templateVariable String
    The placeholder text that can be referenced in a filter string or MQL query. If omitted, the dashboard filter will be applied to all relevant widgets in the dashboard.

    DashboardFilterFilterType, DashboardFilterFilterTypeArgs

    FilterTypeUnspecified
    FILTER_TYPE_UNSPECIFIEDFilter type is unspecified. This is not valid in a well-formed request.
    ResourceLabel
    RESOURCE_LABELFilter on a resource label value
    MetricLabel
    METRIC_LABELFilter on a metrics label value
    UserMetadataLabel
    USER_METADATA_LABELFilter on a user metadata label value
    SystemMetadataLabel
    SYSTEM_METADATA_LABELFilter on a system metadata label value
    Group
    GROUPFilter on a group id
    DashboardFilterFilterTypeFilterTypeUnspecified
    FILTER_TYPE_UNSPECIFIEDFilter type is unspecified. This is not valid in a well-formed request.
    DashboardFilterFilterTypeResourceLabel
    RESOURCE_LABELFilter on a resource label value
    DashboardFilterFilterTypeMetricLabel
    METRIC_LABELFilter on a metrics label value
    DashboardFilterFilterTypeUserMetadataLabel
    USER_METADATA_LABELFilter on a user metadata label value
    DashboardFilterFilterTypeSystemMetadataLabel
    SYSTEM_METADATA_LABELFilter on a system metadata label value
    DashboardFilterFilterTypeGroup
    GROUPFilter on a group id
    FilterTypeUnspecified
    FILTER_TYPE_UNSPECIFIEDFilter type is unspecified. This is not valid in a well-formed request.
    ResourceLabel
    RESOURCE_LABELFilter on a resource label value
    MetricLabel
    METRIC_LABELFilter on a metrics label value
    UserMetadataLabel
    USER_METADATA_LABELFilter on a user metadata label value
    SystemMetadataLabel
    SYSTEM_METADATA_LABELFilter on a system metadata label value
    Group
    GROUPFilter on a group id
    FilterTypeUnspecified
    FILTER_TYPE_UNSPECIFIEDFilter type is unspecified. This is not valid in a well-formed request.
    ResourceLabel
    RESOURCE_LABELFilter on a resource label value
    MetricLabel
    METRIC_LABELFilter on a metrics label value
    UserMetadataLabel
    USER_METADATA_LABELFilter on a user metadata label value
    SystemMetadataLabel
    SYSTEM_METADATA_LABELFilter on a system metadata label value
    Group
    GROUPFilter on a group id
    FILTER_TYPE_UNSPECIFIED
    FILTER_TYPE_UNSPECIFIEDFilter type is unspecified. This is not valid in a well-formed request.
    RESOURCE_LABEL
    RESOURCE_LABELFilter on a resource label value
    METRIC_LABEL
    METRIC_LABELFilter on a metrics label value
    USER_METADATA_LABEL
    USER_METADATA_LABELFilter on a user metadata label value
    SYSTEM_METADATA_LABEL
    SYSTEM_METADATA_LABELFilter on a system metadata label value
    GROUP
    GROUPFilter on a group id
    "FILTER_TYPE_UNSPECIFIED"
    FILTER_TYPE_UNSPECIFIEDFilter type is unspecified. This is not valid in a well-formed request.
    "RESOURCE_LABEL"
    RESOURCE_LABELFilter on a resource label value
    "METRIC_LABEL"
    METRIC_LABELFilter on a metrics label value
    "USER_METADATA_LABEL"
    USER_METADATA_LABELFilter on a user metadata label value
    "SYSTEM_METADATA_LABEL"
    SYSTEM_METADATA_LABELFilter on a system metadata label value
    "GROUP"
    GROUPFilter on a group id

    DashboardFilterResponse, DashboardFilterResponseArgs

    FilterType string
    The specified filter type
    LabelKey string
    The key for the label
    StringValue string
    A variable-length string value.
    TemplateVariable string
    The placeholder text that can be referenced in a filter string or MQL query. If omitted, the dashboard filter will be applied to all relevant widgets in the dashboard.
    FilterType string
    The specified filter type
    LabelKey string
    The key for the label
    StringValue string
    A variable-length string value.
    TemplateVariable string
    The placeholder text that can be referenced in a filter string or MQL query. If omitted, the dashboard filter will be applied to all relevant widgets in the dashboard.
    filterType String
    The specified filter type
    labelKey String
    The key for the label
    stringValue String
    A variable-length string value.
    templateVariable String
    The placeholder text that can be referenced in a filter string or MQL query. If omitted, the dashboard filter will be applied to all relevant widgets in the dashboard.
    filterType string
    The specified filter type
    labelKey string
    The key for the label
    stringValue string
    A variable-length string value.
    templateVariable string
    The placeholder text that can be referenced in a filter string or MQL query. If omitted, the dashboard filter will be applied to all relevant widgets in the dashboard.
    filter_type str
    The specified filter type
    label_key str
    The key for the label
    string_value str
    A variable-length string value.
    template_variable str
    The placeholder text that can be referenced in a filter string or MQL query. If omitted, the dashboard filter will be applied to all relevant widgets in the dashboard.
    filterType String
    The specified filter type
    labelKey String
    The key for the label
    stringValue String
    A variable-length string value.
    templateVariable String
    The placeholder text that can be referenced in a filter string or MQL query. If omitted, the dashboard filter will be applied to all relevant widgets in the dashboard.

    DataSet, DataSetArgs

    TimeSeriesQuery Pulumi.GoogleNative.Monitoring.V1.Inputs.TimeSeriesQuery
    Fields for querying time series data from the Stackdriver metrics API.
    Breakdowns List<Pulumi.GoogleNative.Monitoring.V1.Inputs.Breakdown>
    Optional. The collection of breakdowns to be applied to the dataset.
    Dimensions List<Pulumi.GoogleNative.Monitoring.V1.Inputs.Dimension>
    Optional. A collection of dimension columns.
    LegendTemplate string
    A template string for naming TimeSeries in the resulting data set. This should be a string with interpolations of the form ${label_name}, which will resolve to the label's value.
    Measures List<Pulumi.GoogleNative.Monitoring.V1.Inputs.Measure>
    Optional. A collection of measures.
    MinAlignmentPeriod string
    Optional. The lower bound on data point frequency for this data set, implemented by specifying the minimum alignment period to use in a time series query For example, if the data is published once every 10 minutes, the min_alignment_period should be at least 10 minutes. It would not make sense to fetch and align data at one minute intervals.
    PlotType Pulumi.GoogleNative.Monitoring.V1.DataSetPlotType
    How this data should be plotted on the chart.
    TargetAxis Pulumi.GoogleNative.Monitoring.V1.DataSetTargetAxis
    Optional. The target axis to use for plotting the metric.
    TimeSeriesQuery TimeSeriesQuery
    Fields for querying time series data from the Stackdriver metrics API.
    Breakdowns []Breakdown
    Optional. The collection of breakdowns to be applied to the dataset.
    Dimensions []Dimension
    Optional. A collection of dimension columns.
    LegendTemplate string
    A template string for naming TimeSeries in the resulting data set. This should be a string with interpolations of the form ${label_name}, which will resolve to the label's value.
    Measures []Measure
    Optional. A collection of measures.
    MinAlignmentPeriod string
    Optional. The lower bound on data point frequency for this data set, implemented by specifying the minimum alignment period to use in a time series query For example, if the data is published once every 10 minutes, the min_alignment_period should be at least 10 minutes. It would not make sense to fetch and align data at one minute intervals.
    PlotType DataSetPlotType
    How this data should be plotted on the chart.
    TargetAxis DataSetTargetAxis
    Optional. The target axis to use for plotting the metric.
    timeSeriesQuery TimeSeriesQuery
    Fields for querying time series data from the Stackdriver metrics API.
    breakdowns List<Breakdown>
    Optional. The collection of breakdowns to be applied to the dataset.
    dimensions List<Dimension>
    Optional. A collection of dimension columns.
    legendTemplate String
    A template string for naming TimeSeries in the resulting data set. This should be a string with interpolations of the form ${label_name}, which will resolve to the label's value.
    measures List<Measure>
    Optional. A collection of measures.
    minAlignmentPeriod String
    Optional. The lower bound on data point frequency for this data set, implemented by specifying the minimum alignment period to use in a time series query For example, if the data is published once every 10 minutes, the min_alignment_period should be at least 10 minutes. It would not make sense to fetch and align data at one minute intervals.
    plotType DataSetPlotType
    How this data should be plotted on the chart.
    targetAxis DataSetTargetAxis
    Optional. The target axis to use for plotting the metric.
    timeSeriesQuery TimeSeriesQuery
    Fields for querying time series data from the Stackdriver metrics API.
    breakdowns Breakdown[]
    Optional. The collection of breakdowns to be applied to the dataset.
    dimensions Dimension[]
    Optional. A collection of dimension columns.
    legendTemplate string
    A template string for naming TimeSeries in the resulting data set. This should be a string with interpolations of the form ${label_name}, which will resolve to the label's value.
    measures Measure[]
    Optional. A collection of measures.
    minAlignmentPeriod string
    Optional. The lower bound on data point frequency for this data set, implemented by specifying the minimum alignment period to use in a time series query For example, if the data is published once every 10 minutes, the min_alignment_period should be at least 10 minutes. It would not make sense to fetch and align data at one minute intervals.
    plotType DataSetPlotType
    How this data should be plotted on the chart.
    targetAxis DataSetTargetAxis
    Optional. The target axis to use for plotting the metric.
    time_series_query TimeSeriesQuery
    Fields for querying time series data from the Stackdriver metrics API.
    breakdowns Sequence[Breakdown]
    Optional. The collection of breakdowns to be applied to the dataset.
    dimensions Sequence[Dimension]
    Optional. A collection of dimension columns.
    legend_template str
    A template string for naming TimeSeries in the resulting data set. This should be a string with interpolations of the form ${label_name}, which will resolve to the label's value.
    measures Sequence[Measure]
    Optional. A collection of measures.
    min_alignment_period str
    Optional. The lower bound on data point frequency for this data set, implemented by specifying the minimum alignment period to use in a time series query For example, if the data is published once every 10 minutes, the min_alignment_period should be at least 10 minutes. It would not make sense to fetch and align data at one minute intervals.
    plot_type DataSetPlotType
    How this data should be plotted on the chart.
    target_axis DataSetTargetAxis
    Optional. The target axis to use for plotting the metric.
    timeSeriesQuery Property Map
    Fields for querying time series data from the Stackdriver metrics API.
    breakdowns List<Property Map>
    Optional. The collection of breakdowns to be applied to the dataset.
    dimensions List<Property Map>
    Optional. A collection of dimension columns.
    legendTemplate String
    A template string for naming TimeSeries in the resulting data set. This should be a string with interpolations of the form ${label_name}, which will resolve to the label's value.
    measures List<Property Map>
    Optional. A collection of measures.
    minAlignmentPeriod String
    Optional. The lower bound on data point frequency for this data set, implemented by specifying the minimum alignment period to use in a time series query For example, if the data is published once every 10 minutes, the min_alignment_period should be at least 10 minutes. It would not make sense to fetch and align data at one minute intervals.
    plotType "PLOT_TYPE_UNSPECIFIED" | "LINE" | "STACKED_AREA" | "STACKED_BAR" | "HEATMAP"
    How this data should be plotted on the chart.
    targetAxis "TARGET_AXIS_UNSPECIFIED" | "Y1" | "Y2"
    Optional. The target axis to use for plotting the metric.

    DataSetPlotType, DataSetPlotTypeArgs

    PlotTypeUnspecified
    PLOT_TYPE_UNSPECIFIEDPlot type is unspecified. The view will default to LINE.
    Line
    LINEThe data is plotted as a set of lines (one line per series).
    StackedArea
    STACKED_AREAThe data is plotted as a set of filled areas (one area per series), with the areas stacked vertically (the base of each area is the top of its predecessor, and the base of the first area is the x-axis). Since the areas do not overlap, each is filled with a different opaque color.
    StackedBar
    STACKED_BARThe data is plotted as a set of rectangular boxes (one box per series), with the boxes stacked vertically (the base of each box is the top of its predecessor, and the base of the first box is the x-axis). Since the boxes do not overlap, each is filled with a different opaque color.
    Heatmap
    HEATMAPThe data is plotted as a heatmap. The series being plotted must have a DISTRIBUTION value type. The value of each bucket in the distribution is displayed as a color. This type is not currently available in the Stackdriver Monitoring application.
    DataSetPlotTypePlotTypeUnspecified
    PLOT_TYPE_UNSPECIFIEDPlot type is unspecified. The view will default to LINE.
    DataSetPlotTypeLine
    LINEThe data is plotted as a set of lines (one line per series).
    DataSetPlotTypeStackedArea
    STACKED_AREAThe data is plotted as a set of filled areas (one area per series), with the areas stacked vertically (the base of each area is the top of its predecessor, and the base of the first area is the x-axis). Since the areas do not overlap, each is filled with a different opaque color.
    DataSetPlotTypeStackedBar
    STACKED_BARThe data is plotted as a set of rectangular boxes (one box per series), with the boxes stacked vertically (the base of each box is the top of its predecessor, and the base of the first box is the x-axis). Since the boxes do not overlap, each is filled with a different opaque color.
    DataSetPlotTypeHeatmap
    HEATMAPThe data is plotted as a heatmap. The series being plotted must have a DISTRIBUTION value type. The value of each bucket in the distribution is displayed as a color. This type is not currently available in the Stackdriver Monitoring application.
    PlotTypeUnspecified
    PLOT_TYPE_UNSPECIFIEDPlot type is unspecified. The view will default to LINE.
    Line
    LINEThe data is plotted as a set of lines (one line per series).
    StackedArea
    STACKED_AREAThe data is plotted as a set of filled areas (one area per series), with the areas stacked vertically (the base of each area is the top of its predecessor, and the base of the first area is the x-axis). Since the areas do not overlap, each is filled with a different opaque color.
    StackedBar
    STACKED_BARThe data is plotted as a set of rectangular boxes (one box per series), with the boxes stacked vertically (the base of each box is the top of its predecessor, and the base of the first box is the x-axis). Since the boxes do not overlap, each is filled with a different opaque color.
    Heatmap
    HEATMAPThe data is plotted as a heatmap. The series being plotted must have a DISTRIBUTION value type. The value of each bucket in the distribution is displayed as a color. This type is not currently available in the Stackdriver Monitoring application.
    PlotTypeUnspecified
    PLOT_TYPE_UNSPECIFIEDPlot type is unspecified. The view will default to LINE.
    Line
    LINEThe data is plotted as a set of lines (one line per series).
    StackedArea
    STACKED_AREAThe data is plotted as a set of filled areas (one area per series), with the areas stacked vertically (the base of each area is the top of its predecessor, and the base of the first area is the x-axis). Since the areas do not overlap, each is filled with a different opaque color.
    StackedBar
    STACKED_BARThe data is plotted as a set of rectangular boxes (one box per series), with the boxes stacked vertically (the base of each box is the top of its predecessor, and the base of the first box is the x-axis). Since the boxes do not overlap, each is filled with a different opaque color.
    Heatmap
    HEATMAPThe data is plotted as a heatmap. The series being plotted must have a DISTRIBUTION value type. The value of each bucket in the distribution is displayed as a color. This type is not currently available in the Stackdriver Monitoring application.
    PLOT_TYPE_UNSPECIFIED
    PLOT_TYPE_UNSPECIFIEDPlot type is unspecified. The view will default to LINE.
    LINE
    LINEThe data is plotted as a set of lines (one line per series).
    STACKED_AREA
    STACKED_AREAThe data is plotted as a set of filled areas (one area per series), with the areas stacked vertically (the base of each area is the top of its predecessor, and the base of the first area is the x-axis). Since the areas do not overlap, each is filled with a different opaque color.
    STACKED_BAR
    STACKED_BARThe data is plotted as a set of rectangular boxes (one box per series), with the boxes stacked vertically (the base of each box is the top of its predecessor, and the base of the first box is the x-axis). Since the boxes do not overlap, each is filled with a different opaque color.
    HEATMAP
    HEATMAPThe data is plotted as a heatmap. The series being plotted must have a DISTRIBUTION value type. The value of each bucket in the distribution is displayed as a color. This type is not currently available in the Stackdriver Monitoring application.
    "PLOT_TYPE_UNSPECIFIED"
    PLOT_TYPE_UNSPECIFIEDPlot type is unspecified. The view will default to LINE.
    "LINE"
    LINEThe data is plotted as a set of lines (one line per series).
    "STACKED_AREA"
    STACKED_AREAThe data is plotted as a set of filled areas (one area per series), with the areas stacked vertically (the base of each area is the top of its predecessor, and the base of the first area is the x-axis). Since the areas do not overlap, each is filled with a different opaque color.
    "STACKED_BAR"
    STACKED_BARThe data is plotted as a set of rectangular boxes (one box per series), with the boxes stacked vertically (the base of each box is the top of its predecessor, and the base of the first box is the x-axis). Since the boxes do not overlap, each is filled with a different opaque color.
    "HEATMAP"
    HEATMAPThe data is plotted as a heatmap. The series being plotted must have a DISTRIBUTION value type. The value of each bucket in the distribution is displayed as a color. This type is not currently available in the Stackdriver Monitoring application.

    DataSetResponse, DataSetResponseArgs

    Breakdowns List<Pulumi.GoogleNative.Monitoring.V1.Inputs.BreakdownResponse>
    Optional. The collection of breakdowns to be applied to the dataset.
    Dimensions List<Pulumi.GoogleNative.Monitoring.V1.Inputs.DimensionResponse>
    Optional. A collection of dimension columns.
    LegendTemplate string
    A template string for naming TimeSeries in the resulting data set. This should be a string with interpolations of the form ${label_name}, which will resolve to the label's value.
    Measures List<Pulumi.GoogleNative.Monitoring.V1.Inputs.MeasureResponse>
    Optional. A collection of measures.
    MinAlignmentPeriod string
    Optional. The lower bound on data point frequency for this data set, implemented by specifying the minimum alignment period to use in a time series query For example, if the data is published once every 10 minutes, the min_alignment_period should be at least 10 minutes. It would not make sense to fetch and align data at one minute intervals.
    PlotType string
    How this data should be plotted on the chart.
    TargetAxis string
    Optional. The target axis to use for plotting the metric.
    TimeSeriesQuery Pulumi.GoogleNative.Monitoring.V1.Inputs.TimeSeriesQueryResponse
    Fields for querying time series data from the Stackdriver metrics API.
    Breakdowns []BreakdownResponse
    Optional. The collection of breakdowns to be applied to the dataset.
    Dimensions []DimensionResponse
    Optional. A collection of dimension columns.
    LegendTemplate string
    A template string for naming TimeSeries in the resulting data set. This should be a string with interpolations of the form ${label_name}, which will resolve to the label's value.
    Measures []MeasureResponse
    Optional. A collection of measures.
    MinAlignmentPeriod string
    Optional. The lower bound on data point frequency for this data set, implemented by specifying the minimum alignment period to use in a time series query For example, if the data is published once every 10 minutes, the min_alignment_period should be at least 10 minutes. It would not make sense to fetch and align data at one minute intervals.
    PlotType string
    How this data should be plotted on the chart.
    TargetAxis string
    Optional. The target axis to use for plotting the metric.
    TimeSeriesQuery TimeSeriesQueryResponse
    Fields for querying time series data from the Stackdriver metrics API.
    breakdowns List<BreakdownResponse>
    Optional. The collection of breakdowns to be applied to the dataset.
    dimensions List<DimensionResponse>
    Optional. A collection of dimension columns.
    legendTemplate String
    A template string for naming TimeSeries in the resulting data set. This should be a string with interpolations of the form ${label_name}, which will resolve to the label's value.
    measures List<MeasureResponse>
    Optional. A collection of measures.
    minAlignmentPeriod String
    Optional. The lower bound on data point frequency for this data set, implemented by specifying the minimum alignment period to use in a time series query For example, if the data is published once every 10 minutes, the min_alignment_period should be at least 10 minutes. It would not make sense to fetch and align data at one minute intervals.
    plotType String
    How this data should be plotted on the chart.
    targetAxis String
    Optional. The target axis to use for plotting the metric.
    timeSeriesQuery TimeSeriesQueryResponse
    Fields for querying time series data from the Stackdriver metrics API.
    breakdowns BreakdownResponse[]
    Optional. The collection of breakdowns to be applied to the dataset.
    dimensions DimensionResponse[]
    Optional. A collection of dimension columns.
    legendTemplate string
    A template string for naming TimeSeries in the resulting data set. This should be a string with interpolations of the form ${label_name}, which will resolve to the label's value.
    measures MeasureResponse[]
    Optional. A collection of measures.
    minAlignmentPeriod string
    Optional. The lower bound on data point frequency for this data set, implemented by specifying the minimum alignment period to use in a time series query For example, if the data is published once every 10 minutes, the min_alignment_period should be at least 10 minutes. It would not make sense to fetch and align data at one minute intervals.
    plotType string
    How this data should be plotted on the chart.
    targetAxis string
    Optional. The target axis to use for plotting the metric.
    timeSeriesQuery TimeSeriesQueryResponse
    Fields for querying time series data from the Stackdriver metrics API.
    breakdowns Sequence[BreakdownResponse]
    Optional. The collection of breakdowns to be applied to the dataset.
    dimensions Sequence[DimensionResponse]
    Optional. A collection of dimension columns.
    legend_template str
    A template string for naming TimeSeries in the resulting data set. This should be a string with interpolations of the form ${label_name}, which will resolve to the label's value.
    measures Sequence[MeasureResponse]
    Optional. A collection of measures.
    min_alignment_period str
    Optional. The lower bound on data point frequency for this data set, implemented by specifying the minimum alignment period to use in a time series query For example, if the data is published once every 10 minutes, the min_alignment_period should be at least 10 minutes. It would not make sense to fetch and align data at one minute intervals.
    plot_type str
    How this data should be plotted on the chart.
    target_axis str
    Optional. The target axis to use for plotting the metric.
    time_series_query TimeSeriesQueryResponse
    Fields for querying time series data from the Stackdriver metrics API.
    breakdowns List<Property Map>
    Optional. The collection of breakdowns to be applied to the dataset.
    dimensions List<Property Map>
    Optional. A collection of dimension columns.
    legendTemplate String
    A template string for naming TimeSeries in the resulting data set. This should be a string with interpolations of the form ${label_name}, which will resolve to the label's value.
    measures List<Property Map>
    Optional. A collection of measures.
    minAlignmentPeriod String
    Optional. The lower bound on data point frequency for this data set, implemented by specifying the minimum alignment period to use in a time series query For example, if the data is published once every 10 minutes, the min_alignment_period should be at least 10 minutes. It would not make sense to fetch and align data at one minute intervals.
    plotType String
    How this data should be plotted on the chart.
    targetAxis String
    Optional. The target axis to use for plotting the metric.
    timeSeriesQuery Property Map
    Fields for querying time series data from the Stackdriver metrics API.

    DataSetTargetAxis, DataSetTargetAxisArgs

    TargetAxisUnspecified
    TARGET_AXIS_UNSPECIFIEDThe target axis was not specified. Defaults to Y1.
    Y1
    Y1The y_axis (the right axis of chart).
    Y2
    Y2The y2_axis (the left axis of chart).
    DataSetTargetAxisTargetAxisUnspecified
    TARGET_AXIS_UNSPECIFIEDThe target axis was not specified. Defaults to Y1.
    DataSetTargetAxisY1
    Y1The y_axis (the right axis of chart).
    DataSetTargetAxisY2
    Y2The y2_axis (the left axis of chart).
    TargetAxisUnspecified
    TARGET_AXIS_UNSPECIFIEDThe target axis was not specified. Defaults to Y1.
    Y1
    Y1The y_axis (the right axis of chart).
    Y2
    Y2The y2_axis (the left axis of chart).
    TargetAxisUnspecified
    TARGET_AXIS_UNSPECIFIEDThe target axis was not specified. Defaults to Y1.
    Y1
    Y1The y_axis (the right axis of chart).
    Y2
    Y2The y2_axis (the left axis of chart).
    TARGET_AXIS_UNSPECIFIED
    TARGET_AXIS_UNSPECIFIEDThe target axis was not specified. Defaults to Y1.
    Y1
    Y1The y_axis (the right axis of chart).
    Y2
    Y2The y2_axis (the left axis of chart).
    "TARGET_AXIS_UNSPECIFIED"
    TARGET_AXIS_UNSPECIFIEDThe target axis was not specified. Defaults to Y1.
    "Y1"
    Y1The y_axis (the right axis of chart).
    "Y2"
    Y2The y2_axis (the left axis of chart).

    Dimension, DimensionArgs

    Column string
    The name of the column in the source SQL query that is used to chart the dimension.
    ColumnType string
    Optional. The type of the dimension column. This is relevant only if one of the bin_size fields is set. If it is empty, the type TIMESTAMP or INT64 will be assumed based on which bin_size field is set. If populated, this should be set to one of the following types: DATE, TIME, DATETIME, TIMESTAMP, BIGNUMERIC, INT64, NUMERIC, FLOAT64.
    FloatBinSize double
    Optional. float_bin_size is used when the column type used for a dimension is a floating point numeric column.
    MaxBinCount int
    A limit to the number of bins generated. When 0 is specified, the maximum count is not enforced.
    NumericBinSize int
    numeric_bin_size is used when the column type used for a dimension is numeric or string.
    SortColumn string
    The column name to sort on for binning. This column can be the same column as this dimension or any other column used as a measure in the results. If sort_order is set to NONE, then this value is not used.
    SortOrder Pulumi.GoogleNative.Monitoring.V1.DimensionSortOrder
    The sort order applied to the sort column.
    TimeBinSize string
    time_bin_size is used when the data type specified by column is a time type and the bin size is determined by a time duration. If column_type is DATE, this must be a whole value multiple of 1 day. If column_type is TIME, this must be less than or equal to 24 hours.
    Column string
    The name of the column in the source SQL query that is used to chart the dimension.
    ColumnType string
    Optional. The type of the dimension column. This is relevant only if one of the bin_size fields is set. If it is empty, the type TIMESTAMP or INT64 will be assumed based on which bin_size field is set. If populated, this should be set to one of the following types: DATE, TIME, DATETIME, TIMESTAMP, BIGNUMERIC, INT64, NUMERIC, FLOAT64.
    FloatBinSize float64
    Optional. float_bin_size is used when the column type used for a dimension is a floating point numeric column.
    MaxBinCount int
    A limit to the number of bins generated. When 0 is specified, the maximum count is not enforced.
    NumericBinSize int
    numeric_bin_size is used when the column type used for a dimension is numeric or string.
    SortColumn string
    The column name to sort on for binning. This column can be the same column as this dimension or any other column used as a measure in the results. If sort_order is set to NONE, then this value is not used.
    SortOrder DimensionSortOrder
    The sort order applied to the sort column.
    TimeBinSize string
    time_bin_size is used when the data type specified by column is a time type and the bin size is determined by a time duration. If column_type is DATE, this must be a whole value multiple of 1 day. If column_type is TIME, this must be less than or equal to 24 hours.
    column String
    The name of the column in the source SQL query that is used to chart the dimension.
    columnType String
    Optional. The type of the dimension column. This is relevant only if one of the bin_size fields is set. If it is empty, the type TIMESTAMP or INT64 will be assumed based on which bin_size field is set. If populated, this should be set to one of the following types: DATE, TIME, DATETIME, TIMESTAMP, BIGNUMERIC, INT64, NUMERIC, FLOAT64.
    floatBinSize Double
    Optional. float_bin_size is used when the column type used for a dimension is a floating point numeric column.
    maxBinCount Integer
    A limit to the number of bins generated. When 0 is specified, the maximum count is not enforced.
    numericBinSize Integer
    numeric_bin_size is used when the column type used for a dimension is numeric or string.
    sortColumn String
    The column name to sort on for binning. This column can be the same column as this dimension or any other column used as a measure in the results. If sort_order is set to NONE, then this value is not used.
    sortOrder DimensionSortOrder
    The sort order applied to the sort column.
    timeBinSize String
    time_bin_size is used when the data type specified by column is a time type and the bin size is determined by a time duration. If column_type is DATE, this must be a whole value multiple of 1 day. If column_type is TIME, this must be less than or equal to 24 hours.
    column string
    The name of the column in the source SQL query that is used to chart the dimension.
    columnType string
    Optional. The type of the dimension column. This is relevant only if one of the bin_size fields is set. If it is empty, the type TIMESTAMP or INT64 will be assumed based on which bin_size field is set. If populated, this should be set to one of the following types: DATE, TIME, DATETIME, TIMESTAMP, BIGNUMERIC, INT64, NUMERIC, FLOAT64.
    floatBinSize number
    Optional. float_bin_size is used when the column type used for a dimension is a floating point numeric column.
    maxBinCount number
    A limit to the number of bins generated. When 0 is specified, the maximum count is not enforced.
    numericBinSize number
    numeric_bin_size is used when the column type used for a dimension is numeric or string.
    sortColumn string
    The column name to sort on for binning. This column can be the same column as this dimension or any other column used as a measure in the results. If sort_order is set to NONE, then this value is not used.
    sortOrder DimensionSortOrder
    The sort order applied to the sort column.
    timeBinSize string
    time_bin_size is used when the data type specified by column is a time type and the bin size is determined by a time duration. If column_type is DATE, this must be a whole value multiple of 1 day. If column_type is TIME, this must be less than or equal to 24 hours.
    column str
    The name of the column in the source SQL query that is used to chart the dimension.
    column_type str
    Optional. The type of the dimension column. This is relevant only if one of the bin_size fields is set. If it is empty, the type TIMESTAMP or INT64 will be assumed based on which bin_size field is set. If populated, this should be set to one of the following types: DATE, TIME, DATETIME, TIMESTAMP, BIGNUMERIC, INT64, NUMERIC, FLOAT64.
    float_bin_size float
    Optional. float_bin_size is used when the column type used for a dimension is a floating point numeric column.
    max_bin_count int
    A limit to the number of bins generated. When 0 is specified, the maximum count is not enforced.
    numeric_bin_size int
    numeric_bin_size is used when the column type used for a dimension is numeric or string.
    sort_column str
    The column name to sort on for binning. This column can be the same column as this dimension or any other column used as a measure in the results. If sort_order is set to NONE, then this value is not used.
    sort_order DimensionSortOrder
    The sort order applied to the sort column.
    time_bin_size str
    time_bin_size is used when the data type specified by column is a time type and the bin size is determined by a time duration. If column_type is DATE, this must be a whole value multiple of 1 day. If column_type is TIME, this must be less than or equal to 24 hours.
    column String
    The name of the column in the source SQL query that is used to chart the dimension.
    columnType String
    Optional. The type of the dimension column. This is relevant only if one of the bin_size fields is set. If it is empty, the type TIMESTAMP or INT64 will be assumed based on which bin_size field is set. If populated, this should be set to one of the following types: DATE, TIME, DATETIME, TIMESTAMP, BIGNUMERIC, INT64, NUMERIC, FLOAT64.
    floatBinSize Number
    Optional. float_bin_size is used when the column type used for a dimension is a floating point numeric column.
    maxBinCount Number
    A limit to the number of bins generated. When 0 is specified, the maximum count is not enforced.
    numericBinSize Number
    numeric_bin_size is used when the column type used for a dimension is numeric or string.
    sortColumn String
    The column name to sort on for binning. This column can be the same column as this dimension or any other column used as a measure in the results. If sort_order is set to NONE, then this value is not used.
    sortOrder "SORT_ORDER_UNSPECIFIED" | "SORT_ORDER_NONE" | "SORT_ORDER_ASCENDING" | "SORT_ORDER_DESCENDING"
    The sort order applied to the sort column.
    timeBinSize String
    time_bin_size is used when the data type specified by column is a time type and the bin size is determined by a time duration. If column_type is DATE, this must be a whole value multiple of 1 day. If column_type is TIME, this must be less than or equal to 24 hours.

    DimensionResponse, DimensionResponseArgs

    Column string
    The name of the column in the source SQL query that is used to chart the dimension.
    ColumnType string
    Optional. The type of the dimension column. This is relevant only if one of the bin_size fields is set. If it is empty, the type TIMESTAMP or INT64 will be assumed based on which bin_size field is set. If populated, this should be set to one of the following types: DATE, TIME, DATETIME, TIMESTAMP, BIGNUMERIC, INT64, NUMERIC, FLOAT64.
    FloatBinSize double
    Optional. float_bin_size is used when the column type used for a dimension is a floating point numeric column.
    MaxBinCount int
    A limit to the number of bins generated. When 0 is specified, the maximum count is not enforced.
    NumericBinSize int
    numeric_bin_size is used when the column type used for a dimension is numeric or string.
    SortColumn string
    The column name to sort on for binning. This column can be the same column as this dimension or any other column used as a measure in the results. If sort_order is set to NONE, then this value is not used.
    SortOrder string
    The sort order applied to the sort column.
    TimeBinSize string
    time_bin_size is used when the data type specified by column is a time type and the bin size is determined by a time duration. If column_type is DATE, this must be a whole value multiple of 1 day. If column_type is TIME, this must be less than or equal to 24 hours.
    Column string
    The name of the column in the source SQL query that is used to chart the dimension.
    ColumnType string
    Optional. The type of the dimension column. This is relevant only if one of the bin_size fields is set. If it is empty, the type TIMESTAMP or INT64 will be assumed based on which bin_size field is set. If populated, this should be set to one of the following types: DATE, TIME, DATETIME, TIMESTAMP, BIGNUMERIC, INT64, NUMERIC, FLOAT64.
    FloatBinSize float64
    Optional. float_bin_size is used when the column type used for a dimension is a floating point numeric column.
    MaxBinCount int
    A limit to the number of bins generated. When 0 is specified, the maximum count is not enforced.
    NumericBinSize int
    numeric_bin_size is used when the column type used for a dimension is numeric or string.
    SortColumn string
    The column name to sort on for binning. This column can be the same column as this dimension or any other column used as a measure in the results. If sort_order is set to NONE, then this value is not used.
    SortOrder string
    The sort order applied to the sort column.
    TimeBinSize string
    time_bin_size is used when the data type specified by column is a time type and the bin size is determined by a time duration. If column_type is DATE, this must be a whole value multiple of 1 day. If column_type is TIME, this must be less than or equal to 24 hours.
    column String
    The name of the column in the source SQL query that is used to chart the dimension.
    columnType String
    Optional. The type of the dimension column. This is relevant only if one of the bin_size fields is set. If it is empty, the type TIMESTAMP or INT64 will be assumed based on which bin_size field is set. If populated, this should be set to one of the following types: DATE, TIME, DATETIME, TIMESTAMP, BIGNUMERIC, INT64, NUMERIC, FLOAT64.
    floatBinSize Double
    Optional. float_bin_size is used when the column type used for a dimension is a floating point numeric column.
    maxBinCount Integer
    A limit to the number of bins generated. When 0 is specified, the maximum count is not enforced.
    numericBinSize Integer
    numeric_bin_size is used when the column type used for a dimension is numeric or string.
    sortColumn String
    The column name to sort on for binning. This column can be the same column as this dimension or any other column used as a measure in the results. If sort_order is set to NONE, then this value is not used.
    sortOrder String
    The sort order applied to the sort column.
    timeBinSize String
    time_bin_size is used when the data type specified by column is a time type and the bin size is determined by a time duration. If column_type is DATE, this must be a whole value multiple of 1 day. If column_type is TIME, this must be less than or equal to 24 hours.
    column string
    The name of the column in the source SQL query that is used to chart the dimension.
    columnType string
    Optional. The type of the dimension column. This is relevant only if one of the bin_size fields is set. If it is empty, the type TIMESTAMP or INT64 will be assumed based on which bin_size field is set. If populated, this should be set to one of the following types: DATE, TIME, DATETIME, TIMESTAMP, BIGNUMERIC, INT64, NUMERIC, FLOAT64.
    floatBinSize number
    Optional. float_bin_size is used when the column type used for a dimension is a floating point numeric column.
    maxBinCount number
    A limit to the number of bins generated. When 0 is specified, the maximum count is not enforced.
    numericBinSize number
    numeric_bin_size is used when the column type used for a dimension is numeric or string.
    sortColumn string
    The column name to sort on for binning. This column can be the same column as this dimension or any other column used as a measure in the results. If sort_order is set to NONE, then this value is not used.
    sortOrder string
    The sort order applied to the sort column.
    timeBinSize string
    time_bin_size is used when the data type specified by column is a time type and the bin size is determined by a time duration. If column_type is DATE, this must be a whole value multiple of 1 day. If column_type is TIME, this must be less than or equal to 24 hours.
    column str
    The name of the column in the source SQL query that is used to chart the dimension.
    column_type str
    Optional. The type of the dimension column. This is relevant only if one of the bin_size fields is set. If it is empty, the type TIMESTAMP or INT64 will be assumed based on which bin_size field is set. If populated, this should be set to one of the following types: DATE, TIME, DATETIME, TIMESTAMP, BIGNUMERIC, INT64, NUMERIC, FLOAT64.
    float_bin_size float
    Optional. float_bin_size is used when the column type used for a dimension is a floating point numeric column.
    max_bin_count int
    A limit to the number of bins generated. When 0 is specified, the maximum count is not enforced.
    numeric_bin_size int
    numeric_bin_size is used when the column type used for a dimension is numeric or string.
    sort_column str
    The column name to sort on for binning. This column can be the same column as this dimension or any other column used as a measure in the results. If sort_order is set to NONE, then this value is not used.
    sort_order str
    The sort order applied to the sort column.
    time_bin_size str
    time_bin_size is used when the data type specified by column is a time type and the bin size is determined by a time duration. If column_type is DATE, this must be a whole value multiple of 1 day. If column_type is TIME, this must be less than or equal to 24 hours.
    column String
    The name of the column in the source SQL query that is used to chart the dimension.
    columnType String
    Optional. The type of the dimension column. This is relevant only if one of the bin_size fields is set. If it is empty, the type TIMESTAMP or INT64 will be assumed based on which bin_size field is set. If populated, this should be set to one of the following types: DATE, TIME, DATETIME, TIMESTAMP, BIGNUMERIC, INT64, NUMERIC, FLOAT64.
    floatBinSize Number
    Optional. float_bin_size is used when the column type used for a dimension is a floating point numeric column.
    maxBinCount Number
    A limit to the number of bins generated. When 0 is specified, the maximum count is not enforced.
    numericBinSize Number
    numeric_bin_size is used when the column type used for a dimension is numeric or string.
    sortColumn String
    The column name to sort on for binning. This column can be the same column as this dimension or any other column used as a measure in the results. If sort_order is set to NONE, then this value is not used.
    sortOrder String
    The sort order applied to the sort column.
    timeBinSize String
    time_bin_size is used when the data type specified by column is a time type and the bin size is determined by a time duration. If column_type is DATE, this must be a whole value multiple of 1 day. If column_type is TIME, this must be less than or equal to 24 hours.

    DimensionSortOrder, DimensionSortOrderArgs

    SortOrderUnspecified
    SORT_ORDER_UNSPECIFIEDAn unspecified sort order. This option is invalid when sorting is required.
    SortOrderNone
    SORT_ORDER_NONENo sorting is applied.
    SortOrderAscending
    SORT_ORDER_ASCENDINGThe lowest-valued entries are selected first.
    SortOrderDescending
    SORT_ORDER_DESCENDINGThe highest-valued entries are selected first.
    DimensionSortOrderSortOrderUnspecified
    SORT_ORDER_UNSPECIFIEDAn unspecified sort order. This option is invalid when sorting is required.
    DimensionSortOrderSortOrderNone
    SORT_ORDER_NONENo sorting is applied.
    DimensionSortOrderSortOrderAscending
    SORT_ORDER_ASCENDINGThe lowest-valued entries are selected first.
    DimensionSortOrderSortOrderDescending
    SORT_ORDER_DESCENDINGThe highest-valued entries are selected first.
    SortOrderUnspecified
    SORT_ORDER_UNSPECIFIEDAn unspecified sort order. This option is invalid when sorting is required.
    SortOrderNone
    SORT_ORDER_NONENo sorting is applied.
    SortOrderAscending
    SORT_ORDER_ASCENDINGThe lowest-valued entries are selected first.
    SortOrderDescending
    SORT_ORDER_DESCENDINGThe highest-valued entries are selected first.
    SortOrderUnspecified
    SORT_ORDER_UNSPECIFIEDAn unspecified sort order. This option is invalid when sorting is required.
    SortOrderNone
    SORT_ORDER_NONENo sorting is applied.
    SortOrderAscending
    SORT_ORDER_ASCENDINGThe lowest-valued entries are selected first.
    SortOrderDescending
    SORT_ORDER_DESCENDINGThe highest-valued entries are selected first.
    SORT_ORDER_UNSPECIFIED
    SORT_ORDER_UNSPECIFIEDAn unspecified sort order. This option is invalid when sorting is required.
    SORT_ORDER_NONE
    SORT_ORDER_NONENo sorting is applied.
    SORT_ORDER_ASCENDING
    SORT_ORDER_ASCENDINGThe lowest-valued entries are selected first.
    SORT_ORDER_DESCENDING
    SORT_ORDER_DESCENDINGThe highest-valued entries are selected first.
    "SORT_ORDER_UNSPECIFIED"
    SORT_ORDER_UNSPECIFIEDAn unspecified sort order. This option is invalid when sorting is required.
    "SORT_ORDER_NONE"
    SORT_ORDER_NONENo sorting is applied.
    "SORT_ORDER_ASCENDING"
    SORT_ORDER_ASCENDINGThe lowest-valued entries are selected first.
    "SORT_ORDER_DESCENDING"
    SORT_ORDER_DESCENDINGThe highest-valued entries are selected first.

    ErrorReportingPanel, ErrorReportingPanelArgs

    ProjectNames List<string>
    The resource name of the Google Cloud Platform project. Written as projects/{projectID} or projects/{projectNumber}, where {projectID} and {projectNumber} can be found in the Google Cloud console (https://support.google.com/cloud/answer/6158840).Examples: projects/my-project-123, projects/5551234.
    Services List<string>
    An identifier of the service, such as the name of the executable, job, or Google App Engine service name. This field is expected to have a low number of values that are relatively stable over time, as opposed to version, which can be changed whenever new code is deployed.Contains the service name for error reports extracted from Google App Engine logs or default if the App Engine default service is used.
    Versions List<string>
    Represents the source code version that the developer provided, which could represent a version label or a Git SHA-1 hash, for example. For App Engine standard environment, the version is set to the version of the app.
    ProjectNames []string
    The resource name of the Google Cloud Platform project. Written as projects/{projectID} or projects/{projectNumber}, where {projectID} and {projectNumber} can be found in the Google Cloud console (https://support.google.com/cloud/answer/6158840).Examples: projects/my-project-123, projects/5551234.
    Services []string
    An identifier of the service, such as the name of the executable, job, or Google App Engine service name. This field is expected to have a low number of values that are relatively stable over time, as opposed to version, which can be changed whenever new code is deployed.Contains the service name for error reports extracted from Google App Engine logs or default if the App Engine default service is used.
    Versions []string
    Represents the source code version that the developer provided, which could represent a version label or a Git SHA-1 hash, for example. For App Engine standard environment, the version is set to the version of the app.
    projectNames List<String>
    The resource name of the Google Cloud Platform project. Written as projects/{projectID} or projects/{projectNumber}, where {projectID} and {projectNumber} can be found in the Google Cloud console (https://support.google.com/cloud/answer/6158840).Examples: projects/my-project-123, projects/5551234.
    services List<String>
    An identifier of the service, such as the name of the executable, job, or Google App Engine service name. This field is expected to have a low number of values that are relatively stable over time, as opposed to version, which can be changed whenever new code is deployed.Contains the service name for error reports extracted from Google App Engine logs or default if the App Engine default service is used.
    versions List<String>
    Represents the source code version that the developer provided, which could represent a version label or a Git SHA-1 hash, for example. For App Engine standard environment, the version is set to the version of the app.
    projectNames string[]
    The resource name of the Google Cloud Platform project. Written as projects/{projectID} or projects/{projectNumber}, where {projectID} and {projectNumber} can be found in the Google Cloud console (https://support.google.com/cloud/answer/6158840).Examples: projects/my-project-123, projects/5551234.
    services string[]
    An identifier of the service, such as the name of the executable, job, or Google App Engine service name. This field is expected to have a low number of values that are relatively stable over time, as opposed to version, which can be changed whenever new code is deployed.Contains the service name for error reports extracted from Google App Engine logs or default if the App Engine default service is used.
    versions string[]
    Represents the source code version that the developer provided, which could represent a version label or a Git SHA-1 hash, for example. For App Engine standard environment, the version is set to the version of the app.
    project_names Sequence[str]
    The resource name of the Google Cloud Platform project. Written as projects/{projectID} or projects/{projectNumber}, where {projectID} and {projectNumber} can be found in the Google Cloud console (https://support.google.com/cloud/answer/6158840).Examples: projects/my-project-123, projects/5551234.
    services Sequence[str]
    An identifier of the service, such as the name of the executable, job, or Google App Engine service name. This field is expected to have a low number of values that are relatively stable over time, as opposed to version, which can be changed whenever new code is deployed.Contains the service name for error reports extracted from Google App Engine logs or default if the App Engine default service is used.
    versions Sequence[str]
    Represents the source code version that the developer provided, which could represent a version label or a Git SHA-1 hash, for example. For App Engine standard environment, the version is set to the version of the app.
    projectNames List<String>
    The resource name of the Google Cloud Platform project. Written as projects/{projectID} or projects/{projectNumber}, where {projectID} and {projectNumber} can be found in the Google Cloud console (https://support.google.com/cloud/answer/6158840).Examples: projects/my-project-123, projects/5551234.
    services List<String>
    An identifier of the service, such as the name of the executable, job, or Google App Engine service name. This field is expected to have a low number of values that are relatively stable over time, as opposed to version, which can be changed whenever new code is deployed.Contains the service name for error reports extracted from Google App Engine logs or default if the App Engine default service is used.
    versions List<String>
    Represents the source code version that the developer provided, which could represent a version label or a Git SHA-1 hash, for example. For App Engine standard environment, the version is set to the version of the app.

    ErrorReportingPanelResponse, ErrorReportingPanelResponseArgs

    ProjectNames List<string>
    The resource name of the Google Cloud Platform project. Written as projects/{projectID} or projects/{projectNumber}, where {projectID} and {projectNumber} can be found in the Google Cloud console (https://support.google.com/cloud/answer/6158840).Examples: projects/my-project-123, projects/5551234.
    Services List<string>
    An identifier of the service, such as the name of the executable, job, or Google App Engine service name. This field is expected to have a low number of values that are relatively stable over time, as opposed to version, which can be changed whenever new code is deployed.Contains the service name for error reports extracted from Google App Engine logs or default if the App Engine default service is used.
    Versions List<string>
    Represents the source code version that the developer provided, which could represent a version label or a Git SHA-1 hash, for example. For App Engine standard environment, the version is set to the version of the app.
    ProjectNames []string
    The resource name of the Google Cloud Platform project. Written as projects/{projectID} or projects/{projectNumber}, where {projectID} and {projectNumber} can be found in the Google Cloud console (https://support.google.com/cloud/answer/6158840).Examples: projects/my-project-123, projects/5551234.
    Services []string
    An identifier of the service, such as the name of the executable, job, or Google App Engine service name. This field is expected to have a low number of values that are relatively stable over time, as opposed to version, which can be changed whenever new code is deployed.Contains the service name for error reports extracted from Google App Engine logs or default if the App Engine default service is used.
    Versions []string
    Represents the source code version that the developer provided, which could represent a version label or a Git SHA-1 hash, for example. For App Engine standard environment, the version is set to the version of the app.
    projectNames List<String>
    The resource name of the Google Cloud Platform project. Written as projects/{projectID} or projects/{projectNumber}, where {projectID} and {projectNumber} can be found in the Google Cloud console (https://support.google.com/cloud/answer/6158840).Examples: projects/my-project-123, projects/5551234.
    services List<String>
    An identifier of the service, such as the name of the executable, job, or Google App Engine service name. This field is expected to have a low number of values that are relatively stable over time, as opposed to version, which can be changed whenever new code is deployed.Contains the service name for error reports extracted from Google App Engine logs or default if the App Engine default service is used.
    versions List<String>
    Represents the source code version that the developer provided, which could represent a version label or a Git SHA-1 hash, for example. For App Engine standard environment, the version is set to the version of the app.
    projectNames string[]
    The resource name of the Google Cloud Platform project. Written as projects/{projectID} or projects/{projectNumber}, where {projectID} and {projectNumber} can be found in the Google Cloud console (https://support.google.com/cloud/answer/6158840).Examples: projects/my-project-123, projects/5551234.
    services string[]
    An identifier of the service, such as the name of the executable, job, or Google App Engine service name. This field is expected to have a low number of values that are relatively stable over time, as opposed to version, which can be changed whenever new code is deployed.Contains the service name for error reports extracted from Google App Engine logs or default if the App Engine default service is used.
    versions string[]
    Represents the source code version that the developer provided, which could represent a version label or a Git SHA-1 hash, for example. For App Engine standard environment, the version is set to the version of the app.
    project_names Sequence[str]
    The resource name of the Google Cloud Platform project. Written as projects/{projectID} or projects/{projectNumber}, where {projectID} and {projectNumber} can be found in the Google Cloud console (https://support.google.com/cloud/answer/6158840).Examples: projects/my-project-123, projects/5551234.
    services Sequence[str]
    An identifier of the service, such as the name of the executable, job, or Google App Engine service name. This field is expected to have a low number of values that are relatively stable over time, as opposed to version, which can be changed whenever new code is deployed.Contains the service name for error reports extracted from Google App Engine logs or default if the App Engine default service is used.
    versions Sequence[str]
    Represents the source code version that the developer provided, which could represent a version label or a Git SHA-1 hash, for example. For App Engine standard environment, the version is set to the version of the app.
    projectNames List<String>
    The resource name of the Google Cloud Platform project. Written as projects/{projectID} or projects/{projectNumber}, where {projectID} and {projectNumber} can be found in the Google Cloud console (https://support.google.com/cloud/answer/6158840).Examples: projects/my-project-123, projects/5551234.
    services List<String>
    An identifier of the service, such as the name of the executable, job, or Google App Engine service name. This field is expected to have a low number of values that are relatively stable over time, as opposed to version, which can be changed whenever new code is deployed.Contains the service name for error reports extracted from Google App Engine logs or default if the App Engine default service is used.
    versions List<String>
    Represents the source code version that the developer provided, which could represent a version label or a Git SHA-1 hash, for example. For App Engine standard environment, the version is set to the version of the app.

    GaugeView, GaugeViewArgs

    LowerBound double
    The lower bound for this gauge chart. The value of the chart should always be greater than or equal to this.
    UpperBound double
    The upper bound for this gauge chart. The value of the chart should always be less than or equal to this.
    LowerBound float64
    The lower bound for this gauge chart. The value of the chart should always be greater than or equal to this.
    UpperBound float64
    The upper bound for this gauge chart. The value of the chart should always be less than or equal to this.
    lowerBound Double
    The lower bound for this gauge chart. The value of the chart should always be greater than or equal to this.
    upperBound Double
    The upper bound for this gauge chart. The value of the chart should always be less than or equal to this.
    lowerBound number
    The lower bound for this gauge chart. The value of the chart should always be greater than or equal to this.
    upperBound number
    The upper bound for this gauge chart. The value of the chart should always be less than or equal to this.
    lower_bound float
    The lower bound for this gauge chart. The value of the chart should always be greater than or equal to this.
    upper_bound float
    The upper bound for this gauge chart. The value of the chart should always be less than or equal to this.
    lowerBound Number
    The lower bound for this gauge chart. The value of the chart should always be greater than or equal to this.
    upperBound Number
    The upper bound for this gauge chart. The value of the chart should always be less than or equal to this.

    GaugeViewResponse, GaugeViewResponseArgs

    LowerBound double
    The lower bound for this gauge chart. The value of the chart should always be greater than or equal to this.
    UpperBound double
    The upper bound for this gauge chart. The value of the chart should always be less than or equal to this.
    LowerBound float64
    The lower bound for this gauge chart. The value of the chart should always be greater than or equal to this.
    UpperBound float64
    The upper bound for this gauge chart. The value of the chart should always be less than or equal to this.
    lowerBound Double
    The lower bound for this gauge chart. The value of the chart should always be greater than or equal to this.
    upperBound Double
    The upper bound for this gauge chart. The value of the chart should always be less than or equal to this.
    lowerBound number
    The lower bound for this gauge chart. The value of the chart should always be greater than or equal to this.
    upperBound number
    The upper bound for this gauge chart. The value of the chart should always be less than or equal to this.
    lower_bound float
    The lower bound for this gauge chart. The value of the chart should always be greater than or equal to this.
    upper_bound float
    The upper bound for this gauge chart. The value of the chart should always be less than or equal to this.
    lowerBound Number
    The lower bound for this gauge chart. The value of the chart should always be greater than or equal to this.
    upperBound Number
    The upper bound for this gauge chart. The value of the chart should always be less than or equal to this.

    GridLayout, GridLayoutArgs

    Columns string
    The number of columns into which the view's width is divided. If omitted or set to zero, a system default will be used while rendering.
    Widgets List<Pulumi.GoogleNative.Monitoring.V1.Inputs.Widget>
    The informational elements that are arranged into the columns row-first.
    Columns string
    The number of columns into which the view's width is divided. If omitted or set to zero, a system default will be used while rendering.
    Widgets []Widget
    The informational elements that are arranged into the columns row-first.
    columns String
    The number of columns into which the view's width is divided. If omitted or set to zero, a system default will be used while rendering.
    widgets List<Widget>
    The informational elements that are arranged into the columns row-first.
    columns string
    The number of columns into which the view's width is divided. If omitted or set to zero, a system default will be used while rendering.
    widgets Widget[]
    The informational elements that are arranged into the columns row-first.
    columns str
    The number of columns into which the view's width is divided. If omitted or set to zero, a system default will be used while rendering.
    widgets Sequence[Widget]
    The informational elements that are arranged into the columns row-first.
    columns String
    The number of columns into which the view's width is divided. If omitted or set to zero, a system default will be used while rendering.
    widgets List<Property Map>
    The informational elements that are arranged into the columns row-first.

    GridLayoutResponse, GridLayoutResponseArgs

    Columns string
    The number of columns into which the view's width is divided. If omitted or set to zero, a system default will be used while rendering.
    Widgets List<Pulumi.GoogleNative.Monitoring.V1.Inputs.WidgetResponse>
    The informational elements that are arranged into the columns row-first.
    Columns string
    The number of columns into which the view's width is divided. If omitted or set to zero, a system default will be used while rendering.
    Widgets []WidgetResponse
    The informational elements that are arranged into the columns row-first.
    columns String
    The number of columns into which the view's width is divided. If omitted or set to zero, a system default will be used while rendering.
    widgets List<WidgetResponse>
    The informational elements that are arranged into the columns row-first.
    columns string
    The number of columns into which the view's width is divided. If omitted or set to zero, a system default will be used while rendering.
    widgets WidgetResponse[]
    The informational elements that are arranged into the columns row-first.
    columns str
    The number of columns into which the view's width is divided. If omitted or set to zero, a system default will be used while rendering.
    widgets Sequence[WidgetResponse]
    The informational elements that are arranged into the columns row-first.
    columns String
    The number of columns into which the view's width is divided. If omitted or set to zero, a system default will be used while rendering.
    widgets List<Property Map>
    The informational elements that are arranged into the columns row-first.

    IncidentList, IncidentListArgs

    MonitoredResources List<Pulumi.GoogleNative.Monitoring.V1.Inputs.MonitoredResource>
    Optional. The monitored resource for which incidents are listed. The resource doesn't need to be fully specified. That is, you can specify the resource type but not the values of the resource labels. The resource type and labels are used for filtering.
    PolicyNames List<string>
    Optional. A list of alert policy names to filter the incident list by. Don't include the project ID prefix in the policy name. For example, use alertPolicies/utilization.
    MonitoredResources []MonitoredResource
    Optional. The monitored resource for which incidents are listed. The resource doesn't need to be fully specified. That is, you can specify the resource type but not the values of the resource labels. The resource type and labels are used for filtering.
    PolicyNames []string
    Optional. A list of alert policy names to filter the incident list by. Don't include the project ID prefix in the policy name. For example, use alertPolicies/utilization.
    monitoredResources List<MonitoredResource>
    Optional. The monitored resource for which incidents are listed. The resource doesn't need to be fully specified. That is, you can specify the resource type but not the values of the resource labels. The resource type and labels are used for filtering.
    policyNames List<String>
    Optional. A list of alert policy names to filter the incident list by. Don't include the project ID prefix in the policy name. For example, use alertPolicies/utilization.
    monitoredResources MonitoredResource[]
    Optional. The monitored resource for which incidents are listed. The resource doesn't need to be fully specified. That is, you can specify the resource type but not the values of the resource labels. The resource type and labels are used for filtering.
    policyNames string[]
    Optional. A list of alert policy names to filter the incident list by. Don't include the project ID prefix in the policy name. For example, use alertPolicies/utilization.
    monitored_resources Sequence[MonitoredResource]
    Optional. The monitored resource for which incidents are listed. The resource doesn't need to be fully specified. That is, you can specify the resource type but not the values of the resource labels. The resource type and labels are used for filtering.
    policy_names Sequence[str]
    Optional. A list of alert policy names to filter the incident list by. Don't include the project ID prefix in the policy name. For example, use alertPolicies/utilization.
    monitoredResources List<Property Map>
    Optional. The monitored resource for which incidents are listed. The resource doesn't need to be fully specified. That is, you can specify the resource type but not the values of the resource labels. The resource type and labels are used for filtering.
    policyNames List<String>
    Optional. A list of alert policy names to filter the incident list by. Don't include the project ID prefix in the policy name. For example, use alertPolicies/utilization.

    IncidentListResponse, IncidentListResponseArgs

    MonitoredResources List<Pulumi.GoogleNative.Monitoring.V1.Inputs.MonitoredResourceResponse>
    Optional. The monitored resource for which incidents are listed. The resource doesn't need to be fully specified. That is, you can specify the resource type but not the values of the resource labels. The resource type and labels are used for filtering.
    PolicyNames List<string>
    Optional. A list of alert policy names to filter the incident list by. Don't include the project ID prefix in the policy name. For example, use alertPolicies/utilization.
    MonitoredResources []MonitoredResourceResponse
    Optional. The monitored resource for which incidents are listed. The resource doesn't need to be fully specified. That is, you can specify the resource type but not the values of the resource labels. The resource type and labels are used for filtering.
    PolicyNames []string
    Optional. A list of alert policy names to filter the incident list by. Don't include the project ID prefix in the policy name. For example, use alertPolicies/utilization.
    monitoredResources List<MonitoredResourceResponse>
    Optional. The monitored resource for which incidents are listed. The resource doesn't need to be fully specified. That is, you can specify the resource type but not the values of the resource labels. The resource type and labels are used for filtering.
    policyNames List<String>
    Optional. A list of alert policy names to filter the incident list by. Don't include the project ID prefix in the policy name. For example, use alertPolicies/utilization.
    monitoredResources MonitoredResourceResponse[]
    Optional. The monitored resource for which incidents are listed. The resource doesn't need to be fully specified. That is, you can specify the resource type but not the values of the resource labels. The resource type and labels are used for filtering.
    policyNames string[]
    Optional. A list of alert policy names to filter the incident list by. Don't include the project ID prefix in the policy name. For example, use alertPolicies/utilization.
    monitored_resources Sequence[MonitoredResourceResponse]
    Optional. The monitored resource for which incidents are listed. The resource doesn't need to be fully specified. That is, you can specify the resource type but not the values of the resource labels. The resource type and labels are used for filtering.
    policy_names Sequence[str]
    Optional. A list of alert policy names to filter the incident list by. Don't include the project ID prefix in the policy name. For example, use alertPolicies/utilization.
    monitoredResources List<Property Map>
    Optional. The monitored resource for which incidents are listed. The resource doesn't need to be fully specified. That is, you can specify the resource type but not the values of the resource labels. The resource type and labels are used for filtering.
    policyNames List<String>
    Optional. A list of alert policy names to filter the incident list by. Don't include the project ID prefix in the policy name. For example, use alertPolicies/utilization.

    LogsPanel, LogsPanelArgs

    Filter string
    A filter that chooses which log entries to return. See Advanced Logs Queries (https://cloud.google.com/logging/docs/view/advanced-queries). Only log entries that match the filter are returned. An empty filter matches all log entries.
    ResourceNames List<string>
    The names of logging resources to collect logs for. Currently only projects are supported. If empty, the widget will default to the host project.
    Filter string
    A filter that chooses which log entries to return. See Advanced Logs Queries (https://cloud.google.com/logging/docs/view/advanced-queries). Only log entries that match the filter are returned. An empty filter matches all log entries.
    ResourceNames []string
    The names of logging resources to collect logs for. Currently only projects are supported. If empty, the widget will default to the host project.
    filter String
    A filter that chooses which log entries to return. See Advanced Logs Queries (https://cloud.google.com/logging/docs/view/advanced-queries). Only log entries that match the filter are returned. An empty filter matches all log entries.
    resourceNames List<String>
    The names of logging resources to collect logs for. Currently only projects are supported. If empty, the widget will default to the host project.
    filter string
    A filter that chooses which log entries to return. See Advanced Logs Queries (https://cloud.google.com/logging/docs/view/advanced-queries). Only log entries that match the filter are returned. An empty filter matches all log entries.
    resourceNames string[]
    The names of logging resources to collect logs for. Currently only projects are supported. If empty, the widget will default to the host project.
    filter str
    A filter that chooses which log entries to return. See Advanced Logs Queries (https://cloud.google.com/logging/docs/view/advanced-queries). Only log entries that match the filter are returned. An empty filter matches all log entries.
    resource_names Sequence[str]
    The names of logging resources to collect logs for. Currently only projects are supported. If empty, the widget will default to the host project.
    filter String
    A filter that chooses which log entries to return. See Advanced Logs Queries (https://cloud.google.com/logging/docs/view/advanced-queries). Only log entries that match the filter are returned. An empty filter matches all log entries.
    resourceNames List<String>
    The names of logging resources to collect logs for. Currently only projects are supported. If empty, the widget will default to the host project.

    LogsPanelResponse, LogsPanelResponseArgs

    Filter string
    A filter that chooses which log entries to return. See Advanced Logs Queries (https://cloud.google.com/logging/docs/view/advanced-queries). Only log entries that match the filter are returned. An empty filter matches all log entries.
    ResourceNames List<string>
    The names of logging resources to collect logs for. Currently only projects are supported. If empty, the widget will default to the host project.
    Filter string
    A filter that chooses which log entries to return. See Advanced Logs Queries (https://cloud.google.com/logging/docs/view/advanced-queries). Only log entries that match the filter are returned. An empty filter matches all log entries.
    ResourceNames []string
    The names of logging resources to collect logs for. Currently only projects are supported. If empty, the widget will default to the host project.
    filter String
    A filter that chooses which log entries to return. See Advanced Logs Queries (https://cloud.google.com/logging/docs/view/advanced-queries). Only log entries that match the filter are returned. An empty filter matches all log entries.
    resourceNames List<String>
    The names of logging resources to collect logs for. Currently only projects are supported. If empty, the widget will default to the host project.
    filter string
    A filter that chooses which log entries to return. See Advanced Logs Queries (https://cloud.google.com/logging/docs/view/advanced-queries). Only log entries that match the filter are returned. An empty filter matches all log entries.
    resourceNames string[]
    The names of logging resources to collect logs for. Currently only projects are supported. If empty, the widget will default to the host project.
    filter str
    A filter that chooses which log entries to return. See Advanced Logs Queries (https://cloud.google.com/logging/docs/view/advanced-queries). Only log entries that match the filter are returned. An empty filter matches all log entries.
    resource_names Sequence[str]
    The names of logging resources to collect logs for. Currently only projects are supported. If empty, the widget will default to the host project.
    filter String
    A filter that chooses which log entries to return. See Advanced Logs Queries (https://cloud.google.com/logging/docs/view/advanced-queries). Only log entries that match the filter are returned. An empty filter matches all log entries.
    resourceNames List<String>
    The names of logging resources to collect logs for. Currently only projects are supported. If empty, the widget will default to the host project.

    Measure, MeasureArgs

    AggregationFunction Pulumi.GoogleNative.Monitoring.V1.Inputs.AggregationFunction
    The aggregation function applied to the input column. This must not be set to "none" unless binning is disabled on the dimension. The aggregation function is used to group points on the dimension bins.
    Column string
    The column name within in the dataset used for the measure.
    AggregationFunction AggregationFunction
    The aggregation function applied to the input column. This must not be set to "none" unless binning is disabled on the dimension. The aggregation function is used to group points on the dimension bins.
    Column string
    The column name within in the dataset used for the measure.
    aggregationFunction AggregationFunction
    The aggregation function applied to the input column. This must not be set to "none" unless binning is disabled on the dimension. The aggregation function is used to group points on the dimension bins.
    column String
    The column name within in the dataset used for the measure.
    aggregationFunction AggregationFunction
    The aggregation function applied to the input column. This must not be set to "none" unless binning is disabled on the dimension. The aggregation function is used to group points on the dimension bins.
    column string
    The column name within in the dataset used for the measure.
    aggregation_function AggregationFunction
    The aggregation function applied to the input column. This must not be set to "none" unless binning is disabled on the dimension. The aggregation function is used to group points on the dimension bins.
    column str
    The column name within in the dataset used for the measure.
    aggregationFunction Property Map
    The aggregation function applied to the input column. This must not be set to "none" unless binning is disabled on the dimension. The aggregation function is used to group points on the dimension bins.
    column String
    The column name within in the dataset used for the measure.

    MeasureResponse, MeasureResponseArgs

    AggregationFunction Pulumi.GoogleNative.Monitoring.V1.Inputs.AggregationFunctionResponse
    The aggregation function applied to the input column. This must not be set to "none" unless binning is disabled on the dimension. The aggregation function is used to group points on the dimension bins.
    Column string
    The column name within in the dataset used for the measure.
    AggregationFunction AggregationFunctionResponse
    The aggregation function applied to the input column. This must not be set to "none" unless binning is disabled on the dimension. The aggregation function is used to group points on the dimension bins.
    Column string
    The column name within in the dataset used for the measure.
    aggregationFunction AggregationFunctionResponse
    The aggregation function applied to the input column. This must not be set to "none" unless binning is disabled on the dimension. The aggregation function is used to group points on the dimension bins.
    column String
    The column name within in the dataset used for the measure.
    aggregationFunction AggregationFunctionResponse
    The aggregation function applied to the input column. This must not be set to "none" unless binning is disabled on the dimension. The aggregation function is used to group points on the dimension bins.
    column string
    The column name within in the dataset used for the measure.
    aggregation_function AggregationFunctionResponse
    The aggregation function applied to the input column. This must not be set to "none" unless binning is disabled on the dimension. The aggregation function is used to group points on the dimension bins.
    column str
    The column name within in the dataset used for the measure.
    aggregationFunction Property Map
    The aggregation function applied to the input column. This must not be set to "none" unless binning is disabled on the dimension. The aggregation function is used to group points on the dimension bins.
    column String
    The column name within in the dataset used for the measure.

    MonitoredResource, MonitoredResourceArgs

    Labels Dictionary<string, string>
    Values for all of the labels listed in the associated monitored resource descriptor. For example, Compute Engine VM instances use the labels "project_id", "instance_id", and "zone".
    Type string
    The monitored resource type. This field must match the type field of a MonitoredResourceDescriptor object. For example, the type of a Compute Engine VM instance is gce_instance. For a list of types, see Monitoring resource types (https://cloud.google.com/monitoring/api/resources) and Logging resource types (https://cloud.google.com/logging/docs/api/v2/resource-list).
    Labels map[string]string
    Values for all of the labels listed in the associated monitored resource descriptor. For example, Compute Engine VM instances use the labels "project_id", "instance_id", and "zone".
    Type string
    The monitored resource type. This field must match the type field of a MonitoredResourceDescriptor object. For example, the type of a Compute Engine VM instance is gce_instance. For a list of types, see Monitoring resource types (https://cloud.google.com/monitoring/api/resources) and Logging resource types (https://cloud.google.com/logging/docs/api/v2/resource-list).
    labels Map<String,String>
    Values for all of the labels listed in the associated monitored resource descriptor. For example, Compute Engine VM instances use the labels "project_id", "instance_id", and "zone".
    type String
    The monitored resource type. This field must match the type field of a MonitoredResourceDescriptor object. For example, the type of a Compute Engine VM instance is gce_instance. For a list of types, see Monitoring resource types (https://cloud.google.com/monitoring/api/resources) and Logging resource types (https://cloud.google.com/logging/docs/api/v2/resource-list).
    labels {[key: string]: string}
    Values for all of the labels listed in the associated monitored resource descriptor. For example, Compute Engine VM instances use the labels "project_id", "instance_id", and "zone".
    type string
    The monitored resource type. This field must match the type field of a MonitoredResourceDescriptor object. For example, the type of a Compute Engine VM instance is gce_instance. For a list of types, see Monitoring resource types (https://cloud.google.com/monitoring/api/resources) and Logging resource types (https://cloud.google.com/logging/docs/api/v2/resource-list).
    labels Mapping[str, str]
    Values for all of the labels listed in the associated monitored resource descriptor. For example, Compute Engine VM instances use the labels "project_id", "instance_id", and "zone".
    type str
    The monitored resource type. This field must match the type field of a MonitoredResourceDescriptor object. For example, the type of a Compute Engine VM instance is gce_instance. For a list of types, see Monitoring resource types (https://cloud.google.com/monitoring/api/resources) and Logging resource types (https://cloud.google.com/logging/docs/api/v2/resource-list).
    labels Map<String>
    Values for all of the labels listed in the associated monitored resource descriptor. For example, Compute Engine VM instances use the labels "project_id", "instance_id", and "zone".
    type String
    The monitored resource type. This field must match the type field of a MonitoredResourceDescriptor object. For example, the type of a Compute Engine VM instance is gce_instance. For a list of types, see Monitoring resource types (https://cloud.google.com/monitoring/api/resources) and Logging resource types (https://cloud.google.com/logging/docs/api/v2/resource-list).

    MonitoredResourceResponse, MonitoredResourceResponseArgs

    Labels Dictionary<string, string>
    Values for all of the labels listed in the associated monitored resource descriptor. For example, Compute Engine VM instances use the labels "project_id", "instance_id", and "zone".
    Type string
    The monitored resource type. This field must match the type field of a MonitoredResourceDescriptor object. For example, the type of a Compute Engine VM instance is gce_instance. For a list of types, see Monitoring resource types (https://cloud.google.com/monitoring/api/resources) and Logging resource types (https://cloud.google.com/logging/docs/api/v2/resource-list).
    Labels map[string]string
    Values for all of the labels listed in the associated monitored resource descriptor. For example, Compute Engine VM instances use the labels "project_id", "instance_id", and "zone".
    Type string
    The monitored resource type. This field must match the type field of a MonitoredResourceDescriptor object. For example, the type of a Compute Engine VM instance is gce_instance. For a list of types, see Monitoring resource types (https://cloud.google.com/monitoring/api/resources) and Logging resource types (https://cloud.google.com/logging/docs/api/v2/resource-list).
    labels Map<String,String>
    Values for all of the labels listed in the associated monitored resource descriptor. For example, Compute Engine VM instances use the labels "project_id", "instance_id", and "zone".
    type String
    The monitored resource type. This field must match the type field of a MonitoredResourceDescriptor object. For example, the type of a Compute Engine VM instance is gce_instance. For a list of types, see Monitoring resource types (https://cloud.google.com/monitoring/api/resources) and Logging resource types (https://cloud.google.com/logging/docs/api/v2/resource-list).
    labels {[key: string]: string}
    Values for all of the labels listed in the associated monitored resource descriptor. For example, Compute Engine VM instances use the labels "project_id", "instance_id", and "zone".
    type string
    The monitored resource type. This field must match the type field of a MonitoredResourceDescriptor object. For example, the type of a Compute Engine VM instance is gce_instance. For a list of types, see Monitoring resource types (https://cloud.google.com/monitoring/api/resources) and Logging resource types (https://cloud.google.com/logging/docs/api/v2/resource-list).
    labels Mapping[str, str]
    Values for all of the labels listed in the associated monitored resource descriptor. For example, Compute Engine VM instances use the labels "project_id", "instance_id", and "zone".
    type str
    The monitored resource type. This field must match the type field of a MonitoredResourceDescriptor object. For example, the type of a Compute Engine VM instance is gce_instance. For a list of types, see Monitoring resource types (https://cloud.google.com/monitoring/api/resources) and Logging resource types (https://cloud.google.com/logging/docs/api/v2/resource-list).
    labels Map<String>
    Values for all of the labels listed in the associated monitored resource descriptor. For example, Compute Engine VM instances use the labels "project_id", "instance_id", and "zone".
    type String
    The monitored resource type. This field must match the type field of a MonitoredResourceDescriptor object. For example, the type of a Compute Engine VM instance is gce_instance. For a list of types, see Monitoring resource types (https://cloud.google.com/monitoring/api/resources) and Logging resource types (https://cloud.google.com/logging/docs/api/v2/resource-list).

    MosaicLayout, MosaicLayoutArgs

    Columns int
    The number of columns in the mosaic grid. The number of columns must be between 1 and 12, inclusive.
    Tiles List<Pulumi.GoogleNative.Monitoring.V1.Inputs.Tile>
    The tiles to display.
    Columns int
    The number of columns in the mosaic grid. The number of columns must be between 1 and 12, inclusive.
    Tiles []Tile
    The tiles to display.
    columns Integer
    The number of columns in the mosaic grid. The number of columns must be between 1 and 12, inclusive.
    tiles List<Tile>
    The tiles to display.
    columns number
    The number of columns in the mosaic grid. The number of columns must be between 1 and 12, inclusive.
    tiles Tile[]
    The tiles to display.
    columns int
    The number of columns in the mosaic grid. The number of columns must be between 1 and 12, inclusive.
    tiles Sequence[Tile]
    The tiles to display.
    columns Number
    The number of columns in the mosaic grid. The number of columns must be between 1 and 12, inclusive.
    tiles List<Property Map>
    The tiles to display.

    MosaicLayoutResponse, MosaicLayoutResponseArgs

    Columns int
    The number of columns in the mosaic grid. The number of columns must be between 1 and 12, inclusive.
    Tiles List<Pulumi.GoogleNative.Monitoring.V1.Inputs.TileResponse>
    The tiles to display.
    Columns int
    The number of columns in the mosaic grid. The number of columns must be between 1 and 12, inclusive.
    Tiles []TileResponse
    The tiles to display.
    columns Integer
    The number of columns in the mosaic grid. The number of columns must be between 1 and 12, inclusive.
    tiles List<TileResponse>
    The tiles to display.
    columns number
    The number of columns in the mosaic grid. The number of columns must be between 1 and 12, inclusive.
    tiles TileResponse[]
    The tiles to display.
    columns int
    The number of columns in the mosaic grid. The number of columns must be between 1 and 12, inclusive.
    tiles Sequence[TileResponse]
    The tiles to display.
    columns Number
    The number of columns in the mosaic grid. The number of columns must be between 1 and 12, inclusive.
    tiles List<Property Map>
    The tiles to display.

    OpsAnalyticsQuery, OpsAnalyticsQueryArgs

    Sql string
    A SQL query to fetch time series, category series, or numeric series data.
    Sql string
    A SQL query to fetch time series, category series, or numeric series data.
    sql String
    A SQL query to fetch time series, category series, or numeric series data.
    sql string
    A SQL query to fetch time series, category series, or numeric series data.
    sql str
    A SQL query to fetch time series, category series, or numeric series data.
    sql String
    A SQL query to fetch time series, category series, or numeric series data.

    OpsAnalyticsQueryResponse, OpsAnalyticsQueryResponseArgs

    Sql string
    A SQL query to fetch time series, category series, or numeric series data.
    Sql string
    A SQL query to fetch time series, category series, or numeric series data.
    sql String
    A SQL query to fetch time series, category series, or numeric series data.
    sql string
    A SQL query to fetch time series, category series, or numeric series data.
    sql str
    A SQL query to fetch time series, category series, or numeric series data.
    sql String
    A SQL query to fetch time series, category series, or numeric series data.

    Parameter, ParameterArgs

    DoubleValue double
    A floating-point parameter value.
    IntValue string
    An integer parameter value.
    DoubleValue float64
    A floating-point parameter value.
    IntValue string
    An integer parameter value.
    doubleValue Double
    A floating-point parameter value.
    intValue String
    An integer parameter value.
    doubleValue number
    A floating-point parameter value.
    intValue string
    An integer parameter value.
    double_value float
    A floating-point parameter value.
    int_value str
    An integer parameter value.
    doubleValue Number
    A floating-point parameter value.
    intValue String
    An integer parameter value.

    ParameterResponse, ParameterResponseArgs

    DoubleValue double
    A floating-point parameter value.
    IntValue string
    An integer parameter value.
    DoubleValue float64
    A floating-point parameter value.
    IntValue string
    An integer parameter value.
    doubleValue Double
    A floating-point parameter value.
    intValue String
    An integer parameter value.
    doubleValue number
    A floating-point parameter value.
    intValue string
    An integer parameter value.
    double_value float
    A floating-point parameter value.
    int_value str
    An integer parameter value.
    doubleValue Number
    A floating-point parameter value.
    intValue String
    An integer parameter value.

    PickTimeSeriesFilter, PickTimeSeriesFilterArgs

    Direction Pulumi.GoogleNative.Monitoring.V1.PickTimeSeriesFilterDirection
    How to use the ranking to select time series that pass through the filter.
    NumTimeSeries int
    How many time series to allow to pass through the filter.
    RankingMethod Pulumi.GoogleNative.Monitoring.V1.PickTimeSeriesFilterRankingMethod
    ranking_method is applied to each time series independently to produce the value which will be used to compare the time series to other time series.
    Direction PickTimeSeriesFilterDirection
    How to use the ranking to select time series that pass through the filter.
    NumTimeSeries int
    How many time series to allow to pass through the filter.
    RankingMethod PickTimeSeriesFilterRankingMethod
    ranking_method is applied to each time series independently to produce the value which will be used to compare the time series to other time series.
    direction PickTimeSeriesFilterDirection
    How to use the ranking to select time series that pass through the filter.
    numTimeSeries Integer
    How many time series to allow to pass through the filter.
    rankingMethod PickTimeSeriesFilterRankingMethod
    ranking_method is applied to each time series independently to produce the value which will be used to compare the time series to other time series.
    direction PickTimeSeriesFilterDirection
    How to use the ranking to select time series that pass through the filter.
    numTimeSeries number
    How many time series to allow to pass through the filter.
    rankingMethod PickTimeSeriesFilterRankingMethod
    ranking_method is applied to each time series independently to produce the value which will be used to compare the time series to other time series.
    direction PickTimeSeriesFilterDirection
    How to use the ranking to select time series that pass through the filter.
    num_time_series int
    How many time series to allow to pass through the filter.
    ranking_method PickTimeSeriesFilterRankingMethod
    ranking_method is applied to each time series independently to produce the value which will be used to compare the time series to other time series.
    direction "DIRECTION_UNSPECIFIED" | "TOP" | "BOTTOM"
    How to use the ranking to select time series that pass through the filter.
    numTimeSeries Number
    How many time series to allow to pass through the filter.
    rankingMethod "METHOD_UNSPECIFIED" | "METHOD_MEAN" | "METHOD_MAX" | "METHOD_MIN" | "METHOD_SUM" | "METHOD_LATEST"
    ranking_method is applied to each time series independently to produce the value which will be used to compare the time series to other time series.

    PickTimeSeriesFilterDirection, PickTimeSeriesFilterDirectionArgs

    DirectionUnspecified
    DIRECTION_UNSPECIFIEDNot allowed. You must specify a different Direction if you specify a PickTimeSeriesFilter.
    Top
    TOPPass the highest num_time_series ranking inputs.
    Bottom
    BOTTOMPass the lowest num_time_series ranking inputs.
    PickTimeSeriesFilterDirectionDirectionUnspecified
    DIRECTION_UNSPECIFIEDNot allowed. You must specify a different Direction if you specify a PickTimeSeriesFilter.
    PickTimeSeriesFilterDirectionTop
    TOPPass the highest num_time_series ranking inputs.
    PickTimeSeriesFilterDirectionBottom
    BOTTOMPass the lowest num_time_series ranking inputs.
    DirectionUnspecified
    DIRECTION_UNSPECIFIEDNot allowed. You must specify a different Direction if you specify a PickTimeSeriesFilter.
    Top
    TOPPass the highest num_time_series ranking inputs.
    Bottom
    BOTTOMPass the lowest num_time_series ranking inputs.
    DirectionUnspecified
    DIRECTION_UNSPECIFIEDNot allowed. You must specify a different Direction if you specify a PickTimeSeriesFilter.
    Top
    TOPPass the highest num_time_series ranking inputs.
    Bottom
    BOTTOMPass the lowest num_time_series ranking inputs.
    DIRECTION_UNSPECIFIED
    DIRECTION_UNSPECIFIEDNot allowed. You must specify a different Direction if you specify a PickTimeSeriesFilter.
    TOP
    TOPPass the highest num_time_series ranking inputs.
    BOTTOM
    BOTTOMPass the lowest num_time_series ranking inputs.
    "DIRECTION_UNSPECIFIED"
    DIRECTION_UNSPECIFIEDNot allowed. You must specify a different Direction if you specify a PickTimeSeriesFilter.
    "TOP"
    TOPPass the highest num_time_series ranking inputs.
    "BOTTOM"
    BOTTOMPass the lowest num_time_series ranking inputs.

    PickTimeSeriesFilterRankingMethod, PickTimeSeriesFilterRankingMethodArgs

    MethodUnspecified
    METHOD_UNSPECIFIEDNot allowed. You must specify a different Method if you specify a PickTimeSeriesFilter.
    MethodMean
    METHOD_MEANSelect the mean of all values.
    MethodMax
    METHOD_MAXSelect the maximum value.
    MethodMin
    METHOD_MINSelect the minimum value.
    MethodSum
    METHOD_SUMCompute the sum of all values.
    MethodLatest
    METHOD_LATESTSelect the most recent value.
    PickTimeSeriesFilterRankingMethodMethodUnspecified
    METHOD_UNSPECIFIEDNot allowed. You must specify a different Method if you specify a PickTimeSeriesFilter.
    PickTimeSeriesFilterRankingMethodMethodMean
    METHOD_MEANSelect the mean of all values.
    PickTimeSeriesFilterRankingMethodMethodMax
    METHOD_MAXSelect the maximum value.
    PickTimeSeriesFilterRankingMethodMethodMin
    METHOD_MINSelect the minimum value.
    PickTimeSeriesFilterRankingMethodMethodSum
    METHOD_SUMCompute the sum of all values.
    PickTimeSeriesFilterRankingMethodMethodLatest
    METHOD_LATESTSelect the most recent value.
    MethodUnspecified
    METHOD_UNSPECIFIEDNot allowed. You must specify a different Method if you specify a PickTimeSeriesFilter.
    MethodMean
    METHOD_MEANSelect the mean of all values.
    MethodMax
    METHOD_MAXSelect the maximum value.
    MethodMin
    METHOD_MINSelect the minimum value.
    MethodSum
    METHOD_SUMCompute the sum of all values.
    MethodLatest
    METHOD_LATESTSelect the most recent value.
    MethodUnspecified
    METHOD_UNSPECIFIEDNot allowed. You must specify a different Method if you specify a PickTimeSeriesFilter.
    MethodMean
    METHOD_MEANSelect the mean of all values.
    MethodMax
    METHOD_MAXSelect the maximum value.
    MethodMin
    METHOD_MINSelect the minimum value.
    MethodSum
    METHOD_SUMCompute the sum of all values.
    MethodLatest
    METHOD_LATESTSelect the most recent value.
    METHOD_UNSPECIFIED
    METHOD_UNSPECIFIEDNot allowed. You must specify a different Method if you specify a PickTimeSeriesFilter.
    METHOD_MEAN
    METHOD_MEANSelect the mean of all values.
    METHOD_MAX
    METHOD_MAXSelect the maximum value.
    METHOD_MIN
    METHOD_MINSelect the minimum value.
    METHOD_SUM
    METHOD_SUMCompute the sum of all values.
    METHOD_LATEST
    METHOD_LATESTSelect the most recent value.
    "METHOD_UNSPECIFIED"
    METHOD_UNSPECIFIEDNot allowed. You must specify a different Method if you specify a PickTimeSeriesFilter.
    "METHOD_MEAN"
    METHOD_MEANSelect the mean of all values.
    "METHOD_MAX"
    METHOD_MAXSelect the maximum value.
    "METHOD_MIN"
    METHOD_MINSelect the minimum value.
    "METHOD_SUM"
    METHOD_SUMCompute the sum of all values.
    "METHOD_LATEST"
    METHOD_LATESTSelect the most recent value.

    PickTimeSeriesFilterResponse, PickTimeSeriesFilterResponseArgs

    Direction string
    How to use the ranking to select time series that pass through the filter.
    NumTimeSeries int
    How many time series to allow to pass through the filter.
    RankingMethod string
    ranking_method is applied to each time series independently to produce the value which will be used to compare the time series to other time series.
    Direction string
    How to use the ranking to select time series that pass through the filter.
    NumTimeSeries int
    How many time series to allow to pass through the filter.
    RankingMethod string
    ranking_method is applied to each time series independently to produce the value which will be used to compare the time series to other time series.
    direction String
    How to use the ranking to select time series that pass through the filter.
    numTimeSeries Integer
    How many time series to allow to pass through the filter.
    rankingMethod String
    ranking_method is applied to each time series independently to produce the value which will be used to compare the time series to other time series.
    direction string
    How to use the ranking to select time series that pass through the filter.
    numTimeSeries number
    How many time series to allow to pass through the filter.
    rankingMethod string
    ranking_method is applied to each time series independently to produce the value which will be used to compare the time series to other time series.
    direction str
    How to use the ranking to select time series that pass through the filter.
    num_time_series int
    How many time series to allow to pass through the filter.
    ranking_method str
    ranking_method is applied to each time series independently to produce the value which will be used to compare the time series to other time series.
    direction String
    How to use the ranking to select time series that pass through the filter.
    numTimeSeries Number
    How many time series to allow to pass through the filter.
    rankingMethod String
    ranking_method is applied to each time series independently to produce the value which will be used to compare the time series to other time series.

    PieChart, PieChartArgs

    ChartType Pulumi.GoogleNative.Monitoring.V1.PieChartChartType
    Indicates the visualization type for the PieChart.
    DataSets List<Pulumi.GoogleNative.Monitoring.V1.Inputs.PieChartDataSet>
    The queries for the chart's data.
    ShowLabels bool
    Optional. Indicates whether or not the pie chart should show slices' labels
    ChartType PieChartChartType
    Indicates the visualization type for the PieChart.
    DataSets []PieChartDataSet
    The queries for the chart's data.
    ShowLabels bool
    Optional. Indicates whether or not the pie chart should show slices' labels
    chartType PieChartChartType
    Indicates the visualization type for the PieChart.
    dataSets List<PieChartDataSet>
    The queries for the chart's data.
    showLabels Boolean
    Optional. Indicates whether or not the pie chart should show slices' labels
    chartType PieChartChartType
    Indicates the visualization type for the PieChart.
    dataSets PieChartDataSet[]
    The queries for the chart's data.
    showLabels boolean
    Optional. Indicates whether or not the pie chart should show slices' labels
    chart_type PieChartChartType
    Indicates the visualization type for the PieChart.
    data_sets Sequence[PieChartDataSet]
    The queries for the chart's data.
    show_labels bool
    Optional. Indicates whether or not the pie chart should show slices' labels
    chartType "PIE_CHART_TYPE_UNSPECIFIED" | "PIE" | "DONUT"
    Indicates the visualization type for the PieChart.
    dataSets List<Property Map>
    The queries for the chart's data.
    showLabels Boolean
    Optional. Indicates whether or not the pie chart should show slices' labels

    PieChartChartType, PieChartChartTypeArgs

    PieChartTypeUnspecified
    PIE_CHART_TYPE_UNSPECIFIEDThe zero value. No type specified. Do not use.
    Pie
    PIEA Pie type PieChart.
    Donut
    DONUTSimilar to PIE, but the DONUT type PieChart has a hole in the middle.
    PieChartChartTypePieChartTypeUnspecified
    PIE_CHART_TYPE_UNSPECIFIEDThe zero value. No type specified. Do not use.
    PieChartChartTypePie
    PIEA Pie type PieChart.
    PieChartChartTypeDonut
    DONUTSimilar to PIE, but the DONUT type PieChart has a hole in the middle.
    PieChartTypeUnspecified
    PIE_CHART_TYPE_UNSPECIFIEDThe zero value. No type specified. Do not use.
    Pie
    PIEA Pie type PieChart.
    Donut
    DONUTSimilar to PIE, but the DONUT type PieChart has a hole in the middle.
    PieChartTypeUnspecified
    PIE_CHART_TYPE_UNSPECIFIEDThe zero value. No type specified. Do not use.
    Pie
    PIEA Pie type PieChart.
    Donut
    DONUTSimilar to PIE, but the DONUT type PieChart has a hole in the middle.
    PIE_CHART_TYPE_UNSPECIFIED
    PIE_CHART_TYPE_UNSPECIFIEDThe zero value. No type specified. Do not use.
    PIE
    PIEA Pie type PieChart.
    DONUT
    DONUTSimilar to PIE, but the DONUT type PieChart has a hole in the middle.
    "PIE_CHART_TYPE_UNSPECIFIED"
    PIE_CHART_TYPE_UNSPECIFIEDThe zero value. No type specified. Do not use.
    "PIE"
    PIEA Pie type PieChart.
    "DONUT"
    DONUTSimilar to PIE, but the DONUT type PieChart has a hole in the middle.

    PieChartDataSet, PieChartDataSetArgs

    TimeSeriesQuery Pulumi.GoogleNative.Monitoring.V1.Inputs.TimeSeriesQuery
    The query for the PieChart. See, google.monitoring.dashboard.v1.TimeSeriesQuery.
    MinAlignmentPeriod string
    Optional. The lower bound on data point frequency for this data set, implemented by specifying the minimum alignment period to use in a time series query. For example, if the data is published once every 10 minutes, the min_alignment_period should be at least 10 minutes. It would not make sense to fetch and align data at one minute intervals.
    SliceNameTemplate string
    Optional. A template for the name of the slice. This name will be displayed in the legend and the tooltip of the pie chart. It replaces the auto-generated names for the slices. For example, if the template is set to ${resource.labels.zone}, the zone's value will be used for the name instead of the default name.
    TimeSeriesQuery TimeSeriesQuery
    The query for the PieChart. See, google.monitoring.dashboard.v1.TimeSeriesQuery.
    MinAlignmentPeriod string
    Optional. The lower bound on data point frequency for this data set, implemented by specifying the minimum alignment period to use in a time series query. For example, if the data is published once every 10 minutes, the min_alignment_period should be at least 10 minutes. It would not make sense to fetch and align data at one minute intervals.
    SliceNameTemplate string
    Optional. A template for the name of the slice. This name will be displayed in the legend and the tooltip of the pie chart. It replaces the auto-generated names for the slices. For example, if the template is set to ${resource.labels.zone}, the zone's value will be used for the name instead of the default name.
    timeSeriesQuery TimeSeriesQuery
    The query for the PieChart. See, google.monitoring.dashboard.v1.TimeSeriesQuery.
    minAlignmentPeriod String
    Optional. The lower bound on data point frequency for this data set, implemented by specifying the minimum alignment period to use in a time series query. For example, if the data is published once every 10 minutes, the min_alignment_period should be at least 10 minutes. It would not make sense to fetch and align data at one minute intervals.
    sliceNameTemplate String
    Optional. A template for the name of the slice. This name will be displayed in the legend and the tooltip of the pie chart. It replaces the auto-generated names for the slices. For example, if the template is set to ${resource.labels.zone}, the zone's value will be used for the name instead of the default name.
    timeSeriesQuery TimeSeriesQuery
    The query for the PieChart. See, google.monitoring.dashboard.v1.TimeSeriesQuery.
    minAlignmentPeriod string
    Optional. The lower bound on data point frequency for this data set, implemented by specifying the minimum alignment period to use in a time series query. For example, if the data is published once every 10 minutes, the min_alignment_period should be at least 10 minutes. It would not make sense to fetch and align data at one minute intervals.
    sliceNameTemplate string
    Optional. A template for the name of the slice. This name will be displayed in the legend and the tooltip of the pie chart. It replaces the auto-generated names for the slices. For example, if the template is set to ${resource.labels.zone}, the zone's value will be used for the name instead of the default name.
    time_series_query TimeSeriesQuery
    The query for the PieChart. See, google.monitoring.dashboard.v1.TimeSeriesQuery.
    min_alignment_period str
    Optional. The lower bound on data point frequency for this data set, implemented by specifying the minimum alignment period to use in a time series query. For example, if the data is published once every 10 minutes, the min_alignment_period should be at least 10 minutes. It would not make sense to fetch and align data at one minute intervals.
    slice_name_template str
    Optional. A template for the name of the slice. This name will be displayed in the legend and the tooltip of the pie chart. It replaces the auto-generated names for the slices. For example, if the template is set to ${resource.labels.zone}, the zone's value will be used for the name instead of the default name.
    timeSeriesQuery Property Map
    The query for the PieChart. See, google.monitoring.dashboard.v1.TimeSeriesQuery.
    minAlignmentPeriod String
    Optional. The lower bound on data point frequency for this data set, implemented by specifying the minimum alignment period to use in a time series query. For example, if the data is published once every 10 minutes, the min_alignment_period should be at least 10 minutes. It would not make sense to fetch and align data at one minute intervals.
    sliceNameTemplate String
    Optional. A template for the name of the slice. This name will be displayed in the legend and the tooltip of the pie chart. It replaces the auto-generated names for the slices. For example, if the template is set to ${resource.labels.zone}, the zone's value will be used for the name instead of the default name.

    PieChartDataSetResponse, PieChartDataSetResponseArgs

    MinAlignmentPeriod string
    Optional. The lower bound on data point frequency for this data set, implemented by specifying the minimum alignment period to use in a time series query. For example, if the data is published once every 10 minutes, the min_alignment_period should be at least 10 minutes. It would not make sense to fetch and align data at one minute intervals.
    SliceNameTemplate string
    Optional. A template for the name of the slice. This name will be displayed in the legend and the tooltip of the pie chart. It replaces the auto-generated names for the slices. For example, if the template is set to ${resource.labels.zone}, the zone's value will be used for the name instead of the default name.
    TimeSeriesQuery Pulumi.GoogleNative.Monitoring.V1.Inputs.TimeSeriesQueryResponse
    The query for the PieChart. See, google.monitoring.dashboard.v1.TimeSeriesQuery.
    MinAlignmentPeriod string
    Optional. The lower bound on data point frequency for this data set, implemented by specifying the minimum alignment period to use in a time series query. For example, if the data is published once every 10 minutes, the min_alignment_period should be at least 10 minutes. It would not make sense to fetch and align data at one minute intervals.
    SliceNameTemplate string
    Optional. A template for the name of the slice. This name will be displayed in the legend and the tooltip of the pie chart. It replaces the auto-generated names for the slices. For example, if the template is set to ${resource.labels.zone}, the zone's value will be used for the name instead of the default name.
    TimeSeriesQuery TimeSeriesQueryResponse
    The query for the PieChart. See, google.monitoring.dashboard.v1.TimeSeriesQuery.
    minAlignmentPeriod String
    Optional. The lower bound on data point frequency for this data set, implemented by specifying the minimum alignment period to use in a time series query. For example, if the data is published once every 10 minutes, the min_alignment_period should be at least 10 minutes. It would not make sense to fetch and align data at one minute intervals.
    sliceNameTemplate String
    Optional. A template for the name of the slice. This name will be displayed in the legend and the tooltip of the pie chart. It replaces the auto-generated names for the slices. For example, if the template is set to ${resource.labels.zone}, the zone's value will be used for the name instead of the default name.
    timeSeriesQuery TimeSeriesQueryResponse
    The query for the PieChart. See, google.monitoring.dashboard.v1.TimeSeriesQuery.
    minAlignmentPeriod string
    Optional. The lower bound on data point frequency for this data set, implemented by specifying the minimum alignment period to use in a time series query. For example, if the data is published once every 10 minutes, the min_alignment_period should be at least 10 minutes. It would not make sense to fetch and align data at one minute intervals.
    sliceNameTemplate string
    Optional. A template for the name of the slice. This name will be displayed in the legend and the tooltip of the pie chart. It replaces the auto-generated names for the slices. For example, if the template is set to ${resource.labels.zone}, the zone's value will be used for the name instead of the default name.
    timeSeriesQuery TimeSeriesQueryResponse
    The query for the PieChart. See, google.monitoring.dashboard.v1.TimeSeriesQuery.
    min_alignment_period str
    Optional. The lower bound on data point frequency for this data set, implemented by specifying the minimum alignment period to use in a time series query. For example, if the data is published once every 10 minutes, the min_alignment_period should be at least 10 minutes. It would not make sense to fetch and align data at one minute intervals.
    slice_name_template str
    Optional. A template for the name of the slice. This name will be displayed in the legend and the tooltip of the pie chart. It replaces the auto-generated names for the slices. For example, if the template is set to ${resource.labels.zone}, the zone's value will be used for the name instead of the default name.
    time_series_query TimeSeriesQueryResponse
    The query for the PieChart. See, google.monitoring.dashboard.v1.TimeSeriesQuery.
    minAlignmentPeriod String
    Optional. The lower bound on data point frequency for this data set, implemented by specifying the minimum alignment period to use in a time series query. For example, if the data is published once every 10 minutes, the min_alignment_period should be at least 10 minutes. It would not make sense to fetch and align data at one minute intervals.
    sliceNameTemplate String
    Optional. A template for the name of the slice. This name will be displayed in the legend and the tooltip of the pie chart. It replaces the auto-generated names for the slices. For example, if the template is set to ${resource.labels.zone}, the zone's value will be used for the name instead of the default name.
    timeSeriesQuery Property Map
    The query for the PieChart. See, google.monitoring.dashboard.v1.TimeSeriesQuery.

    PieChartResponse, PieChartResponseArgs

    ChartType string
    Indicates the visualization type for the PieChart.
    DataSets List<Pulumi.GoogleNative.Monitoring.V1.Inputs.PieChartDataSetResponse>
    The queries for the chart's data.
    ShowLabels bool
    Optional. Indicates whether or not the pie chart should show slices' labels
    ChartType string
    Indicates the visualization type for the PieChart.
    DataSets []PieChartDataSetResponse
    The queries for the chart's data.
    ShowLabels bool
    Optional. Indicates whether or not the pie chart should show slices' labels
    chartType String
    Indicates the visualization type for the PieChart.
    dataSets List<PieChartDataSetResponse>
    The queries for the chart's data.
    showLabels Boolean
    Optional. Indicates whether or not the pie chart should show slices' labels
    chartType string
    Indicates the visualization type for the PieChart.
    dataSets PieChartDataSetResponse[]
    The queries for the chart's data.
    showLabels boolean
    Optional. Indicates whether or not the pie chart should show slices' labels
    chart_type str
    Indicates the visualization type for the PieChart.
    data_sets Sequence[PieChartDataSetResponse]
    The queries for the chart's data.
    show_labels bool
    Optional. Indicates whether or not the pie chart should show slices' labels
    chartType String
    Indicates the visualization type for the PieChart.
    dataSets List<Property Map>
    The queries for the chart's data.
    showLabels Boolean
    Optional. Indicates whether or not the pie chart should show slices' labels

    RatioPart, RatioPartArgs

    Filter string
    The monitoring filter (https://cloud.google.com/monitoring/api/v3/filters) that identifies the metric types, resources, and projects to query.
    Aggregation Pulumi.GoogleNative.Monitoring.V1.Inputs.Aggregation
    By default, the raw time series data is returned. Use this field to combine multiple time series for different views of the data.
    Filter string
    The monitoring filter (https://cloud.google.com/monitoring/api/v3/filters) that identifies the metric types, resources, and projects to query.
    Aggregation Aggregation
    By default, the raw time series data is returned. Use this field to combine multiple time series for different views of the data.
    filter String
    The monitoring filter (https://cloud.google.com/monitoring/api/v3/filters) that identifies the metric types, resources, and projects to query.
    aggregation Aggregation
    By default, the raw time series data is returned. Use this field to combine multiple time series for different views of the data.
    filter string
    The monitoring filter (https://cloud.google.com/monitoring/api/v3/filters) that identifies the metric types, resources, and projects to query.
    aggregation Aggregation
    By default, the raw time series data is returned. Use this field to combine multiple time series for different views of the data.
    filter str
    The monitoring filter (https://cloud.google.com/monitoring/api/v3/filters) that identifies the metric types, resources, and projects to query.
    aggregation Aggregation
    By default, the raw time series data is returned. Use this field to combine multiple time series for different views of the data.
    filter String
    The monitoring filter (https://cloud.google.com/monitoring/api/v3/filters) that identifies the metric types, resources, and projects to query.
    aggregation Property Map
    By default, the raw time series data is returned. Use this field to combine multiple time series for different views of the data.

    RatioPartResponse, RatioPartResponseArgs

    Aggregation Pulumi.GoogleNative.Monitoring.V1.Inputs.AggregationResponse
    By default, the raw time series data is returned. Use this field to combine multiple time series for different views of the data.
    Filter string
    The monitoring filter (https://cloud.google.com/monitoring/api/v3/filters) that identifies the metric types, resources, and projects to query.
    Aggregation AggregationResponse
    By default, the raw time series data is returned. Use this field to combine multiple time series for different views of the data.
    Filter string
    The monitoring filter (https://cloud.google.com/monitoring/api/v3/filters) that identifies the metric types, resources, and projects to query.
    aggregation AggregationResponse
    By default, the raw time series data is returned. Use this field to combine multiple time series for different views of the data.
    filter String
    The monitoring filter (https://cloud.google.com/monitoring/api/v3/filters) that identifies the metric types, resources, and projects to query.
    aggregation AggregationResponse
    By default, the raw time series data is returned. Use this field to combine multiple time series for different views of the data.
    filter string
    The monitoring filter (https://cloud.google.com/monitoring/api/v3/filters) that identifies the metric types, resources, and projects to query.
    aggregation AggregationResponse
    By default, the raw time series data is returned. Use this field to combine multiple time series for different views of the data.
    filter str
    The monitoring filter (https://cloud.google.com/monitoring/api/v3/filters) that identifies the metric types, resources, and projects to query.
    aggregation Property Map
    By default, the raw time series data is returned. Use this field to combine multiple time series for different views of the data.
    filter String
    The monitoring filter (https://cloud.google.com/monitoring/api/v3/filters) that identifies the metric types, resources, and projects to query.

    Row, RowArgs

    Weight string
    The relative weight of this row. The row weight is used to adjust the height of rows on the screen (relative to peers). Greater the weight, greater the height of the row on the screen. If omitted, a value of 1 is used while rendering.
    Widgets List<Pulumi.GoogleNative.Monitoring.V1.Inputs.Widget>
    The display widgets arranged horizontally in this row.
    Weight string
    The relative weight of this row. The row weight is used to adjust the height of rows on the screen (relative to peers). Greater the weight, greater the height of the row on the screen. If omitted, a value of 1 is used while rendering.
    Widgets []Widget
    The display widgets arranged horizontally in this row.
    weight String
    The relative weight of this row. The row weight is used to adjust the height of rows on the screen (relative to peers). Greater the weight, greater the height of the row on the screen. If omitted, a value of 1 is used while rendering.
    widgets List<Widget>
    The display widgets arranged horizontally in this row.
    weight string
    The relative weight of this row. The row weight is used to adjust the height of rows on the screen (relative to peers). Greater the weight, greater the height of the row on the screen. If omitted, a value of 1 is used while rendering.
    widgets Widget[]
    The display widgets arranged horizontally in this row.
    weight str
    The relative weight of this row. The row weight is used to adjust the height of rows on the screen (relative to peers). Greater the weight, greater the height of the row on the screen. If omitted, a value of 1 is used while rendering.
    widgets Sequence[Widget]
    The display widgets arranged horizontally in this row.
    weight String
    The relative weight of this row. The row weight is used to adjust the height of rows on the screen (relative to peers). Greater the weight, greater the height of the row on the screen. If omitted, a value of 1 is used while rendering.
    widgets List<Property Map>
    The display widgets arranged horizontally in this row.

    RowLayout, RowLayoutArgs

    Rows []Row
    The rows of content to display.
    rows List<Row>
    The rows of content to display.
    rows Row[]
    The rows of content to display.
    rows Sequence[Row]
    The rows of content to display.
    rows List<Property Map>
    The rows of content to display.

    RowLayoutResponse, RowLayoutResponseArgs

    Rows []RowResponse
    The rows of content to display.
    rows List<RowResponse>
    The rows of content to display.
    rows RowResponse[]
    The rows of content to display.
    rows Sequence[RowResponse]
    The rows of content to display.
    rows List<Property Map>
    The rows of content to display.

    RowResponse, RowResponseArgs

    Weight string
    The relative weight of this row. The row weight is used to adjust the height of rows on the screen (relative to peers). Greater the weight, greater the height of the row on the screen. If omitted, a value of 1 is used while rendering.
    Widgets List<Pulumi.GoogleNative.Monitoring.V1.Inputs.WidgetResponse>
    The display widgets arranged horizontally in this row.
    Weight string
    The relative weight of this row. The row weight is used to adjust the height of rows on the screen (relative to peers). Greater the weight, greater the height of the row on the screen. If omitted, a value of 1 is used while rendering.
    Widgets []WidgetResponse
    The display widgets arranged horizontally in this row.
    weight String
    The relative weight of this row. The row weight is used to adjust the height of rows on the screen (relative to peers). Greater the weight, greater the height of the row on the screen. If omitted, a value of 1 is used while rendering.
    widgets List<WidgetResponse>
    The display widgets arranged horizontally in this row.
    weight string
    The relative weight of this row. The row weight is used to adjust the height of rows on the screen (relative to peers). Greater the weight, greater the height of the row on the screen. If omitted, a value of 1 is used while rendering.
    widgets WidgetResponse[]
    The display widgets arranged horizontally in this row.
    weight str
    The relative weight of this row. The row weight is used to adjust the height of rows on the screen (relative to peers). Greater the weight, greater the height of the row on the screen. If omitted, a value of 1 is used while rendering.
    widgets Sequence[WidgetResponse]
    The display widgets arranged horizontally in this row.
    weight String
    The relative weight of this row. The row weight is used to adjust the height of rows on the screen (relative to peers). Greater the weight, greater the height of the row on the screen. If omitted, a value of 1 is used while rendering.
    widgets List<Property Map>
    The display widgets arranged horizontally in this row.

    Scorecard, ScorecardArgs

    TimeSeriesQuery Pulumi.GoogleNative.Monitoring.V1.Inputs.TimeSeriesQuery
    Fields for querying time series data from the Stackdriver metrics API.
    BlankView Pulumi.GoogleNative.Monitoring.V1.Inputs.Empty
    Will cause the Scorecard to show only the value, with no indicator to its value relative to its thresholds.
    GaugeView Pulumi.GoogleNative.Monitoring.V1.Inputs.GaugeView
    Will cause the scorecard to show a gauge chart.
    SparkChartView Pulumi.GoogleNative.Monitoring.V1.Inputs.SparkChartView
    Will cause the scorecard to show a spark chart.
    Thresholds List<Pulumi.GoogleNative.Monitoring.V1.Inputs.Threshold>
    The thresholds used to determine the state of the scorecard given the time series' current value. For an actual value x, the scorecard is in a danger state if x is less than or equal to a danger threshold that triggers below, or greater than or equal to a danger threshold that triggers above. Similarly, if x is above/below a warning threshold that triggers above/below, then the scorecard is in a warning state - unless x also puts it in a danger state. (Danger trumps warning.)As an example, consider a scorecard with the following four thresholds: { value: 90, category: 'DANGER', trigger: 'ABOVE', }, { value: 70, category: 'WARNING', trigger: 'ABOVE', }, { value: 10, category: 'DANGER', trigger: 'BELOW', }, { value: 20, category: 'WARNING', trigger: 'BELOW', } Then: values less than or equal to 10 would put the scorecard in a DANGER state, values greater than 10 but less than or equal to 20 a WARNING state, values strictly between 20 and 70 an OK state, values greater than or equal to 70 but less than 90 a WARNING state, and values greater than or equal to 90 a DANGER state.
    TimeSeriesQuery TimeSeriesQuery
    Fields for querying time series data from the Stackdriver metrics API.
    BlankView Empty
    Will cause the Scorecard to show only the value, with no indicator to its value relative to its thresholds.
    GaugeView GaugeView
    Will cause the scorecard to show a gauge chart.
    SparkChartView SparkChartView
    Will cause the scorecard to show a spark chart.
    Thresholds []Threshold
    The thresholds used to determine the state of the scorecard given the time series' current value. For an actual value x, the scorecard is in a danger state if x is less than or equal to a danger threshold that triggers below, or greater than or equal to a danger threshold that triggers above. Similarly, if x is above/below a warning threshold that triggers above/below, then the scorecard is in a warning state - unless x also puts it in a danger state. (Danger trumps warning.)As an example, consider a scorecard with the following four thresholds: { value: 90, category: 'DANGER', trigger: 'ABOVE', }, { value: 70, category: 'WARNING', trigger: 'ABOVE', }, { value: 10, category: 'DANGER', trigger: 'BELOW', }, { value: 20, category: 'WARNING', trigger: 'BELOW', } Then: values less than or equal to 10 would put the scorecard in a DANGER state, values greater than 10 but less than or equal to 20 a WARNING state, values strictly between 20 and 70 an OK state, values greater than or equal to 70 but less than 90 a WARNING state, and values greater than or equal to 90 a DANGER state.
    timeSeriesQuery TimeSeriesQuery
    Fields for querying time series data from the Stackdriver metrics API.
    blankView Empty
    Will cause the Scorecard to show only the value, with no indicator to its value relative to its thresholds.
    gaugeView GaugeView
    Will cause the scorecard to show a gauge chart.
    sparkChartView SparkChartView
    Will cause the scorecard to show a spark chart.
    thresholds List<Threshold>
    The thresholds used to determine the state of the scorecard given the time series' current value. For an actual value x, the scorecard is in a danger state if x is less than or equal to a danger threshold that triggers below, or greater than or equal to a danger threshold that triggers above. Similarly, if x is above/below a warning threshold that triggers above/below, then the scorecard is in a warning state - unless x also puts it in a danger state. (Danger trumps warning.)As an example, consider a scorecard with the following four thresholds: { value: 90, category: 'DANGER', trigger: 'ABOVE', }, { value: 70, category: 'WARNING', trigger: 'ABOVE', }, { value: 10, category: 'DANGER', trigger: 'BELOW', }, { value: 20, category: 'WARNING', trigger: 'BELOW', } Then: values less than or equal to 10 would put the scorecard in a DANGER state, values greater than 10 but less than or equal to 20 a WARNING state, values strictly between 20 and 70 an OK state, values greater than or equal to 70 but less than 90 a WARNING state, and values greater than or equal to 90 a DANGER state.
    timeSeriesQuery TimeSeriesQuery
    Fields for querying time series data from the Stackdriver metrics API.
    blankView Empty
    Will cause the Scorecard to show only the value, with no indicator to its value relative to its thresholds.
    gaugeView GaugeView
    Will cause the scorecard to show a gauge chart.
    sparkChartView SparkChartView
    Will cause the scorecard to show a spark chart.
    thresholds Threshold[]
    The thresholds used to determine the state of the scorecard given the time series' current value. For an actual value x, the scorecard is in a danger state if x is less than or equal to a danger threshold that triggers below, or greater than or equal to a danger threshold that triggers above. Similarly, if x is above/below a warning threshold that triggers above/below, then the scorecard is in a warning state - unless x also puts it in a danger state. (Danger trumps warning.)As an example, consider a scorecard with the following four thresholds: { value: 90, category: 'DANGER', trigger: 'ABOVE', }, { value: 70, category: 'WARNING', trigger: 'ABOVE', }, { value: 10, category: 'DANGER', trigger: 'BELOW', }, { value: 20, category: 'WARNING', trigger: 'BELOW', } Then: values less than or equal to 10 would put the scorecard in a DANGER state, values greater than 10 but less than or equal to 20 a WARNING state, values strictly between 20 and 70 an OK state, values greater than or equal to 70 but less than 90 a WARNING state, and values greater than or equal to 90 a DANGER state.
    time_series_query TimeSeriesQuery
    Fields for querying time series data from the Stackdriver metrics API.
    blank_view Empty
    Will cause the Scorecard to show only the value, with no indicator to its value relative to its thresholds.
    gauge_view GaugeView
    Will cause the scorecard to show a gauge chart.
    spark_chart_view SparkChartView
    Will cause the scorecard to show a spark chart.
    thresholds Sequence[Threshold]
    The thresholds used to determine the state of the scorecard given the time series' current value. For an actual value x, the scorecard is in a danger state if x is less than or equal to a danger threshold that triggers below, or greater than or equal to a danger threshold that triggers above. Similarly, if x is above/below a warning threshold that triggers above/below, then the scorecard is in a warning state - unless x also puts it in a danger state. (Danger trumps warning.)As an example, consider a scorecard with the following four thresholds: { value: 90, category: 'DANGER', trigger: 'ABOVE', }, { value: 70, category: 'WARNING', trigger: 'ABOVE', }, { value: 10, category: 'DANGER', trigger: 'BELOW', }, { value: 20, category: 'WARNING', trigger: 'BELOW', } Then: values less than or equal to 10 would put the scorecard in a DANGER state, values greater than 10 but less than or equal to 20 a WARNING state, values strictly between 20 and 70 an OK state, values greater than or equal to 70 but less than 90 a WARNING state, and values greater than or equal to 90 a DANGER state.
    timeSeriesQuery Property Map
    Fields for querying time series data from the Stackdriver metrics API.
    blankView Property Map
    Will cause the Scorecard to show only the value, with no indicator to its value relative to its thresholds.
    gaugeView Property Map
    Will cause the scorecard to show a gauge chart.
    sparkChartView Property Map
    Will cause the scorecard to show a spark chart.
    thresholds List<Property Map>
    The thresholds used to determine the state of the scorecard given the time series' current value. For an actual value x, the scorecard is in a danger state if x is less than or equal to a danger threshold that triggers below, or greater than or equal to a danger threshold that triggers above. Similarly, if x is above/below a warning threshold that triggers above/below, then the scorecard is in a warning state - unless x also puts it in a danger state. (Danger trumps warning.)As an example, consider a scorecard with the following four thresholds: { value: 90, category: 'DANGER', trigger: 'ABOVE', }, { value: 70, category: 'WARNING', trigger: 'ABOVE', }, { value: 10, category: 'DANGER', trigger: 'BELOW', }, { value: 20, category: 'WARNING', trigger: 'BELOW', } Then: values less than or equal to 10 would put the scorecard in a DANGER state, values greater than 10 but less than or equal to 20 a WARNING state, values strictly between 20 and 70 an OK state, values greater than or equal to 70 but less than 90 a WARNING state, and values greater than or equal to 90 a DANGER state.

    ScorecardResponse, ScorecardResponseArgs

    BlankView Pulumi.GoogleNative.Monitoring.V1.Inputs.EmptyResponse
    Will cause the Scorecard to show only the value, with no indicator to its value relative to its thresholds.
    GaugeView Pulumi.GoogleNative.Monitoring.V1.Inputs.GaugeViewResponse
    Will cause the scorecard to show a gauge chart.
    SparkChartView Pulumi.GoogleNative.Monitoring.V1.Inputs.SparkChartViewResponse
    Will cause the scorecard to show a spark chart.
    Thresholds List<Pulumi.GoogleNative.Monitoring.V1.Inputs.ThresholdResponse>
    The thresholds used to determine the state of the scorecard given the time series' current value. For an actual value x, the scorecard is in a danger state if x is less than or equal to a danger threshold that triggers below, or greater than or equal to a danger threshold that triggers above. Similarly, if x is above/below a warning threshold that triggers above/below, then the scorecard is in a warning state - unless x also puts it in a danger state. (Danger trumps warning.)As an example, consider a scorecard with the following four thresholds: { value: 90, category: 'DANGER', trigger: 'ABOVE', }, { value: 70, category: 'WARNING', trigger: 'ABOVE', }, { value: 10, category: 'DANGER', trigger: 'BELOW', }, { value: 20, category: 'WARNING', trigger: 'BELOW', } Then: values less than or equal to 10 would put the scorecard in a DANGER state, values greater than 10 but less than or equal to 20 a WARNING state, values strictly between 20 and 70 an OK state, values greater than or equal to 70 but less than 90 a WARNING state, and values greater than or equal to 90 a DANGER state.
    TimeSeriesQuery Pulumi.GoogleNative.Monitoring.V1.Inputs.TimeSeriesQueryResponse
    Fields for querying time series data from the Stackdriver metrics API.
    BlankView EmptyResponse
    Will cause the Scorecard to show only the value, with no indicator to its value relative to its thresholds.
    GaugeView GaugeViewResponse
    Will cause the scorecard to show a gauge chart.
    SparkChartView SparkChartViewResponse
    Will cause the scorecard to show a spark chart.
    Thresholds []ThresholdResponse
    The thresholds used to determine the state of the scorecard given the time series' current value. For an actual value x, the scorecard is in a danger state if x is less than or equal to a danger threshold that triggers below, or greater than or equal to a danger threshold that triggers above. Similarly, if x is above/below a warning threshold that triggers above/below, then the scorecard is in a warning state - unless x also puts it in a danger state. (Danger trumps warning.)As an example, consider a scorecard with the following four thresholds: { value: 90, category: 'DANGER', trigger: 'ABOVE', }, { value: 70, category: 'WARNING', trigger: 'ABOVE', }, { value: 10, category: 'DANGER', trigger: 'BELOW', }, { value: 20, category: 'WARNING', trigger: 'BELOW', } Then: values less than or equal to 10 would put the scorecard in a DANGER state, values greater than 10 but less than or equal to 20 a WARNING state, values strictly between 20 and 70 an OK state, values greater than or equal to 70 but less than 90 a WARNING state, and values greater than or equal to 90 a DANGER state.
    TimeSeriesQuery TimeSeriesQueryResponse
    Fields for querying time series data from the Stackdriver metrics API.
    blankView EmptyResponse
    Will cause the Scorecard to show only the value, with no indicator to its value relative to its thresholds.
    gaugeView GaugeViewResponse
    Will cause the scorecard to show a gauge chart.
    sparkChartView SparkChartViewResponse
    Will cause the scorecard to show a spark chart.
    thresholds List<ThresholdResponse>
    The thresholds used to determine the state of the scorecard given the time series' current value. For an actual value x, the scorecard is in a danger state if x is less than or equal to a danger threshold that triggers below, or greater than or equal to a danger threshold that triggers above. Similarly, if x is above/below a warning threshold that triggers above/below, then the scorecard is in a warning state - unless x also puts it in a danger state. (Danger trumps warning.)As an example, consider a scorecard with the following four thresholds: { value: 90, category: 'DANGER', trigger: 'ABOVE', }, { value: 70, category: 'WARNING', trigger: 'ABOVE', }, { value: 10, category: 'DANGER', trigger: 'BELOW', }, { value: 20, category: 'WARNING', trigger: 'BELOW', } Then: values less than or equal to 10 would put the scorecard in a DANGER state, values greater than 10 but less than or equal to 20 a WARNING state, values strictly between 20 and 70 an OK state, values greater than or equal to 70 but less than 90 a WARNING state, and values greater than or equal to 90 a DANGER state.
    timeSeriesQuery TimeSeriesQueryResponse
    Fields for querying time series data from the Stackdriver metrics API.
    blankView EmptyResponse
    Will cause the Scorecard to show only the value, with no indicator to its value relative to its thresholds.
    gaugeView GaugeViewResponse
    Will cause the scorecard to show a gauge chart.
    sparkChartView SparkChartViewResponse
    Will cause the scorecard to show a spark chart.
    thresholds ThresholdResponse[]
    The thresholds used to determine the state of the scorecard given the time series' current value. For an actual value x, the scorecard is in a danger state if x is less than or equal to a danger threshold that triggers below, or greater than or equal to a danger threshold that triggers above. Similarly, if x is above/below a warning threshold that triggers above/below, then the scorecard is in a warning state - unless x also puts it in a danger state. (Danger trumps warning.)As an example, consider a scorecard with the following four thresholds: { value: 90, category: 'DANGER', trigger: 'ABOVE', }, { value: 70, category: 'WARNING', trigger: 'ABOVE', }, { value: 10, category: 'DANGER', trigger: 'BELOW', }, { value: 20, category: 'WARNING', trigger: 'BELOW', } Then: values less than or equal to 10 would put the scorecard in a DANGER state, values greater than 10 but less than or equal to 20 a WARNING state, values strictly between 20 and 70 an OK state, values greater than or equal to 70 but less than 90 a WARNING state, and values greater than or equal to 90 a DANGER state.
    timeSeriesQuery TimeSeriesQueryResponse
    Fields for querying time series data from the Stackdriver metrics API.
    blank_view EmptyResponse
    Will cause the Scorecard to show only the value, with no indicator to its value relative to its thresholds.
    gauge_view GaugeViewResponse
    Will cause the scorecard to show a gauge chart.
    spark_chart_view SparkChartViewResponse
    Will cause the scorecard to show a spark chart.
    thresholds Sequence[ThresholdResponse]
    The thresholds used to determine the state of the scorecard given the time series' current value. For an actual value x, the scorecard is in a danger state if x is less than or equal to a danger threshold that triggers below, or greater than or equal to a danger threshold that triggers above. Similarly, if x is above/below a warning threshold that triggers above/below, then the scorecard is in a warning state - unless x also puts it in a danger state. (Danger trumps warning.)As an example, consider a scorecard with the following four thresholds: { value: 90, category: 'DANGER', trigger: 'ABOVE', }, { value: 70, category: 'WARNING', trigger: 'ABOVE', }, { value: 10, category: 'DANGER', trigger: 'BELOW', }, { value: 20, category: 'WARNING', trigger: 'BELOW', } Then: values less than or equal to 10 would put the scorecard in a DANGER state, values greater than 10 but less than or equal to 20 a WARNING state, values strictly between 20 and 70 an OK state, values greater than or equal to 70 but less than 90 a WARNING state, and values greater than or equal to 90 a DANGER state.
    time_series_query TimeSeriesQueryResponse
    Fields for querying time series data from the Stackdriver metrics API.
    blankView Property Map
    Will cause the Scorecard to show only the value, with no indicator to its value relative to its thresholds.
    gaugeView Property Map
    Will cause the scorecard to show a gauge chart.
    sparkChartView Property Map
    Will cause the scorecard to show a spark chart.
    thresholds List<Property Map>
    The thresholds used to determine the state of the scorecard given the time series' current value. For an actual value x, the scorecard is in a danger state if x is less than or equal to a danger threshold that triggers below, or greater than or equal to a danger threshold that triggers above. Similarly, if x is above/below a warning threshold that triggers above/below, then the scorecard is in a warning state - unless x also puts it in a danger state. (Danger trumps warning.)As an example, consider a scorecard with the following four thresholds: { value: 90, category: 'DANGER', trigger: 'ABOVE', }, { value: 70, category: 'WARNING', trigger: 'ABOVE', }, { value: 10, category: 'DANGER', trigger: 'BELOW', }, { value: 20, category: 'WARNING', trigger: 'BELOW', } Then: values less than or equal to 10 would put the scorecard in a DANGER state, values greater than 10 but less than or equal to 20 a WARNING state, values strictly between 20 and 70 an OK state, values greater than or equal to 70 but less than 90 a WARNING state, and values greater than or equal to 90 a DANGER state.
    timeSeriesQuery Property Map
    Fields for querying time series data from the Stackdriver metrics API.

    SparkChartView, SparkChartViewArgs

    SparkChartType Pulumi.GoogleNative.Monitoring.V1.SparkChartViewSparkChartType
    The type of sparkchart to show in this chartView.
    MinAlignmentPeriod string
    The lower bound on data point frequency in the chart implemented by specifying the minimum alignment period to use in a time series query. For example, if the data is published once every 10 minutes it would not make sense to fetch and align data at one minute intervals. This field is optional and exists only as a hint.
    SparkChartType SparkChartViewSparkChartType
    The type of sparkchart to show in this chartView.
    MinAlignmentPeriod string
    The lower bound on data point frequency in the chart implemented by specifying the minimum alignment period to use in a time series query. For example, if the data is published once every 10 minutes it would not make sense to fetch and align data at one minute intervals. This field is optional and exists only as a hint.
    sparkChartType SparkChartViewSparkChartType
    The type of sparkchart to show in this chartView.
    minAlignmentPeriod String
    The lower bound on data point frequency in the chart implemented by specifying the minimum alignment period to use in a time series query. For example, if the data is published once every 10 minutes it would not make sense to fetch and align data at one minute intervals. This field is optional and exists only as a hint.
    sparkChartType SparkChartViewSparkChartType
    The type of sparkchart to show in this chartView.
    minAlignmentPeriod string
    The lower bound on data point frequency in the chart implemented by specifying the minimum alignment period to use in a time series query. For example, if the data is published once every 10 minutes it would not make sense to fetch and align data at one minute intervals. This field is optional and exists only as a hint.
    spark_chart_type SparkChartViewSparkChartType
    The type of sparkchart to show in this chartView.
    min_alignment_period str
    The lower bound on data point frequency in the chart implemented by specifying the minimum alignment period to use in a time series query. For example, if the data is published once every 10 minutes it would not make sense to fetch and align data at one minute intervals. This field is optional and exists only as a hint.
    sparkChartType "SPARK_CHART_TYPE_UNSPECIFIED" | "SPARK_LINE" | "SPARK_BAR"
    The type of sparkchart to show in this chartView.
    minAlignmentPeriod String
    The lower bound on data point frequency in the chart implemented by specifying the minimum alignment period to use in a time series query. For example, if the data is published once every 10 minutes it would not make sense to fetch and align data at one minute intervals. This field is optional and exists only as a hint.

    SparkChartViewResponse, SparkChartViewResponseArgs

    MinAlignmentPeriod string
    The lower bound on data point frequency in the chart implemented by specifying the minimum alignment period to use in a time series query. For example, if the data is published once every 10 minutes it would not make sense to fetch and align data at one minute intervals. This field is optional and exists only as a hint.
    SparkChartType string
    The type of sparkchart to show in this chartView.
    MinAlignmentPeriod string
    The lower bound on data point frequency in the chart implemented by specifying the minimum alignment period to use in a time series query. For example, if the data is published once every 10 minutes it would not make sense to fetch and align data at one minute intervals. This field is optional and exists only as a hint.
    SparkChartType string
    The type of sparkchart to show in this chartView.
    minAlignmentPeriod String
    The lower bound on data point frequency in the chart implemented by specifying the minimum alignment period to use in a time series query. For example, if the data is published once every 10 minutes it would not make sense to fetch and align data at one minute intervals. This field is optional and exists only as a hint.
    sparkChartType String
    The type of sparkchart to show in this chartView.
    minAlignmentPeriod string
    The lower bound on data point frequency in the chart implemented by specifying the minimum alignment period to use in a time series query. For example, if the data is published once every 10 minutes it would not make sense to fetch and align data at one minute intervals. This field is optional and exists only as a hint.
    sparkChartType string
    The type of sparkchart to show in this chartView.
    min_alignment_period str
    The lower bound on data point frequency in the chart implemented by specifying the minimum alignment period to use in a time series query. For example, if the data is published once every 10 minutes it would not make sense to fetch and align data at one minute intervals. This field is optional and exists only as a hint.
    spark_chart_type str
    The type of sparkchart to show in this chartView.
    minAlignmentPeriod String
    The lower bound on data point frequency in the chart implemented by specifying the minimum alignment period to use in a time series query. For example, if the data is published once every 10 minutes it would not make sense to fetch and align data at one minute intervals. This field is optional and exists only as a hint.
    sparkChartType String
    The type of sparkchart to show in this chartView.

    SparkChartViewSparkChartType, SparkChartViewSparkChartTypeArgs

    SparkChartTypeUnspecified
    SPARK_CHART_TYPE_UNSPECIFIEDNot allowed in well-formed requests.
    SparkLine
    SPARK_LINEThe sparkline will be rendered as a small line chart.
    SparkBar
    SPARK_BARThe sparkbar will be rendered as a small bar chart.
    SparkChartViewSparkChartTypeSparkChartTypeUnspecified
    SPARK_CHART_TYPE_UNSPECIFIEDNot allowed in well-formed requests.
    SparkChartViewSparkChartTypeSparkLine
    SPARK_LINEThe sparkline will be rendered as a small line chart.
    SparkChartViewSparkChartTypeSparkBar
    SPARK_BARThe sparkbar will be rendered as a small bar chart.
    SparkChartTypeUnspecified
    SPARK_CHART_TYPE_UNSPECIFIEDNot allowed in well-formed requests.
    SparkLine
    SPARK_LINEThe sparkline will be rendered as a small line chart.
    SparkBar
    SPARK_BARThe sparkbar will be rendered as a small bar chart.
    SparkChartTypeUnspecified
    SPARK_CHART_TYPE_UNSPECIFIEDNot allowed in well-formed requests.
    SparkLine
    SPARK_LINEThe sparkline will be rendered as a small line chart.
    SparkBar
    SPARK_BARThe sparkbar will be rendered as a small bar chart.
    SPARK_CHART_TYPE_UNSPECIFIED
    SPARK_CHART_TYPE_UNSPECIFIEDNot allowed in well-formed requests.
    SPARK_LINE
    SPARK_LINEThe sparkline will be rendered as a small line chart.
    SPARK_BAR
    SPARK_BARThe sparkbar will be rendered as a small bar chart.
    "SPARK_CHART_TYPE_UNSPECIFIED"
    SPARK_CHART_TYPE_UNSPECIFIEDNot allowed in well-formed requests.
    "SPARK_LINE"
    SPARK_LINEThe sparkline will be rendered as a small line chart.
    "SPARK_BAR"
    SPARK_BARThe sparkbar will be rendered as a small bar chart.

    StatisticalTimeSeriesFilter, StatisticalTimeSeriesFilterArgs

    NumTimeSeries int
    How many time series to output.
    RankingMethod Pulumi.GoogleNative.Monitoring.V1.StatisticalTimeSeriesFilterRankingMethod
    rankingMethod is applied to a set of time series, and then the produced value for each individual time series is used to compare a given time series to others. These are methods that cannot be applied stream-by-stream, but rather require the full context of a request to evaluate time series.
    NumTimeSeries int
    How many time series to output.
    RankingMethod StatisticalTimeSeriesFilterRankingMethod
    rankingMethod is applied to a set of time series, and then the produced value for each individual time series is used to compare a given time series to others. These are methods that cannot be applied stream-by-stream, but rather require the full context of a request to evaluate time series.
    numTimeSeries Integer
    How many time series to output.
    rankingMethod StatisticalTimeSeriesFilterRankingMethod
    rankingMethod is applied to a set of time series, and then the produced value for each individual time series is used to compare a given time series to others. These are methods that cannot be applied stream-by-stream, but rather require the full context of a request to evaluate time series.
    numTimeSeries number
    How many time series to output.
    rankingMethod StatisticalTimeSeriesFilterRankingMethod
    rankingMethod is applied to a set of time series, and then the produced value for each individual time series is used to compare a given time series to others. These are methods that cannot be applied stream-by-stream, but rather require the full context of a request to evaluate time series.
    num_time_series int
    How many time series to output.
    ranking_method StatisticalTimeSeriesFilterRankingMethod
    rankingMethod is applied to a set of time series, and then the produced value for each individual time series is used to compare a given time series to others. These are methods that cannot be applied stream-by-stream, but rather require the full context of a request to evaluate time series.
    numTimeSeries Number
    How many time series to output.
    rankingMethod "METHOD_UNSPECIFIED" | "METHOD_CLUSTER_OUTLIER"
    rankingMethod is applied to a set of time series, and then the produced value for each individual time series is used to compare a given time series to others. These are methods that cannot be applied stream-by-stream, but rather require the full context of a request to evaluate time series.

    StatisticalTimeSeriesFilterRankingMethod, StatisticalTimeSeriesFilterRankingMethodArgs

    MethodUnspecified
    METHOD_UNSPECIFIEDNot allowed in well-formed requests.
    MethodClusterOutlier
    METHOD_CLUSTER_OUTLIERCompute the outlier score of each stream.
    StatisticalTimeSeriesFilterRankingMethodMethodUnspecified
    METHOD_UNSPECIFIEDNot allowed in well-formed requests.
    StatisticalTimeSeriesFilterRankingMethodMethodClusterOutlier
    METHOD_CLUSTER_OUTLIERCompute the outlier score of each stream.
    MethodUnspecified
    METHOD_UNSPECIFIEDNot allowed in well-formed requests.
    MethodClusterOutlier
    METHOD_CLUSTER_OUTLIERCompute the outlier score of each stream.
    MethodUnspecified
    METHOD_UNSPECIFIEDNot allowed in well-formed requests.
    MethodClusterOutlier
    METHOD_CLUSTER_OUTLIERCompute the outlier score of each stream.
    METHOD_UNSPECIFIED
    METHOD_UNSPECIFIEDNot allowed in well-formed requests.
    METHOD_CLUSTER_OUTLIER
    METHOD_CLUSTER_OUTLIERCompute the outlier score of each stream.
    "METHOD_UNSPECIFIED"
    METHOD_UNSPECIFIEDNot allowed in well-formed requests.
    "METHOD_CLUSTER_OUTLIER"
    METHOD_CLUSTER_OUTLIERCompute the outlier score of each stream.

    StatisticalTimeSeriesFilterResponse, StatisticalTimeSeriesFilterResponseArgs

    NumTimeSeries int
    How many time series to output.
    RankingMethod string
    rankingMethod is applied to a set of time series, and then the produced value for each individual time series is used to compare a given time series to others. These are methods that cannot be applied stream-by-stream, but rather require the full context of a request to evaluate time series.
    NumTimeSeries int
    How many time series to output.
    RankingMethod string
    rankingMethod is applied to a set of time series, and then the produced value for each individual time series is used to compare a given time series to others. These are methods that cannot be applied stream-by-stream, but rather require the full context of a request to evaluate time series.
    numTimeSeries Integer
    How many time series to output.
    rankingMethod String
    rankingMethod is applied to a set of time series, and then the produced value for each individual time series is used to compare a given time series to others. These are methods that cannot be applied stream-by-stream, but rather require the full context of a request to evaluate time series.
    numTimeSeries number
    How many time series to output.
    rankingMethod string
    rankingMethod is applied to a set of time series, and then the produced value for each individual time series is used to compare a given time series to others. These are methods that cannot be applied stream-by-stream, but rather require the full context of a request to evaluate time series.
    num_time_series int
    How many time series to output.
    ranking_method str
    rankingMethod is applied to a set of time series, and then the produced value for each individual time series is used to compare a given time series to others. These are methods that cannot be applied stream-by-stream, but rather require the full context of a request to evaluate time series.
    numTimeSeries Number
    How many time series to output.
    rankingMethod String
    rankingMethod is applied to a set of time series, and then the produced value for each individual time series is used to compare a given time series to others. These are methods that cannot be applied stream-by-stream, but rather require the full context of a request to evaluate time series.

    TableDataSet, TableDataSetArgs

    TimeSeriesQuery Pulumi.GoogleNative.Monitoring.V1.Inputs.TimeSeriesQuery
    Fields for querying time series data from the Stackdriver metrics API.
    MinAlignmentPeriod string
    Optional. The lower bound on data point frequency for this data set, implemented by specifying the minimum alignment period to use in a time series query For example, if the data is published once every 10 minutes, the min_alignment_period should be at least 10 minutes. It would not make sense to fetch and align data at one minute intervals.
    TableDisplayOptions Pulumi.GoogleNative.Monitoring.V1.Inputs.TableDisplayOptions
    Optional. Table display options for configuring how the table is rendered.
    TableTemplate string
    Optional. A template string for naming TimeSeries in the resulting data set. This should be a string with interpolations of the form ${label_name}, which will resolve to the label's value i.e. "${resource.labels.project_id}."
    TimeSeriesQuery TimeSeriesQuery
    Fields for querying time series data from the Stackdriver metrics API.
    MinAlignmentPeriod string
    Optional. The lower bound on data point frequency for this data set, implemented by specifying the minimum alignment period to use in a time series query For example, if the data is published once every 10 minutes, the min_alignment_period should be at least 10 minutes. It would not make sense to fetch and align data at one minute intervals.
    TableDisplayOptions TableDisplayOptions
    Optional. Table display options for configuring how the table is rendered.
    TableTemplate string
    Optional. A template string for naming TimeSeries in the resulting data set. This should be a string with interpolations of the form ${label_name}, which will resolve to the label's value i.e. "${resource.labels.project_id}."
    timeSeriesQuery TimeSeriesQuery
    Fields for querying time series data from the Stackdriver metrics API.
    minAlignmentPeriod String
    Optional. The lower bound on data point frequency for this data set, implemented by specifying the minimum alignment period to use in a time series query For example, if the data is published once every 10 minutes, the min_alignment_period should be at least 10 minutes. It would not make sense to fetch and align data at one minute intervals.
    tableDisplayOptions TableDisplayOptions
    Optional. Table display options for configuring how the table is rendered.
    tableTemplate String
    Optional. A template string for naming TimeSeries in the resulting data set. This should be a string with interpolations of the form ${label_name}, which will resolve to the label's value i.e. "${resource.labels.project_id}."
    timeSeriesQuery TimeSeriesQuery
    Fields for querying time series data from the Stackdriver metrics API.
    minAlignmentPeriod string
    Optional. The lower bound on data point frequency for this data set, implemented by specifying the minimum alignment period to use in a time series query For example, if the data is published once every 10 minutes, the min_alignment_period should be at least 10 minutes. It would not make sense to fetch and align data at one minute intervals.
    tableDisplayOptions TableDisplayOptions
    Optional. Table display options for configuring how the table is rendered.
    tableTemplate string
    Optional. A template string for naming TimeSeries in the resulting data set. This should be a string with interpolations of the form ${label_name}, which will resolve to the label's value i.e. "${resource.labels.project_id}."
    time_series_query TimeSeriesQuery
    Fields for querying time series data from the Stackdriver metrics API.
    min_alignment_period str
    Optional. The lower bound on data point frequency for this data set, implemented by specifying the minimum alignment period to use in a time series query For example, if the data is published once every 10 minutes, the min_alignment_period should be at least 10 minutes. It would not make sense to fetch and align data at one minute intervals.
    table_display_options TableDisplayOptions
    Optional. Table display options for configuring how the table is rendered.
    table_template str
    Optional. A template string for naming TimeSeries in the resulting data set. This should be a string with interpolations of the form ${label_name}, which will resolve to the label's value i.e. "${resource.labels.project_id}."
    timeSeriesQuery Property Map
    Fields for querying time series data from the Stackdriver metrics API.
    minAlignmentPeriod String
    Optional. The lower bound on data point frequency for this data set, implemented by specifying the minimum alignment period to use in a time series query For example, if the data is published once every 10 minutes, the min_alignment_period should be at least 10 minutes. It would not make sense to fetch and align data at one minute intervals.
    tableDisplayOptions Property Map
    Optional. Table display options for configuring how the table is rendered.
    tableTemplate String
    Optional. A template string for naming TimeSeries in the resulting data set. This should be a string with interpolations of the form ${label_name}, which will resolve to the label's value i.e. "${resource.labels.project_id}."

    TableDataSetResponse, TableDataSetResponseArgs

    MinAlignmentPeriod string
    Optional. The lower bound on data point frequency for this data set, implemented by specifying the minimum alignment period to use in a time series query For example, if the data is published once every 10 minutes, the min_alignment_period should be at least 10 minutes. It would not make sense to fetch and align data at one minute intervals.
    TableDisplayOptions Pulumi.GoogleNative.Monitoring.V1.Inputs.TableDisplayOptionsResponse
    Optional. Table display options for configuring how the table is rendered.
    TableTemplate string
    Optional. A template string for naming TimeSeries in the resulting data set. This should be a string with interpolations of the form ${label_name}, which will resolve to the label's value i.e. "${resource.labels.project_id}."
    TimeSeriesQuery Pulumi.GoogleNative.Monitoring.V1.Inputs.TimeSeriesQueryResponse
    Fields for querying time series data from the Stackdriver metrics API.
    MinAlignmentPeriod string
    Optional. The lower bound on data point frequency for this data set, implemented by specifying the minimum alignment period to use in a time series query For example, if the data is published once every 10 minutes, the min_alignment_period should be at least 10 minutes. It would not make sense to fetch and align data at one minute intervals.
    TableDisplayOptions TableDisplayOptionsResponse
    Optional. Table display options for configuring how the table is rendered.
    TableTemplate string
    Optional. A template string for naming TimeSeries in the resulting data set. This should be a string with interpolations of the form ${label_name}, which will resolve to the label's value i.e. "${resource.labels.project_id}."
    TimeSeriesQuery TimeSeriesQueryResponse
    Fields for querying time series data from the Stackdriver metrics API.
    minAlignmentPeriod String
    Optional. The lower bound on data point frequency for this data set, implemented by specifying the minimum alignment period to use in a time series query For example, if the data is published once every 10 minutes, the min_alignment_period should be at least 10 minutes. It would not make sense to fetch and align data at one minute intervals.
    tableDisplayOptions TableDisplayOptionsResponse
    Optional. Table display options for configuring how the table is rendered.
    tableTemplate String
    Optional. A template string for naming TimeSeries in the resulting data set. This should be a string with interpolations of the form ${label_name}, which will resolve to the label's value i.e. "${resource.labels.project_id}."
    timeSeriesQuery TimeSeriesQueryResponse
    Fields for querying time series data from the Stackdriver metrics API.
    minAlignmentPeriod string
    Optional. The lower bound on data point frequency for this data set, implemented by specifying the minimum alignment period to use in a time series query For example, if the data is published once every 10 minutes, the min_alignment_period should be at least 10 minutes. It would not make sense to fetch and align data at one minute intervals.
    tableDisplayOptions TableDisplayOptionsResponse
    Optional. Table display options for configuring how the table is rendered.
    tableTemplate string
    Optional. A template string for naming TimeSeries in the resulting data set. This should be a string with interpolations of the form ${label_name}, which will resolve to the label's value i.e. "${resource.labels.project_id}."
    timeSeriesQuery TimeSeriesQueryResponse
    Fields for querying time series data from the Stackdriver metrics API.
    min_alignment_period str
    Optional. The lower bound on data point frequency for this data set, implemented by specifying the minimum alignment period to use in a time series query For example, if the data is published once every 10 minutes, the min_alignment_period should be at least 10 minutes. It would not make sense to fetch and align data at one minute intervals.
    table_display_options TableDisplayOptionsResponse
    Optional. Table display options for configuring how the table is rendered.
    table_template str
    Optional. A template string for naming TimeSeries in the resulting data set. This should be a string with interpolations of the form ${label_name}, which will resolve to the label's value i.e. "${resource.labels.project_id}."
    time_series_query TimeSeriesQueryResponse
    Fields for querying time series data from the Stackdriver metrics API.
    minAlignmentPeriod String
    Optional. The lower bound on data point frequency for this data set, implemented by specifying the minimum alignment period to use in a time series query For example, if the data is published once every 10 minutes, the min_alignment_period should be at least 10 minutes. It would not make sense to fetch and align data at one minute intervals.
    tableDisplayOptions Property Map
    Optional. Table display options for configuring how the table is rendered.
    tableTemplate String
    Optional. A template string for naming TimeSeries in the resulting data set. This should be a string with interpolations of the form ${label_name}, which will resolve to the label's value i.e. "${resource.labels.project_id}."
    timeSeriesQuery Property Map
    Fields for querying time series data from the Stackdriver metrics API.

    TableDisplayOptions, TableDisplayOptionsArgs

    ShownColumns List<string>
    Optional. This field is unused and has been replaced by TimeSeriesTable.column_settings
    ShownColumns []string
    Optional. This field is unused and has been replaced by TimeSeriesTable.column_settings
    shownColumns List<String>
    Optional. This field is unused and has been replaced by TimeSeriesTable.column_settings
    shownColumns string[]
    Optional. This field is unused and has been replaced by TimeSeriesTable.column_settings
    shown_columns Sequence[str]
    Optional. This field is unused and has been replaced by TimeSeriesTable.column_settings
    shownColumns List<String>
    Optional. This field is unused and has been replaced by TimeSeriesTable.column_settings

    TableDisplayOptionsResponse, TableDisplayOptionsResponseArgs

    ShownColumns List<string>
    Optional. This field is unused and has been replaced by TimeSeriesTable.column_settings
    ShownColumns []string
    Optional. This field is unused and has been replaced by TimeSeriesTable.column_settings
    shownColumns List<String>
    Optional. This field is unused and has been replaced by TimeSeriesTable.column_settings
    shownColumns string[]
    Optional. This field is unused and has been replaced by TimeSeriesTable.column_settings
    shown_columns Sequence[str]
    Optional. This field is unused and has been replaced by TimeSeriesTable.column_settings
    shownColumns List<String>
    Optional. This field is unused and has been replaced by TimeSeriesTable.column_settings

    Text, TextArgs

    Content string
    The text content to be displayed.
    Format Pulumi.GoogleNative.Monitoring.V1.TextFormat
    How the text content is formatted.
    Style Pulumi.GoogleNative.Monitoring.V1.Inputs.TextStyle
    How the text is styled
    Content string
    The text content to be displayed.
    Format TextFormat
    How the text content is formatted.
    Style TextStyle
    How the text is styled
    content String
    The text content to be displayed.
    format TextFormat
    How the text content is formatted.
    style TextStyle
    How the text is styled
    content string
    The text content to be displayed.
    format TextFormat
    How the text content is formatted.
    style TextStyle
    How the text is styled
    content str
    The text content to be displayed.
    format TextFormat
    How the text content is formatted.
    style TextStyle
    How the text is styled
    content String
    The text content to be displayed.
    format "FORMAT_UNSPECIFIED" | "MARKDOWN" | "RAW"
    How the text content is formatted.
    style Property Map
    How the text is styled

    TextFormat, TextFormatArgs

    FormatUnspecified
    FORMAT_UNSPECIFIEDFormat is unspecified. Defaults to MARKDOWN.
    Markdown
    MARKDOWNThe text contains Markdown formatting.
    Raw
    RAWThe text contains no special formatting.
    TextFormatFormatUnspecified
    FORMAT_UNSPECIFIEDFormat is unspecified. Defaults to MARKDOWN.
    TextFormatMarkdown
    MARKDOWNThe text contains Markdown formatting.
    TextFormatRaw
    RAWThe text contains no special formatting.
    FormatUnspecified
    FORMAT_UNSPECIFIEDFormat is unspecified. Defaults to MARKDOWN.
    Markdown
    MARKDOWNThe text contains Markdown formatting.
    Raw
    RAWThe text contains no special formatting.
    FormatUnspecified
    FORMAT_UNSPECIFIEDFormat is unspecified. Defaults to MARKDOWN.
    Markdown
    MARKDOWNThe text contains Markdown formatting.
    Raw
    RAWThe text contains no special formatting.
    FORMAT_UNSPECIFIED
    FORMAT_UNSPECIFIEDFormat is unspecified. Defaults to MARKDOWN.
    MARKDOWN
    MARKDOWNThe text contains Markdown formatting.
    RAW
    RAWThe text contains no special formatting.
    "FORMAT_UNSPECIFIED"
    FORMAT_UNSPECIFIEDFormat is unspecified. Defaults to MARKDOWN.
    "MARKDOWN"
    MARKDOWNThe text contains Markdown formatting.
    "RAW"
    RAWThe text contains no special formatting.

    TextResponse, TextResponseArgs

    Content string
    The text content to be displayed.
    Format string
    How the text content is formatted.
    Style Pulumi.GoogleNative.Monitoring.V1.Inputs.TextStyleResponse
    How the text is styled
    Content string
    The text content to be displayed.
    Format string
    How the text content is formatted.
    Style TextStyleResponse
    How the text is styled
    content String
    The text content to be displayed.
    format String
    How the text content is formatted.
    style TextStyleResponse
    How the text is styled
    content string
    The text content to be displayed.
    format string
    How the text content is formatted.
    style TextStyleResponse
    How the text is styled
    content str
    The text content to be displayed.
    format str
    How the text content is formatted.
    style TextStyleResponse
    How the text is styled
    content String
    The text content to be displayed.
    format String
    How the text content is formatted.
    style Property Map
    How the text is styled

    TextStyle, TextStyleArgs

    BackgroundColor string
    The background color as a hex string. "#RRGGBB" or "#RGB"
    FontSize Pulumi.GoogleNative.Monitoring.V1.TextStyleFontSize
    Font sizes for both the title and content. The title will still be larger relative to the content.
    HorizontalAlignment Pulumi.GoogleNative.Monitoring.V1.TextStyleHorizontalAlignment
    The horizontal alignment of both the title and content
    Padding Pulumi.GoogleNative.Monitoring.V1.TextStylePadding
    The amount of padding around the widget
    PointerLocation Pulumi.GoogleNative.Monitoring.V1.TextStylePointerLocation
    The pointer location for this widget (also sometimes called a "tail")
    TextColor string
    The text color as a hex string. "#RRGGBB" or "#RGB"
    VerticalAlignment Pulumi.GoogleNative.Monitoring.V1.TextStyleVerticalAlignment
    The vertical alignment of both the title and content
    BackgroundColor string
    The background color as a hex string. "#RRGGBB" or "#RGB"
    FontSize TextStyleFontSize
    Font sizes for both the title and content. The title will still be larger relative to the content.
    HorizontalAlignment TextStyleHorizontalAlignment
    The horizontal alignment of both the title and content
    Padding TextStylePadding
    The amount of padding around the widget
    PointerLocation TextStylePointerLocation
    The pointer location for this widget (also sometimes called a "tail")
    TextColor string
    The text color as a hex string. "#RRGGBB" or "#RGB"
    VerticalAlignment TextStyleVerticalAlignment
    The vertical alignment of both the title and content
    backgroundColor String
    The background color as a hex string. "#RRGGBB" or "#RGB"
    fontSize TextStyleFontSize
    Font sizes for both the title and content. The title will still be larger relative to the content.
    horizontalAlignment TextStyleHorizontalAlignment
    The horizontal alignment of both the title and content
    padding TextStylePadding
    The amount of padding around the widget
    pointerLocation TextStylePointerLocation
    The pointer location for this widget (also sometimes called a "tail")
    textColor String
    The text color as a hex string. "#RRGGBB" or "#RGB"
    verticalAlignment TextStyleVerticalAlignment
    The vertical alignment of both the title and content
    backgroundColor string
    The background color as a hex string. "#RRGGBB" or "#RGB"
    fontSize TextStyleFontSize
    Font sizes for both the title and content. The title will still be larger relative to the content.
    horizontalAlignment TextStyleHorizontalAlignment
    The horizontal alignment of both the title and content
    padding TextStylePadding
    The amount of padding around the widget
    pointerLocation TextStylePointerLocation
    The pointer location for this widget (also sometimes called a "tail")
    textColor string
    The text color as a hex string. "#RRGGBB" or "#RGB"
    verticalAlignment TextStyleVerticalAlignment
    The vertical alignment of both the title and content
    background_color str
    The background color as a hex string. "#RRGGBB" or "#RGB"
    font_size TextStyleFontSize
    Font sizes for both the title and content. The title will still be larger relative to the content.
    horizontal_alignment TextStyleHorizontalAlignment
    The horizontal alignment of both the title and content
    padding TextStylePadding
    The amount of padding around the widget
    pointer_location TextStylePointerLocation
    The pointer location for this widget (also sometimes called a "tail")
    text_color str
    The text color as a hex string. "#RRGGBB" or "#RGB"
    vertical_alignment TextStyleVerticalAlignment
    The vertical alignment of both the title and content
    backgroundColor String
    The background color as a hex string. "#RRGGBB" or "#RGB"
    fontSize "FONT_SIZE_UNSPECIFIED" | "FS_EXTRA_SMALL" | "FS_SMALL" | "FS_MEDIUM" | "FS_LARGE" | "FS_EXTRA_LARGE"
    Font sizes for both the title and content. The title will still be larger relative to the content.
    horizontalAlignment "HORIZONTAL_ALIGNMENT_UNSPECIFIED" | "H_LEFT" | "H_CENTER" | "H_RIGHT"
    The horizontal alignment of both the title and content
    padding "PADDING_SIZE_UNSPECIFIED" | "P_EXTRA_SMALL" | "P_SMALL" | "P_MEDIUM" | "P_LARGE" | "P_EXTRA_LARGE"
    The amount of padding around the widget
    pointerLocation "POINTER_LOCATION_UNSPECIFIED" | "PL_TOP" | "PL_RIGHT" | "PL_BOTTOM" | "PL_LEFT" | "PL_TOP_LEFT" | "PL_TOP_RIGHT" | "PL_RIGHT_TOP" | "PL_RIGHT_BOTTOM" | "PL_BOTTOM_RIGHT" | "PL_BOTTOM_LEFT" | "PL_LEFT_BOTTOM" | "PL_LEFT_TOP"
    The pointer location for this widget (also sometimes called a "tail")
    textColor String
    The text color as a hex string. "#RRGGBB" or "#RGB"
    verticalAlignment "VERTICAL_ALIGNMENT_UNSPECIFIED" | "V_TOP" | "V_CENTER" | "V_BOTTOM"
    The vertical alignment of both the title and content

    TextStyleFontSize, TextStyleFontSizeArgs

    FontSizeUnspecified
    FONT_SIZE_UNSPECIFIEDNo font size specified, will default to FS_LARGE
    FsExtraSmall
    FS_EXTRA_SMALLExtra small font size
    FsSmall
    FS_SMALLSmall font size
    FsMedium
    FS_MEDIUMMedium font size
    FsLarge
    FS_LARGELarge font size
    FsExtraLarge
    FS_EXTRA_LARGEExtra large font size
    TextStyleFontSizeFontSizeUnspecified
    FONT_SIZE_UNSPECIFIEDNo font size specified, will default to FS_LARGE
    TextStyleFontSizeFsExtraSmall
    FS_EXTRA_SMALLExtra small font size
    TextStyleFontSizeFsSmall
    FS_SMALLSmall font size
    TextStyleFontSizeFsMedium
    FS_MEDIUMMedium font size
    TextStyleFontSizeFsLarge
    FS_LARGELarge font size
    TextStyleFontSizeFsExtraLarge
    FS_EXTRA_LARGEExtra large font size
    FontSizeUnspecified
    FONT_SIZE_UNSPECIFIEDNo font size specified, will default to FS_LARGE
    FsExtraSmall
    FS_EXTRA_SMALLExtra small font size
    FsSmall
    FS_SMALLSmall font size
    FsMedium
    FS_MEDIUMMedium font size
    FsLarge
    FS_LARGELarge font size
    FsExtraLarge
    FS_EXTRA_LARGEExtra large font size
    FontSizeUnspecified
    FONT_SIZE_UNSPECIFIEDNo font size specified, will default to FS_LARGE
    FsExtraSmall
    FS_EXTRA_SMALLExtra small font size
    FsSmall
    FS_SMALLSmall font size
    FsMedium
    FS_MEDIUMMedium font size
    FsLarge
    FS_LARGELarge font size
    FsExtraLarge
    FS_EXTRA_LARGEExtra large font size
    FONT_SIZE_UNSPECIFIED
    FONT_SIZE_UNSPECIFIEDNo font size specified, will default to FS_LARGE
    FS_EXTRA_SMALL
    FS_EXTRA_SMALLExtra small font size
    FS_SMALL
    FS_SMALLSmall font size
    FS_MEDIUM
    FS_MEDIUMMedium font size
    FS_LARGE
    FS_LARGELarge font size
    FS_EXTRA_LARGE
    FS_EXTRA_LARGEExtra large font size
    "FONT_SIZE_UNSPECIFIED"
    FONT_SIZE_UNSPECIFIEDNo font size specified, will default to FS_LARGE
    "FS_EXTRA_SMALL"
    FS_EXTRA_SMALLExtra small font size
    "FS_SMALL"
    FS_SMALLSmall font size
    "FS_MEDIUM"
    FS_MEDIUMMedium font size
    "FS_LARGE"
    FS_LARGELarge font size
    "FS_EXTRA_LARGE"
    FS_EXTRA_LARGEExtra large font size

    TextStyleHorizontalAlignment, TextStyleHorizontalAlignmentArgs

    HorizontalAlignmentUnspecified
    HORIZONTAL_ALIGNMENT_UNSPECIFIEDNo horizontal alignment specified, will default to H_LEFT
    HLeft
    H_LEFTLeft-align
    HCenter
    H_CENTERCenter-align
    HRight
    H_RIGHTRight-align
    TextStyleHorizontalAlignmentHorizontalAlignmentUnspecified
    HORIZONTAL_ALIGNMENT_UNSPECIFIEDNo horizontal alignment specified, will default to H_LEFT
    TextStyleHorizontalAlignmentHLeft
    H_LEFTLeft-align
    TextStyleHorizontalAlignmentHCenter
    H_CENTERCenter-align
    TextStyleHorizontalAlignmentHRight
    H_RIGHTRight-align
    HorizontalAlignmentUnspecified
    HORIZONTAL_ALIGNMENT_UNSPECIFIEDNo horizontal alignment specified, will default to H_LEFT
    HLeft
    H_LEFTLeft-align
    HCenter
    H_CENTERCenter-align
    HRight
    H_RIGHTRight-align
    HorizontalAlignmentUnspecified
    HORIZONTAL_ALIGNMENT_UNSPECIFIEDNo horizontal alignment specified, will default to H_LEFT
    HLeft
    H_LEFTLeft-align
    HCenter
    H_CENTERCenter-align
    HRight
    H_RIGHTRight-align
    HORIZONTAL_ALIGNMENT_UNSPECIFIED
    HORIZONTAL_ALIGNMENT_UNSPECIFIEDNo horizontal alignment specified, will default to H_LEFT
    H_LEFT
    H_LEFTLeft-align
    H_CENTER
    H_CENTERCenter-align
    H_RIGHT
    H_RIGHTRight-align
    "HORIZONTAL_ALIGNMENT_UNSPECIFIED"
    HORIZONTAL_ALIGNMENT_UNSPECIFIEDNo horizontal alignment specified, will default to H_LEFT
    "H_LEFT"
    H_LEFTLeft-align
    "H_CENTER"
    H_CENTERCenter-align
    "H_RIGHT"
    H_RIGHTRight-align

    TextStylePadding, TextStylePaddingArgs

    PaddingSizeUnspecified
    PADDING_SIZE_UNSPECIFIEDNo padding size specified, will default to P_EXTRA_SMALL
    PExtraSmall
    P_EXTRA_SMALLExtra small padding
    PSmall
    P_SMALLSmall padding
    PMedium
    P_MEDIUMMedium padding
    PLarge
    P_LARGELarge padding
    PExtraLarge
    P_EXTRA_LARGEExtra large padding
    TextStylePaddingPaddingSizeUnspecified
    PADDING_SIZE_UNSPECIFIEDNo padding size specified, will default to P_EXTRA_SMALL
    TextStylePaddingPExtraSmall
    P_EXTRA_SMALLExtra small padding
    TextStylePaddingPSmall
    P_SMALLSmall padding
    TextStylePaddingPMedium
    P_MEDIUMMedium padding
    TextStylePaddingPLarge
    P_LARGELarge padding
    TextStylePaddingPExtraLarge
    P_EXTRA_LARGEExtra large padding
    PaddingSizeUnspecified
    PADDING_SIZE_UNSPECIFIEDNo padding size specified, will default to P_EXTRA_SMALL
    PExtraSmall
    P_EXTRA_SMALLExtra small padding
    PSmall
    P_SMALLSmall padding
    PMedium
    P_MEDIUMMedium padding
    PLarge
    P_LARGELarge padding
    PExtraLarge
    P_EXTRA_LARGEExtra large padding
    PaddingSizeUnspecified
    PADDING_SIZE_UNSPECIFIEDNo padding size specified, will default to P_EXTRA_SMALL
    PExtraSmall
    P_EXTRA_SMALLExtra small padding
    PSmall
    P_SMALLSmall padding
    PMedium
    P_MEDIUMMedium padding
    PLarge
    P_LARGELarge padding
    PExtraLarge
    P_EXTRA_LARGEExtra large padding
    PADDING_SIZE_UNSPECIFIED
    PADDING_SIZE_UNSPECIFIEDNo padding size specified, will default to P_EXTRA_SMALL
    P_EXTRA_SMALL
    P_EXTRA_SMALLExtra small padding
    P_SMALL
    P_SMALLSmall padding
    P_MEDIUM
    P_MEDIUMMedium padding
    P_LARGE
    P_LARGELarge padding
    P_EXTRA_LARGE
    P_EXTRA_LARGEExtra large padding
    "PADDING_SIZE_UNSPECIFIED"
    PADDING_SIZE_UNSPECIFIEDNo padding size specified, will default to P_EXTRA_SMALL
    "P_EXTRA_SMALL"
    P_EXTRA_SMALLExtra small padding
    "P_SMALL"
    P_SMALLSmall padding
    "P_MEDIUM"
    P_MEDIUMMedium padding
    "P_LARGE"
    P_LARGELarge padding
    "P_EXTRA_LARGE"
    P_EXTRA_LARGEExtra large padding

    TextStylePointerLocation, TextStylePointerLocationArgs

    PointerLocationUnspecified
    POINTER_LOCATION_UNSPECIFIEDNo visual pointer
    PlTop
    PL_TOPPlaced in the middle of the top of the widget
    PlRight
    PL_RIGHTPlaced in the middle of the right side of the widget
    PlBottom
    PL_BOTTOMPlaced in the middle of the bottom of the widget
    PlLeft
    PL_LEFTPlaced in the middle of the left side of the widget
    PlTopLeft
    PL_TOP_LEFTPlaced on the left side of the top of the widget
    PlTopRight
    PL_TOP_RIGHTPlaced on the right side of the top of the widget
    PlRightTop
    PL_RIGHT_TOPPlaced on the top of the right side of the widget
    PlRightBottom
    PL_RIGHT_BOTTOMPlaced on the bottom of the right side of the widget
    PlBottomRight
    PL_BOTTOM_RIGHTPlaced on the right side of the bottom of the widget
    PlBottomLeft
    PL_BOTTOM_LEFTPlaced on the left side of the bottom of the widget
    PlLeftBottom
    PL_LEFT_BOTTOMPlaced on the bottom of the left side of the widget
    PlLeftTop
    PL_LEFT_TOPPlaced on the top of the left side of the widget
    TextStylePointerLocationPointerLocationUnspecified
    POINTER_LOCATION_UNSPECIFIEDNo visual pointer
    TextStylePointerLocationPlTop
    PL_TOPPlaced in the middle of the top of the widget
    TextStylePointerLocationPlRight
    PL_RIGHTPlaced in the middle of the right side of the widget
    TextStylePointerLocationPlBottom
    PL_BOTTOMPlaced in the middle of the bottom of the widget
    TextStylePointerLocationPlLeft
    PL_LEFTPlaced in the middle of the left side of the widget
    TextStylePointerLocationPlTopLeft
    PL_TOP_LEFTPlaced on the left side of the top of the widget
    TextStylePointerLocationPlTopRight
    PL_TOP_RIGHTPlaced on the right side of the top of the widget
    TextStylePointerLocationPlRightTop
    PL_RIGHT_TOPPlaced on the top of the right side of the widget
    TextStylePointerLocationPlRightBottom
    PL_RIGHT_BOTTOMPlaced on the bottom of the right side of the widget
    TextStylePointerLocationPlBottomRight
    PL_BOTTOM_RIGHTPlaced on the right side of the bottom of the widget
    TextStylePointerLocationPlBottomLeft
    PL_BOTTOM_LEFTPlaced on the left side of the bottom of the widget
    TextStylePointerLocationPlLeftBottom
    PL_LEFT_BOTTOMPlaced on the bottom of the left side of the widget
    TextStylePointerLocationPlLeftTop
    PL_LEFT_TOPPlaced on the top of the left side of the widget
    PointerLocationUnspecified
    POINTER_LOCATION_UNSPECIFIEDNo visual pointer
    PlTop
    PL_TOPPlaced in the middle of the top of the widget
    PlRight
    PL_RIGHTPlaced in the middle of the right side of the widget
    PlBottom
    PL_BOTTOMPlaced in the middle of the bottom of the widget
    PlLeft
    PL_LEFTPlaced in the middle of the left side of the widget
    PlTopLeft
    PL_TOP_LEFTPlaced on the left side of the top of the widget
    PlTopRight
    PL_TOP_RIGHTPlaced on the right side of the top of the widget
    PlRightTop
    PL_RIGHT_TOPPlaced on the top of the right side of the widget
    PlRightBottom
    PL_RIGHT_BOTTOMPlaced on the bottom of the right side of the widget
    PlBottomRight
    PL_BOTTOM_RIGHTPlaced on the right side of the bottom of the widget
    PlBottomLeft
    PL_BOTTOM_LEFTPlaced on the left side of the bottom of the widget
    PlLeftBottom
    PL_LEFT_BOTTOMPlaced on the bottom of the left side of the widget
    PlLeftTop
    PL_LEFT_TOPPlaced on the top of the left side of the widget
    PointerLocationUnspecified
    POINTER_LOCATION_UNSPECIFIEDNo visual pointer
    PlTop
    PL_TOPPlaced in the middle of the top of the widget
    PlRight
    PL_RIGHTPlaced in the middle of the right side of the widget
    PlBottom
    PL_BOTTOMPlaced in the middle of the bottom of the widget
    PlLeft
    PL_LEFTPlaced in the middle of the left side of the widget
    PlTopLeft
    PL_TOP_LEFTPlaced on the left side of the top of the widget
    PlTopRight
    PL_TOP_RIGHTPlaced on the right side of the top of the widget
    PlRightTop
    PL_RIGHT_TOPPlaced on the top of the right side of the widget
    PlRightBottom
    PL_RIGHT_BOTTOMPlaced on the bottom of the right side of the widget
    PlBottomRight
    PL_BOTTOM_RIGHTPlaced on the right side of the bottom of the widget
    PlBottomLeft
    PL_BOTTOM_LEFTPlaced on the left side of the bottom of the widget
    PlLeftBottom
    PL_LEFT_BOTTOMPlaced on the bottom of the left side of the widget
    PlLeftTop
    PL_LEFT_TOPPlaced on the top of the left side of the widget
    POINTER_LOCATION_UNSPECIFIED
    POINTER_LOCATION_UNSPECIFIEDNo visual pointer
    PL_TOP
    PL_TOPPlaced in the middle of the top of the widget
    PL_RIGHT
    PL_RIGHTPlaced in the middle of the right side of the widget
    PL_BOTTOM
    PL_BOTTOMPlaced in the middle of the bottom of the widget
    PL_LEFT
    PL_LEFTPlaced in the middle of the left side of the widget
    PL_TOP_LEFT
    PL_TOP_LEFTPlaced on the left side of the top of the widget
    PL_TOP_RIGHT
    PL_TOP_RIGHTPlaced on the right side of the top of the widget
    PL_RIGHT_TOP
    PL_RIGHT_TOPPlaced on the top of the right side of the widget
    PL_RIGHT_BOTTOM
    PL_RIGHT_BOTTOMPlaced on the bottom of the right side of the widget
    PL_BOTTOM_RIGHT
    PL_BOTTOM_RIGHTPlaced on the right side of the bottom of the widget
    PL_BOTTOM_LEFT
    PL_BOTTOM_LEFTPlaced on the left side of the bottom of the widget
    PL_LEFT_BOTTOM
    PL_LEFT_BOTTOMPlaced on the bottom of the left side of the widget
    PL_LEFT_TOP
    PL_LEFT_TOPPlaced on the top of the left side of the widget
    "POINTER_LOCATION_UNSPECIFIED"
    POINTER_LOCATION_UNSPECIFIEDNo visual pointer
    "PL_TOP"
    PL_TOPPlaced in the middle of the top of the widget
    "PL_RIGHT"
    PL_RIGHTPlaced in the middle of the right side of the widget
    "PL_BOTTOM"
    PL_BOTTOMPlaced in the middle of the bottom of the widget
    "PL_LEFT"
    PL_LEFTPlaced in the middle of the left side of the widget
    "PL_TOP_LEFT"
    PL_TOP_LEFTPlaced on the left side of the top of the widget
    "PL_TOP_RIGHT"
    PL_TOP_RIGHTPlaced on the right side of the top of the widget
    "PL_RIGHT_TOP"
    PL_RIGHT_TOPPlaced on the top of the right side of the widget
    "PL_RIGHT_BOTTOM"
    PL_RIGHT_BOTTOMPlaced on the bottom of the right side of the widget
    "PL_BOTTOM_RIGHT"
    PL_BOTTOM_RIGHTPlaced on the right side of the bottom of the widget
    "PL_BOTTOM_LEFT"
    PL_BOTTOM_LEFTPlaced on the left side of the bottom of the widget
    "PL_LEFT_BOTTOM"
    PL_LEFT_BOTTOMPlaced on the bottom of the left side of the widget
    "PL_LEFT_TOP"
    PL_LEFT_TOPPlaced on the top of the left side of the widget

    TextStyleResponse, TextStyleResponseArgs

    BackgroundColor string
    The background color as a hex string. "#RRGGBB" or "#RGB"
    FontSize string
    Font sizes for both the title and content. The title will still be larger relative to the content.
    HorizontalAlignment string
    The horizontal alignment of both the title and content
    Padding string
    The amount of padding around the widget
    PointerLocation string
    The pointer location for this widget (also sometimes called a "tail")
    TextColor string
    The text color as a hex string. "#RRGGBB" or "#RGB"
    VerticalAlignment string
    The vertical alignment of both the title and content
    BackgroundColor string
    The background color as a hex string. "#RRGGBB" or "#RGB"
    FontSize string
    Font sizes for both the title and content. The title will still be larger relative to the content.
    HorizontalAlignment string
    The horizontal alignment of both the title and content
    Padding string
    The amount of padding around the widget
    PointerLocation string
    The pointer location for this widget (also sometimes called a "tail")
    TextColor string
    The text color as a hex string. "#RRGGBB" or "#RGB"
    VerticalAlignment string
    The vertical alignment of both the title and content
    backgroundColor String
    The background color as a hex string. "#RRGGBB" or "#RGB"
    fontSize String
    Font sizes for both the title and content. The title will still be larger relative to the content.
    horizontalAlignment String
    The horizontal alignment of both the title and content
    padding String
    The amount of padding around the widget
    pointerLocation String
    The pointer location for this widget (also sometimes called a "tail")
    textColor String
    The text color as a hex string. "#RRGGBB" or "#RGB"
    verticalAlignment String
    The vertical alignment of both the title and content
    backgroundColor string
    The background color as a hex string. "#RRGGBB" or "#RGB"
    fontSize string
    Font sizes for both the title and content. The title will still be larger relative to the content.
    horizontalAlignment string
    The horizontal alignment of both the title and content
    padding string
    The amount of padding around the widget
    pointerLocation string
    The pointer location for this widget (also sometimes called a "tail")
    textColor string
    The text color as a hex string. "#RRGGBB" or "#RGB"
    verticalAlignment string
    The vertical alignment of both the title and content
    background_color str
    The background color as a hex string. "#RRGGBB" or "#RGB"
    font_size str
    Font sizes for both the title and content. The title will still be larger relative to the content.
    horizontal_alignment str
    The horizontal alignment of both the title and content
    padding str
    The amount of padding around the widget
    pointer_location str
    The pointer location for this widget (also sometimes called a "tail")
    text_color str
    The text color as a hex string. "#RRGGBB" or "#RGB"
    vertical_alignment str
    The vertical alignment of both the title and content
    backgroundColor String
    The background color as a hex string. "#RRGGBB" or "#RGB"
    fontSize String
    Font sizes for both the title and content. The title will still be larger relative to the content.
    horizontalAlignment String
    The horizontal alignment of both the title and content
    padding String
    The amount of padding around the widget
    pointerLocation String
    The pointer location for this widget (also sometimes called a "tail")
    textColor String
    The text color as a hex string. "#RRGGBB" or "#RGB"
    verticalAlignment String
    The vertical alignment of both the title and content

    TextStyleVerticalAlignment, TextStyleVerticalAlignmentArgs

    VerticalAlignmentUnspecified
    VERTICAL_ALIGNMENT_UNSPECIFIEDNo vertical alignment specified, will default to V_TOP
    VTop
    V_TOPTop-align
    VCenter
    V_CENTERCenter-align
    VBottom
    V_BOTTOMBottom-align
    TextStyleVerticalAlignmentVerticalAlignmentUnspecified
    VERTICAL_ALIGNMENT_UNSPECIFIEDNo vertical alignment specified, will default to V_TOP
    TextStyleVerticalAlignmentVTop
    V_TOPTop-align
    TextStyleVerticalAlignmentVCenter
    V_CENTERCenter-align
    TextStyleVerticalAlignmentVBottom
    V_BOTTOMBottom-align
    VerticalAlignmentUnspecified
    VERTICAL_ALIGNMENT_UNSPECIFIEDNo vertical alignment specified, will default to V_TOP
    VTop
    V_TOPTop-align
    VCenter
    V_CENTERCenter-align
    VBottom
    V_BOTTOMBottom-align
    VerticalAlignmentUnspecified
    VERTICAL_ALIGNMENT_UNSPECIFIEDNo vertical alignment specified, will default to V_TOP
    VTop
    V_TOPTop-align
    VCenter
    V_CENTERCenter-align
    VBottom
    V_BOTTOMBottom-align
    VERTICAL_ALIGNMENT_UNSPECIFIED
    VERTICAL_ALIGNMENT_UNSPECIFIEDNo vertical alignment specified, will default to V_TOP
    V_TOP
    V_TOPTop-align
    V_CENTER
    V_CENTERCenter-align
    V_BOTTOM
    V_BOTTOMBottom-align
    "VERTICAL_ALIGNMENT_UNSPECIFIED"
    VERTICAL_ALIGNMENT_UNSPECIFIEDNo vertical alignment specified, will default to V_TOP
    "V_TOP"
    V_TOPTop-align
    "V_CENTER"
    V_CENTERCenter-align
    "V_BOTTOM"
    V_BOTTOMBottom-align

    Threshold, ThresholdArgs

    Color Pulumi.GoogleNative.Monitoring.V1.ThresholdColor
    The state color for this threshold. Color is not allowed in a XyChart.
    Direction Pulumi.GoogleNative.Monitoring.V1.ThresholdDirection
    The direction for the current threshold. Direction is not allowed in a XyChart.
    Label string
    A label for the threshold.
    TargetAxis Pulumi.GoogleNative.Monitoring.V1.ThresholdTargetAxis
    The target axis to use for plotting the threshold. Target axis is not allowed in a Scorecard.
    Value double
    The value of the threshold. The value should be defined in the native scale of the metric.
    Color ThresholdColor
    The state color for this threshold. Color is not allowed in a XyChart.
    Direction ThresholdDirection
    The direction for the current threshold. Direction is not allowed in a XyChart.
    Label string
    A label for the threshold.
    TargetAxis ThresholdTargetAxis
    The target axis to use for plotting the threshold. Target axis is not allowed in a Scorecard.
    Value float64
    The value of the threshold. The value should be defined in the native scale of the metric.
    color ThresholdColor
    The state color for this threshold. Color is not allowed in a XyChart.
    direction ThresholdDirection
    The direction for the current threshold. Direction is not allowed in a XyChart.
    label String
    A label for the threshold.
    targetAxis ThresholdTargetAxis
    The target axis to use for plotting the threshold. Target axis is not allowed in a Scorecard.
    value Double
    The value of the threshold. The value should be defined in the native scale of the metric.
    color ThresholdColor
    The state color for this threshold. Color is not allowed in a XyChart.
    direction ThresholdDirection
    The direction for the current threshold. Direction is not allowed in a XyChart.
    label string
    A label for the threshold.
    targetAxis ThresholdTargetAxis
    The target axis to use for plotting the threshold. Target axis is not allowed in a Scorecard.
    value number
    The value of the threshold. The value should be defined in the native scale of the metric.
    color ThresholdColor
    The state color for this threshold. Color is not allowed in a XyChart.
    direction ThresholdDirection
    The direction for the current threshold. Direction is not allowed in a XyChart.
    label str
    A label for the threshold.
    target_axis ThresholdTargetAxis
    The target axis to use for plotting the threshold. Target axis is not allowed in a Scorecard.
    value float
    The value of the threshold. The value should be defined in the native scale of the metric.
    color "COLOR_UNSPECIFIED" | "YELLOW" | "RED"
    The state color for this threshold. Color is not allowed in a XyChart.
    direction "DIRECTION_UNSPECIFIED" | "ABOVE" | "BELOW"
    The direction for the current threshold. Direction is not allowed in a XyChart.
    label String
    A label for the threshold.
    targetAxis "TARGET_AXIS_UNSPECIFIED" | "Y1" | "Y2"
    The target axis to use for plotting the threshold. Target axis is not allowed in a Scorecard.
    value Number
    The value of the threshold. The value should be defined in the native scale of the metric.

    ThresholdColor, ThresholdColorArgs

    ColorUnspecified
    COLOR_UNSPECIFIEDColor is unspecified. Not allowed in well-formed requests.
    Yellow
    YELLOWCrossing the threshold is "concerning" behavior.
    Red
    REDCrossing the threshold is "emergency" behavior.
    ThresholdColorColorUnspecified
    COLOR_UNSPECIFIEDColor is unspecified. Not allowed in well-formed requests.
    ThresholdColorYellow
    YELLOWCrossing the threshold is "concerning" behavior.
    ThresholdColorRed
    REDCrossing the threshold is "emergency" behavior.
    ColorUnspecified
    COLOR_UNSPECIFIEDColor is unspecified. Not allowed in well-formed requests.
    Yellow
    YELLOWCrossing the threshold is "concerning" behavior.
    Red
    REDCrossing the threshold is "emergency" behavior.
    ColorUnspecified
    COLOR_UNSPECIFIEDColor is unspecified. Not allowed in well-formed requests.
    Yellow
    YELLOWCrossing the threshold is "concerning" behavior.
    Red
    REDCrossing the threshold is "emergency" behavior.
    COLOR_UNSPECIFIED
    COLOR_UNSPECIFIEDColor is unspecified. Not allowed in well-formed requests.
    YELLOW
    YELLOWCrossing the threshold is "concerning" behavior.
    RED
    REDCrossing the threshold is "emergency" behavior.
    "COLOR_UNSPECIFIED"
    COLOR_UNSPECIFIEDColor is unspecified. Not allowed in well-formed requests.
    "YELLOW"
    YELLOWCrossing the threshold is "concerning" behavior.
    "RED"
    REDCrossing the threshold is "emergency" behavior.

    ThresholdDirection, ThresholdDirectionArgs

    DirectionUnspecified
    DIRECTION_UNSPECIFIEDNot allowed in well-formed requests.
    Above
    ABOVEThe threshold will be considered crossed if the actual value is above the threshold value.
    Below
    BELOWThe threshold will be considered crossed if the actual value is below the threshold value.
    ThresholdDirectionDirectionUnspecified
    DIRECTION_UNSPECIFIEDNot allowed in well-formed requests.
    ThresholdDirectionAbove
    ABOVEThe threshold will be considered crossed if the actual value is above the threshold value.
    ThresholdDirectionBelow
    BELOWThe threshold will be considered crossed if the actual value is below the threshold value.
    DirectionUnspecified
    DIRECTION_UNSPECIFIEDNot allowed in well-formed requests.
    Above
    ABOVEThe threshold will be considered crossed if the actual value is above the threshold value.
    Below
    BELOWThe threshold will be considered crossed if the actual value is below the threshold value.
    DirectionUnspecified
    DIRECTION_UNSPECIFIEDNot allowed in well-formed requests.
    Above
    ABOVEThe threshold will be considered crossed if the actual value is above the threshold value.
    Below
    BELOWThe threshold will be considered crossed if the actual value is below the threshold value.
    DIRECTION_UNSPECIFIED
    DIRECTION_UNSPECIFIEDNot allowed in well-formed requests.
    ABOVE
    ABOVEThe threshold will be considered crossed if the actual value is above the threshold value.
    BELOW
    BELOWThe threshold will be considered crossed if the actual value is below the threshold value.
    "DIRECTION_UNSPECIFIED"
    DIRECTION_UNSPECIFIEDNot allowed in well-formed requests.
    "ABOVE"
    ABOVEThe threshold will be considered crossed if the actual value is above the threshold value.
    "BELOW"
    BELOWThe threshold will be considered crossed if the actual value is below the threshold value.

    ThresholdResponse, ThresholdResponseArgs

    Color string
    The state color for this threshold. Color is not allowed in a XyChart.
    Direction string
    The direction for the current threshold. Direction is not allowed in a XyChart.
    Label string
    A label for the threshold.
    TargetAxis string
    The target axis to use for plotting the threshold. Target axis is not allowed in a Scorecard.
    Value double
    The value of the threshold. The value should be defined in the native scale of the metric.
    Color string
    The state color for this threshold. Color is not allowed in a XyChart.
    Direction string
    The direction for the current threshold. Direction is not allowed in a XyChart.
    Label string
    A label for the threshold.
    TargetAxis string
    The target axis to use for plotting the threshold. Target axis is not allowed in a Scorecard.
    Value float64
    The value of the threshold. The value should be defined in the native scale of the metric.
    color String
    The state color for this threshold. Color is not allowed in a XyChart.
    direction String
    The direction for the current threshold. Direction is not allowed in a XyChart.
    label String
    A label for the threshold.
    targetAxis String
    The target axis to use for plotting the threshold. Target axis is not allowed in a Scorecard.
    value Double
    The value of the threshold. The value should be defined in the native scale of the metric.
    color string
    The state color for this threshold. Color is not allowed in a XyChart.
    direction string
    The direction for the current threshold. Direction is not allowed in a XyChart.
    label string
    A label for the threshold.
    targetAxis string
    The target axis to use for plotting the threshold. Target axis is not allowed in a Scorecard.
    value number
    The value of the threshold. The value should be defined in the native scale of the metric.
    color str
    The state color for this threshold. Color is not allowed in a XyChart.
    direction str
    The direction for the current threshold. Direction is not allowed in a XyChart.
    label str
    A label for the threshold.
    target_axis str
    The target axis to use for plotting the threshold. Target axis is not allowed in a Scorecard.
    value float
    The value of the threshold. The value should be defined in the native scale of the metric.
    color String
    The state color for this threshold. Color is not allowed in a XyChart.
    direction String
    The direction for the current threshold. Direction is not allowed in a XyChart.
    label String
    A label for the threshold.
    targetAxis String
    The target axis to use for plotting the threshold. Target axis is not allowed in a Scorecard.
    value Number
    The value of the threshold. The value should be defined in the native scale of the metric.

    ThresholdTargetAxis, ThresholdTargetAxisArgs

    TargetAxisUnspecified
    TARGET_AXIS_UNSPECIFIEDThe target axis was not specified. Defaults to Y1.
    Y1
    Y1The y_axis (the right axis of chart).
    Y2
    Y2The y2_axis (the left axis of chart).
    ThresholdTargetAxisTargetAxisUnspecified
    TARGET_AXIS_UNSPECIFIEDThe target axis was not specified. Defaults to Y1.
    ThresholdTargetAxisY1
    Y1The y_axis (the right axis of chart).
    ThresholdTargetAxisY2
    Y2The y2_axis (the left axis of chart).
    TargetAxisUnspecified
    TARGET_AXIS_UNSPECIFIEDThe target axis was not specified. Defaults to Y1.
    Y1
    Y1The y_axis (the right axis of chart).
    Y2
    Y2The y2_axis (the left axis of chart).
    TargetAxisUnspecified
    TARGET_AXIS_UNSPECIFIEDThe target axis was not specified. Defaults to Y1.
    Y1
    Y1The y_axis (the right axis of chart).
    Y2
    Y2The y2_axis (the left axis of chart).
    TARGET_AXIS_UNSPECIFIED
    TARGET_AXIS_UNSPECIFIEDThe target axis was not specified. Defaults to Y1.
    Y1
    Y1The y_axis (the right axis of chart).
    Y2
    Y2The y2_axis (the left axis of chart).
    "TARGET_AXIS_UNSPECIFIED"
    TARGET_AXIS_UNSPECIFIEDThe target axis was not specified. Defaults to Y1.
    "Y1"
    Y1The y_axis (the right axis of chart).
    "Y2"
    Y2The y2_axis (the left axis of chart).

    Tile, TileArgs

    Height int
    The height of the tile, measured in grid blocks. Tiles must have a minimum height of 1.
    Widget Pulumi.GoogleNative.Monitoring.V1.Inputs.Widget
    The informational widget contained in the tile. For example an XyChart.
    Width int
    The width of the tile, measured in grid blocks. Tiles must have a minimum width of 1.
    XPos int
    The zero-indexed position of the tile in grid blocks relative to the left edge of the grid. Tiles must be contained within the specified number of columns. x_pos cannot be negative.
    YPos int
    The zero-indexed position of the tile in grid blocks relative to the top edge of the grid. y_pos cannot be negative.
    Height int
    The height of the tile, measured in grid blocks. Tiles must have a minimum height of 1.
    Widget Widget
    The informational widget contained in the tile. For example an XyChart.
    Width int
    The width of the tile, measured in grid blocks. Tiles must have a minimum width of 1.
    XPos int
    The zero-indexed position of the tile in grid blocks relative to the left edge of the grid. Tiles must be contained within the specified number of columns. x_pos cannot be negative.
    YPos int
    The zero-indexed position of the tile in grid blocks relative to the top edge of the grid. y_pos cannot be negative.
    height Integer
    The height of the tile, measured in grid blocks. Tiles must have a minimum height of 1.
    widget Widget
    The informational widget contained in the tile. For example an XyChart.
    width Integer
    The width of the tile, measured in grid blocks. Tiles must have a minimum width of 1.
    xPos Integer
    The zero-indexed position of the tile in grid blocks relative to the left edge of the grid. Tiles must be contained within the specified number of columns. x_pos cannot be negative.
    yPos Integer
    The zero-indexed position of the tile in grid blocks relative to the top edge of the grid. y_pos cannot be negative.
    height number
    The height of the tile, measured in grid blocks. Tiles must have a minimum height of 1.
    widget Widget
    The informational widget contained in the tile. For example an XyChart.
    width number
    The width of the tile, measured in grid blocks. Tiles must have a minimum width of 1.
    xPos number
    The zero-indexed position of the tile in grid blocks relative to the left edge of the grid. Tiles must be contained within the specified number of columns. x_pos cannot be negative.
    yPos number
    The zero-indexed position of the tile in grid blocks relative to the top edge of the grid. y_pos cannot be negative.
    height int
    The height of the tile, measured in grid blocks. Tiles must have a minimum height of 1.
    widget Widget
    The informational widget contained in the tile. For example an XyChart.
    width int
    The width of the tile, measured in grid blocks. Tiles must have a minimum width of 1.
    x_pos int
    The zero-indexed position of the tile in grid blocks relative to the left edge of the grid. Tiles must be contained within the specified number of columns. x_pos cannot be negative.
    y_pos int
    The zero-indexed position of the tile in grid blocks relative to the top edge of the grid. y_pos cannot be negative.
    height Number
    The height of the tile, measured in grid blocks. Tiles must have a minimum height of 1.
    widget Property Map
    The informational widget contained in the tile. For example an XyChart.
    width Number
    The width of the tile, measured in grid blocks. Tiles must have a minimum width of 1.
    xPos Number
    The zero-indexed position of the tile in grid blocks relative to the left edge of the grid. Tiles must be contained within the specified number of columns. x_pos cannot be negative.
    yPos Number
    The zero-indexed position of the tile in grid blocks relative to the top edge of the grid. y_pos cannot be negative.

    TileResponse, TileResponseArgs

    Height int
    The height of the tile, measured in grid blocks. Tiles must have a minimum height of 1.
    Widget Pulumi.GoogleNative.Monitoring.V1.Inputs.WidgetResponse
    The informational widget contained in the tile. For example an XyChart.
    Width int
    The width of the tile, measured in grid blocks. Tiles must have a minimum width of 1.
    XPos int
    The zero-indexed position of the tile in grid blocks relative to the left edge of the grid. Tiles must be contained within the specified number of columns. x_pos cannot be negative.
    YPos int
    The zero-indexed position of the tile in grid blocks relative to the top edge of the grid. y_pos cannot be negative.
    Height int
    The height of the tile, measured in grid blocks. Tiles must have a minimum height of 1.
    Widget WidgetResponse
    The informational widget contained in the tile. For example an XyChart.
    Width int
    The width of the tile, measured in grid blocks. Tiles must have a minimum width of 1.
    XPos int
    The zero-indexed position of the tile in grid blocks relative to the left edge of the grid. Tiles must be contained within the specified number of columns. x_pos cannot be negative.
    YPos int
    The zero-indexed position of the tile in grid blocks relative to the top edge of the grid. y_pos cannot be negative.
    height Integer
    The height of the tile, measured in grid blocks. Tiles must have a minimum height of 1.
    widget WidgetResponse
    The informational widget contained in the tile. For example an XyChart.
    width Integer
    The width of the tile, measured in grid blocks. Tiles must have a minimum width of 1.
    xPos Integer
    The zero-indexed position of the tile in grid blocks relative to the left edge of the grid. Tiles must be contained within the specified number of columns. x_pos cannot be negative.
    yPos Integer
    The zero-indexed position of the tile in grid blocks relative to the top edge of the grid. y_pos cannot be negative.
    height number
    The height of the tile, measured in grid blocks. Tiles must have a minimum height of 1.
    widget WidgetResponse
    The informational widget contained in the tile. For example an XyChart.
    width number
    The width of the tile, measured in grid blocks. Tiles must have a minimum width of 1.
    xPos number
    The zero-indexed position of the tile in grid blocks relative to the left edge of the grid. Tiles must be contained within the specified number of columns. x_pos cannot be negative.
    yPos number
    The zero-indexed position of the tile in grid blocks relative to the top edge of the grid. y_pos cannot be negative.
    height int
    The height of the tile, measured in grid blocks. Tiles must have a minimum height of 1.
    widget WidgetResponse
    The informational widget contained in the tile. For example an XyChart.
    width int
    The width of the tile, measured in grid blocks. Tiles must have a minimum width of 1.
    x_pos int
    The zero-indexed position of the tile in grid blocks relative to the left edge of the grid. Tiles must be contained within the specified number of columns. x_pos cannot be negative.
    y_pos int
    The zero-indexed position of the tile in grid blocks relative to the top edge of the grid. y_pos cannot be negative.
    height Number
    The height of the tile, measured in grid blocks. Tiles must have a minimum height of 1.
    widget Property Map
    The informational widget contained in the tile. For example an XyChart.
    width Number
    The width of the tile, measured in grid blocks. Tiles must have a minimum width of 1.
    xPos Number
    The zero-indexed position of the tile in grid blocks relative to the left edge of the grid. Tiles must be contained within the specified number of columns. x_pos cannot be negative.
    yPos Number
    The zero-indexed position of the tile in grid blocks relative to the top edge of the grid. y_pos cannot be negative.

    TimeSeriesFilter, TimeSeriesFilterArgs

    Filter string
    The monitoring filter (https://cloud.google.com/monitoring/api/v3/filters) that identifies the metric types, resources, and projects to query.
    Aggregation Pulumi.GoogleNative.Monitoring.V1.Inputs.Aggregation
    By default, the raw time series data is returned. Use this field to combine multiple time series for different views of the data.
    PickTimeSeriesFilter Pulumi.GoogleNative.Monitoring.V1.Inputs.PickTimeSeriesFilter
    Ranking based time series filter.
    SecondaryAggregation Pulumi.GoogleNative.Monitoring.V1.Inputs.Aggregation
    Apply a second aggregation after aggregation is applied.
    StatisticalTimeSeriesFilter Pulumi.GoogleNative.Monitoring.V1.Inputs.StatisticalTimeSeriesFilter
    Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    Deprecated:Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    Filter string
    The monitoring filter (https://cloud.google.com/monitoring/api/v3/filters) that identifies the metric types, resources, and projects to query.
    Aggregation Aggregation
    By default, the raw time series data is returned. Use this field to combine multiple time series for different views of the data.
    PickTimeSeriesFilter PickTimeSeriesFilter
    Ranking based time series filter.
    SecondaryAggregation Aggregation
    Apply a second aggregation after aggregation is applied.
    StatisticalTimeSeriesFilter StatisticalTimeSeriesFilter
    Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    Deprecated:Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    filter String
    The monitoring filter (https://cloud.google.com/monitoring/api/v3/filters) that identifies the metric types, resources, and projects to query.
    aggregation Aggregation
    By default, the raw time series data is returned. Use this field to combine multiple time series for different views of the data.
    pickTimeSeriesFilter PickTimeSeriesFilter
    Ranking based time series filter.
    secondaryAggregation Aggregation
    Apply a second aggregation after aggregation is applied.
    statisticalTimeSeriesFilter StatisticalTimeSeriesFilter
    Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    Deprecated:Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    filter string
    The monitoring filter (https://cloud.google.com/monitoring/api/v3/filters) that identifies the metric types, resources, and projects to query.
    aggregation Aggregation
    By default, the raw time series data is returned. Use this field to combine multiple time series for different views of the data.
    pickTimeSeriesFilter PickTimeSeriesFilter
    Ranking based time series filter.
    secondaryAggregation Aggregation
    Apply a second aggregation after aggregation is applied.
    statisticalTimeSeriesFilter StatisticalTimeSeriesFilter
    Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    Deprecated:Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    filter str
    The monitoring filter (https://cloud.google.com/monitoring/api/v3/filters) that identifies the metric types, resources, and projects to query.
    aggregation Aggregation
    By default, the raw time series data is returned. Use this field to combine multiple time series for different views of the data.
    pick_time_series_filter PickTimeSeriesFilter
    Ranking based time series filter.
    secondary_aggregation Aggregation
    Apply a second aggregation after aggregation is applied.
    statistical_time_series_filter StatisticalTimeSeriesFilter
    Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    Deprecated:Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    filter String
    The monitoring filter (https://cloud.google.com/monitoring/api/v3/filters) that identifies the metric types, resources, and projects to query.
    aggregation Property Map
    By default, the raw time series data is returned. Use this field to combine multiple time series for different views of the data.
    pickTimeSeriesFilter Property Map
    Ranking based time series filter.
    secondaryAggregation Property Map
    Apply a second aggregation after aggregation is applied.
    statisticalTimeSeriesFilter Property Map
    Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    Deprecated:Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    TimeSeriesFilterRatio, TimeSeriesFilterRatioArgs

    Denominator Pulumi.GoogleNative.Monitoring.V1.Inputs.RatioPart
    The denominator of the ratio.
    Numerator Pulumi.GoogleNative.Monitoring.V1.Inputs.RatioPart
    The numerator of the ratio.
    PickTimeSeriesFilter Pulumi.GoogleNative.Monitoring.V1.Inputs.PickTimeSeriesFilter
    Ranking based time series filter.
    SecondaryAggregation Pulumi.GoogleNative.Monitoring.V1.Inputs.Aggregation
    Apply a second aggregation after the ratio is computed.
    StatisticalTimeSeriesFilter Pulumi.GoogleNative.Monitoring.V1.Inputs.StatisticalTimeSeriesFilter
    Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    Deprecated:Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    Denominator RatioPart
    The denominator of the ratio.
    Numerator RatioPart
    The numerator of the ratio.
    PickTimeSeriesFilter PickTimeSeriesFilter
    Ranking based time series filter.
    SecondaryAggregation Aggregation
    Apply a second aggregation after the ratio is computed.
    StatisticalTimeSeriesFilter StatisticalTimeSeriesFilter
    Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    Deprecated:Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    denominator RatioPart
    The denominator of the ratio.
    numerator RatioPart
    The numerator of the ratio.
    pickTimeSeriesFilter PickTimeSeriesFilter
    Ranking based time series filter.
    secondaryAggregation Aggregation
    Apply a second aggregation after the ratio is computed.
    statisticalTimeSeriesFilter StatisticalTimeSeriesFilter
    Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    Deprecated:Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    denominator RatioPart
    The denominator of the ratio.
    numerator RatioPart
    The numerator of the ratio.
    pickTimeSeriesFilter PickTimeSeriesFilter
    Ranking based time series filter.
    secondaryAggregation Aggregation
    Apply a second aggregation after the ratio is computed.
    statisticalTimeSeriesFilter StatisticalTimeSeriesFilter
    Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    Deprecated:Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    denominator RatioPart
    The denominator of the ratio.
    numerator RatioPart
    The numerator of the ratio.
    pick_time_series_filter PickTimeSeriesFilter
    Ranking based time series filter.
    secondary_aggregation Aggregation
    Apply a second aggregation after the ratio is computed.
    statistical_time_series_filter StatisticalTimeSeriesFilter
    Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    Deprecated:Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    denominator Property Map
    The denominator of the ratio.
    numerator Property Map
    The numerator of the ratio.
    pickTimeSeriesFilter Property Map
    Ranking based time series filter.
    secondaryAggregation Property Map
    Apply a second aggregation after the ratio is computed.
    statisticalTimeSeriesFilter Property Map
    Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    Deprecated:Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    TimeSeriesFilterRatioResponse, TimeSeriesFilterRatioResponseArgs

    Denominator Pulumi.GoogleNative.Monitoring.V1.Inputs.RatioPartResponse
    The denominator of the ratio.
    Numerator Pulumi.GoogleNative.Monitoring.V1.Inputs.RatioPartResponse
    The numerator of the ratio.
    PickTimeSeriesFilter Pulumi.GoogleNative.Monitoring.V1.Inputs.PickTimeSeriesFilterResponse
    Ranking based time series filter.
    SecondaryAggregation Pulumi.GoogleNative.Monitoring.V1.Inputs.AggregationResponse
    Apply a second aggregation after the ratio is computed.
    StatisticalTimeSeriesFilter Pulumi.GoogleNative.Monitoring.V1.Inputs.StatisticalTimeSeriesFilterResponse
    Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    Deprecated:Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    Denominator RatioPartResponse
    The denominator of the ratio.
    Numerator RatioPartResponse
    The numerator of the ratio.
    PickTimeSeriesFilter PickTimeSeriesFilterResponse
    Ranking based time series filter.
    SecondaryAggregation AggregationResponse
    Apply a second aggregation after the ratio is computed.
    StatisticalTimeSeriesFilter StatisticalTimeSeriesFilterResponse
    Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    Deprecated:Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    denominator RatioPartResponse
    The denominator of the ratio.
    numerator RatioPartResponse
    The numerator of the ratio.
    pickTimeSeriesFilter PickTimeSeriesFilterResponse
    Ranking based time series filter.
    secondaryAggregation AggregationResponse
    Apply a second aggregation after the ratio is computed.
    statisticalTimeSeriesFilter StatisticalTimeSeriesFilterResponse
    Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    Deprecated:Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    denominator RatioPartResponse
    The denominator of the ratio.
    numerator RatioPartResponse
    The numerator of the ratio.
    pickTimeSeriesFilter PickTimeSeriesFilterResponse
    Ranking based time series filter.
    secondaryAggregation AggregationResponse
    Apply a second aggregation after the ratio is computed.
    statisticalTimeSeriesFilter StatisticalTimeSeriesFilterResponse
    Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    Deprecated:Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    denominator RatioPartResponse
    The denominator of the ratio.
    numerator RatioPartResponse
    The numerator of the ratio.
    pick_time_series_filter PickTimeSeriesFilterResponse
    Ranking based time series filter.
    secondary_aggregation AggregationResponse
    Apply a second aggregation after the ratio is computed.
    statistical_time_series_filter StatisticalTimeSeriesFilterResponse
    Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    Deprecated:Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    denominator Property Map
    The denominator of the ratio.
    numerator Property Map
    The numerator of the ratio.
    pickTimeSeriesFilter Property Map
    Ranking based time series filter.
    secondaryAggregation Property Map
    Apply a second aggregation after the ratio is computed.
    statisticalTimeSeriesFilter Property Map
    Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    Deprecated:Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    TimeSeriesFilterResponse, TimeSeriesFilterResponseArgs

    Aggregation Pulumi.GoogleNative.Monitoring.V1.Inputs.AggregationResponse
    By default, the raw time series data is returned. Use this field to combine multiple time series for different views of the data.
    Filter string
    The monitoring filter (https://cloud.google.com/monitoring/api/v3/filters) that identifies the metric types, resources, and projects to query.
    PickTimeSeriesFilter Pulumi.GoogleNative.Monitoring.V1.Inputs.PickTimeSeriesFilterResponse
    Ranking based time series filter.
    SecondaryAggregation Pulumi.GoogleNative.Monitoring.V1.Inputs.AggregationResponse
    Apply a second aggregation after aggregation is applied.
    StatisticalTimeSeriesFilter Pulumi.GoogleNative.Monitoring.V1.Inputs.StatisticalTimeSeriesFilterResponse
    Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    Deprecated:Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    Aggregation AggregationResponse
    By default, the raw time series data is returned. Use this field to combine multiple time series for different views of the data.
    Filter string
    The monitoring filter (https://cloud.google.com/monitoring/api/v3/filters) that identifies the metric types, resources, and projects to query.
    PickTimeSeriesFilter PickTimeSeriesFilterResponse
    Ranking based time series filter.
    SecondaryAggregation AggregationResponse
    Apply a second aggregation after aggregation is applied.
    StatisticalTimeSeriesFilter StatisticalTimeSeriesFilterResponse
    Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    Deprecated:Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    aggregation AggregationResponse
    By default, the raw time series data is returned. Use this field to combine multiple time series for different views of the data.
    filter String
    The monitoring filter (https://cloud.google.com/monitoring/api/v3/filters) that identifies the metric types, resources, and projects to query.
    pickTimeSeriesFilter PickTimeSeriesFilterResponse
    Ranking based time series filter.
    secondaryAggregation AggregationResponse
    Apply a second aggregation after aggregation is applied.
    statisticalTimeSeriesFilter StatisticalTimeSeriesFilterResponse
    Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    Deprecated:Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    aggregation AggregationResponse
    By default, the raw time series data is returned. Use this field to combine multiple time series for different views of the data.
    filter string
    The monitoring filter (https://cloud.google.com/monitoring/api/v3/filters) that identifies the metric types, resources, and projects to query.
    pickTimeSeriesFilter PickTimeSeriesFilterResponse
    Ranking based time series filter.
    secondaryAggregation AggregationResponse
    Apply a second aggregation after aggregation is applied.
    statisticalTimeSeriesFilter StatisticalTimeSeriesFilterResponse
    Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    Deprecated:Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    aggregation AggregationResponse
    By default, the raw time series data is returned. Use this field to combine multiple time series for different views of the data.
    filter str
    The monitoring filter (https://cloud.google.com/monitoring/api/v3/filters) that identifies the metric types, resources, and projects to query.
    pick_time_series_filter PickTimeSeriesFilterResponse
    Ranking based time series filter.
    secondary_aggregation AggregationResponse
    Apply a second aggregation after aggregation is applied.
    statistical_time_series_filter StatisticalTimeSeriesFilterResponse
    Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    Deprecated:Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    aggregation Property Map
    By default, the raw time series data is returned. Use this field to combine multiple time series for different views of the data.
    filter String
    The monitoring filter (https://cloud.google.com/monitoring/api/v3/filters) that identifies the metric types, resources, and projects to query.
    pickTimeSeriesFilter Property Map
    Ranking based time series filter.
    secondaryAggregation Property Map
    Apply a second aggregation after aggregation is applied.
    statisticalTimeSeriesFilter Property Map
    Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    Deprecated:Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.

    TimeSeriesQuery, TimeSeriesQueryArgs

    OpsAnalyticsQuery Pulumi.GoogleNative.Monitoring.V1.Inputs.OpsAnalyticsQuery
    Preview: A query used to fetch a time series, category series, or numeric series with SQL. This is a preview feature and may be subject to change before final release.
    OutputFullDuration bool
    Optional. If set, Cloud Monitoring will treat the full query duration as the alignment period so that there will be only 1 output value.*Note: This could override the configured alignment period except for the cases where a series of data points are expected, like - XyChart - Scorecard's spark chart
    PrometheusQuery string
    A query used to fetch time series with PromQL.
    TimeSeriesFilter Pulumi.GoogleNative.Monitoring.V1.Inputs.TimeSeriesFilter
    Filter parameters to fetch time series.
    TimeSeriesFilterRatio Pulumi.GoogleNative.Monitoring.V1.Inputs.TimeSeriesFilterRatio
    Parameters to fetch a ratio between two time series filters.
    TimeSeriesQueryLanguage string
    A query used to fetch time series with MQL.
    UnitOverride string
    The unit of data contained in fetched time series. If non-empty, this unit will override any unit that accompanies fetched data. The format is the same as the unit (https://cloud.google.com/monitoring/api/ref_v3/rest/v3/projects.metricDescriptors) field in MetricDescriptor.
    OpsAnalyticsQuery OpsAnalyticsQuery
    Preview: A query used to fetch a time series, category series, or numeric series with SQL. This is a preview feature and may be subject to change before final release.
    OutputFullDuration bool
    Optional. If set, Cloud Monitoring will treat the full query duration as the alignment period so that there will be only 1 output value.*Note: This could override the configured alignment period except for the cases where a series of data points are expected, like - XyChart - Scorecard's spark chart
    PrometheusQuery string
    A query used to fetch time series with PromQL.
    TimeSeriesFilter TimeSeriesFilter
    Filter parameters to fetch time series.
    TimeSeriesFilterRatio TimeSeriesFilterRatio
    Parameters to fetch a ratio between two time series filters.
    TimeSeriesQueryLanguage string
    A query used to fetch time series with MQL.
    UnitOverride string
    The unit of data contained in fetched time series. If non-empty, this unit will override any unit that accompanies fetched data. The format is the same as the unit (https://cloud.google.com/monitoring/api/ref_v3/rest/v3/projects.metricDescriptors) field in MetricDescriptor.
    opsAnalyticsQuery OpsAnalyticsQuery
    Preview: A query used to fetch a time series, category series, or numeric series with SQL. This is a preview feature and may be subject to change before final release.
    outputFullDuration Boolean
    Optional. If set, Cloud Monitoring will treat the full query duration as the alignment period so that there will be only 1 output value.*Note: This could override the configured alignment period except for the cases where a series of data points are expected, like - XyChart - Scorecard's spark chart
    prometheusQuery String
    A query used to fetch time series with PromQL.
    timeSeriesFilter TimeSeriesFilter
    Filter parameters to fetch time series.
    timeSeriesFilterRatio TimeSeriesFilterRatio
    Parameters to fetch a ratio between two time series filters.
    timeSeriesQueryLanguage String
    A query used to fetch time series with MQL.
    unitOverride String
    The unit of data contained in fetched time series. If non-empty, this unit will override any unit that accompanies fetched data. The format is the same as the unit (https://cloud.google.com/monitoring/api/ref_v3/rest/v3/projects.metricDescriptors) field in MetricDescriptor.
    opsAnalyticsQuery OpsAnalyticsQuery
    Preview: A query used to fetch a time series, category series, or numeric series with SQL. This is a preview feature and may be subject to change before final release.
    outputFullDuration boolean
    Optional. If set, Cloud Monitoring will treat the full query duration as the alignment period so that there will be only 1 output value.*Note: This could override the configured alignment period except for the cases where a series of data points are expected, like - XyChart - Scorecard's spark chart
    prometheusQuery string
    A query used to fetch time series with PromQL.
    timeSeriesFilter TimeSeriesFilter
    Filter parameters to fetch time series.
    timeSeriesFilterRatio TimeSeriesFilterRatio
    Parameters to fetch a ratio between two time series filters.
    timeSeriesQueryLanguage string
    A query used to fetch time series with MQL.
    unitOverride string
    The unit of data contained in fetched time series. If non-empty, this unit will override any unit that accompanies fetched data. The format is the same as the unit (https://cloud.google.com/monitoring/api/ref_v3/rest/v3/projects.metricDescriptors) field in MetricDescriptor.
    ops_analytics_query OpsAnalyticsQuery
    Preview: A query used to fetch a time series, category series, or numeric series with SQL. This is a preview feature and may be subject to change before final release.
    output_full_duration bool
    Optional. If set, Cloud Monitoring will treat the full query duration as the alignment period so that there will be only 1 output value.*Note: This could override the configured alignment period except for the cases where a series of data points are expected, like - XyChart - Scorecard's spark chart
    prometheus_query str
    A query used to fetch time series with PromQL.
    time_series_filter TimeSeriesFilter
    Filter parameters to fetch time series.
    time_series_filter_ratio TimeSeriesFilterRatio
    Parameters to fetch a ratio between two time series filters.
    time_series_query_language str
    A query used to fetch time series with MQL.
    unit_override str
    The unit of data contained in fetched time series. If non-empty, this unit will override any unit that accompanies fetched data. The format is the same as the unit (https://cloud.google.com/monitoring/api/ref_v3/rest/v3/projects.metricDescriptors) field in MetricDescriptor.
    opsAnalyticsQuery Property Map
    Preview: A query used to fetch a time series, category series, or numeric series with SQL. This is a preview feature and may be subject to change before final release.
    outputFullDuration Boolean
    Optional. If set, Cloud Monitoring will treat the full query duration as the alignment period so that there will be only 1 output value.*Note: This could override the configured alignment period except for the cases where a series of data points are expected, like - XyChart - Scorecard's spark chart
    prometheusQuery String
    A query used to fetch time series with PromQL.
    timeSeriesFilter Property Map
    Filter parameters to fetch time series.
    timeSeriesFilterRatio Property Map
    Parameters to fetch a ratio between two time series filters.
    timeSeriesQueryLanguage String
    A query used to fetch time series with MQL.
    unitOverride String
    The unit of data contained in fetched time series. If non-empty, this unit will override any unit that accompanies fetched data. The format is the same as the unit (https://cloud.google.com/monitoring/api/ref_v3/rest/v3/projects.metricDescriptors) field in MetricDescriptor.

    TimeSeriesQueryResponse, TimeSeriesQueryResponseArgs

    OpsAnalyticsQuery Pulumi.GoogleNative.Monitoring.V1.Inputs.OpsAnalyticsQueryResponse
    Preview: A query used to fetch a time series, category series, or numeric series with SQL. This is a preview feature and may be subject to change before final release.
    OutputFullDuration bool
    Optional. If set, Cloud Monitoring will treat the full query duration as the alignment period so that there will be only 1 output value.*Note: This could override the configured alignment period except for the cases where a series of data points are expected, like - XyChart - Scorecard's spark chart
    PrometheusQuery string
    A query used to fetch time series with PromQL.
    TimeSeriesFilter Pulumi.GoogleNative.Monitoring.V1.Inputs.TimeSeriesFilterResponse
    Filter parameters to fetch time series.
    TimeSeriesFilterRatio Pulumi.GoogleNative.Monitoring.V1.Inputs.TimeSeriesFilterRatioResponse
    Parameters to fetch a ratio between two time series filters.
    TimeSeriesQueryLanguage string
    A query used to fetch time series with MQL.
    UnitOverride string
    The unit of data contained in fetched time series. If non-empty, this unit will override any unit that accompanies fetched data. The format is the same as the unit (https://cloud.google.com/monitoring/api/ref_v3/rest/v3/projects.metricDescriptors) field in MetricDescriptor.
    OpsAnalyticsQuery OpsAnalyticsQueryResponse
    Preview: A query used to fetch a time series, category series, or numeric series with SQL. This is a preview feature and may be subject to change before final release.
    OutputFullDuration bool
    Optional. If set, Cloud Monitoring will treat the full query duration as the alignment period so that there will be only 1 output value.*Note: This could override the configured alignment period except for the cases where a series of data points are expected, like - XyChart - Scorecard's spark chart
    PrometheusQuery string
    A query used to fetch time series with PromQL.
    TimeSeriesFilter TimeSeriesFilterResponse
    Filter parameters to fetch time series.
    TimeSeriesFilterRatio TimeSeriesFilterRatioResponse
    Parameters to fetch a ratio between two time series filters.
    TimeSeriesQueryLanguage string
    A query used to fetch time series with MQL.
    UnitOverride string
    The unit of data contained in fetched time series. If non-empty, this unit will override any unit that accompanies fetched data. The format is the same as the unit (https://cloud.google.com/monitoring/api/ref_v3/rest/v3/projects.metricDescriptors) field in MetricDescriptor.
    opsAnalyticsQuery OpsAnalyticsQueryResponse
    Preview: A query used to fetch a time series, category series, or numeric series with SQL. This is a preview feature and may be subject to change before final release.
    outputFullDuration Boolean
    Optional. If set, Cloud Monitoring will treat the full query duration as the alignment period so that there will be only 1 output value.*Note: This could override the configured alignment period except for the cases where a series of data points are expected, like - XyChart - Scorecard's spark chart
    prometheusQuery String
    A query used to fetch time series with PromQL.
    timeSeriesFilter TimeSeriesFilterResponse
    Filter parameters to fetch time series.
    timeSeriesFilterRatio TimeSeriesFilterRatioResponse
    Parameters to fetch a ratio between two time series filters.
    timeSeriesQueryLanguage String
    A query used to fetch time series with MQL.
    unitOverride String
    The unit of data contained in fetched time series. If non-empty, this unit will override any unit that accompanies fetched data. The format is the same as the unit (https://cloud.google.com/monitoring/api/ref_v3/rest/v3/projects.metricDescriptors) field in MetricDescriptor.
    opsAnalyticsQuery OpsAnalyticsQueryResponse
    Preview: A query used to fetch a time series, category series, or numeric series with SQL. This is a preview feature and may be subject to change before final release.
    outputFullDuration boolean
    Optional. If set, Cloud Monitoring will treat the full query duration as the alignment period so that there will be only 1 output value.*Note: This could override the configured alignment period except for the cases where a series of data points are expected, like - XyChart - Scorecard's spark chart
    prometheusQuery string
    A query used to fetch time series with PromQL.
    timeSeriesFilter TimeSeriesFilterResponse
    Filter parameters to fetch time series.
    timeSeriesFilterRatio TimeSeriesFilterRatioResponse
    Parameters to fetch a ratio between two time series filters.
    timeSeriesQueryLanguage string
    A query used to fetch time series with MQL.
    unitOverride string
    The unit of data contained in fetched time series. If non-empty, this unit will override any unit that accompanies fetched data. The format is the same as the unit (https://cloud.google.com/monitoring/api/ref_v3/rest/v3/projects.metricDescriptors) field in MetricDescriptor.
    ops_analytics_query OpsAnalyticsQueryResponse
    Preview: A query used to fetch a time series, category series, or numeric series with SQL. This is a preview feature and may be subject to change before final release.
    output_full_duration bool
    Optional. If set, Cloud Monitoring will treat the full query duration as the alignment period so that there will be only 1 output value.*Note: This could override the configured alignment period except for the cases where a series of data points are expected, like - XyChart - Scorecard's spark chart
    prometheus_query str
    A query used to fetch time series with PromQL.
    time_series_filter TimeSeriesFilterResponse
    Filter parameters to fetch time series.
    time_series_filter_ratio TimeSeriesFilterRatioResponse
    Parameters to fetch a ratio between two time series filters.
    time_series_query_language str
    A query used to fetch time series with MQL.
    unit_override str
    The unit of data contained in fetched time series. If non-empty, this unit will override any unit that accompanies fetched data. The format is the same as the unit (https://cloud.google.com/monitoring/api/ref_v3/rest/v3/projects.metricDescriptors) field in MetricDescriptor.
    opsAnalyticsQuery Property Map
    Preview: A query used to fetch a time series, category series, or numeric series with SQL. This is a preview feature and may be subject to change before final release.
    outputFullDuration Boolean
    Optional. If set, Cloud Monitoring will treat the full query duration as the alignment period so that there will be only 1 output value.*Note: This could override the configured alignment period except for the cases where a series of data points are expected, like - XyChart - Scorecard's spark chart
    prometheusQuery String
    A query used to fetch time series with PromQL.
    timeSeriesFilter Property Map
    Filter parameters to fetch time series.
    timeSeriesFilterRatio Property Map
    Parameters to fetch a ratio between two time series filters.
    timeSeriesQueryLanguage String
    A query used to fetch time series with MQL.
    unitOverride String
    The unit of data contained in fetched time series. If non-empty, this unit will override any unit that accompanies fetched data. The format is the same as the unit (https://cloud.google.com/monitoring/api/ref_v3/rest/v3/projects.metricDescriptors) field in MetricDescriptor.

    TimeSeriesTable, TimeSeriesTableArgs

    DataSets []TableDataSet
    The data displayed in this table.
    ColumnSettings []ColumnSettings
    Optional. The list of the persistent column settings for the table.
    MetricVisualization TimeSeriesTableMetricVisualization
    Optional. Store rendering strategy
    dataSets List<TableDataSet>
    The data displayed in this table.
    columnSettings List<ColumnSettings>
    Optional. The list of the persistent column settings for the table.
    metricVisualization TimeSeriesTableMetricVisualization
    Optional. Store rendering strategy
    dataSets TableDataSet[]
    The data displayed in this table.
    columnSettings ColumnSettings[]
    Optional. The list of the persistent column settings for the table.
    metricVisualization TimeSeriesTableMetricVisualization
    Optional. Store rendering strategy
    data_sets Sequence[TableDataSet]
    The data displayed in this table.
    column_settings Sequence[ColumnSettings]
    Optional. The list of the persistent column settings for the table.
    metric_visualization TimeSeriesTableMetricVisualization
    Optional. Store rendering strategy
    dataSets List<Property Map>
    The data displayed in this table.
    columnSettings List<Property Map>
    Optional. The list of the persistent column settings for the table.
    metricVisualization "METRIC_VISUALIZATION_UNSPECIFIED" | "NUMBER" | "BAR"
    Optional. Store rendering strategy

    TimeSeriesTableMetricVisualization, TimeSeriesTableMetricVisualizationArgs

    MetricVisualizationUnspecified
    METRIC_VISUALIZATION_UNSPECIFIEDUnspecified state
    Number
    NUMBERDefault text rendering
    Bar
    BARHorizontal bar rendering
    TimeSeriesTableMetricVisualizationMetricVisualizationUnspecified
    METRIC_VISUALIZATION_UNSPECIFIEDUnspecified state
    TimeSeriesTableMetricVisualizationNumber
    NUMBERDefault text rendering
    TimeSeriesTableMetricVisualizationBar
    BARHorizontal bar rendering
    MetricVisualizationUnspecified
    METRIC_VISUALIZATION_UNSPECIFIEDUnspecified state
    Number
    NUMBERDefault text rendering
    Bar
    BARHorizontal bar rendering
    MetricVisualizationUnspecified
    METRIC_VISUALIZATION_UNSPECIFIEDUnspecified state
    Number
    NUMBERDefault text rendering
    Bar
    BARHorizontal bar rendering
    METRIC_VISUALIZATION_UNSPECIFIED
    METRIC_VISUALIZATION_UNSPECIFIEDUnspecified state
    NUMBER
    NUMBERDefault text rendering
    BAR
    BARHorizontal bar rendering
    "METRIC_VISUALIZATION_UNSPECIFIED"
    METRIC_VISUALIZATION_UNSPECIFIEDUnspecified state
    "NUMBER"
    NUMBERDefault text rendering
    "BAR"
    BARHorizontal bar rendering

    TimeSeriesTableResponse, TimeSeriesTableResponseArgs

    ColumnSettings List<Pulumi.GoogleNative.Monitoring.V1.Inputs.ColumnSettingsResponse>
    Optional. The list of the persistent column settings for the table.
    DataSets List<Pulumi.GoogleNative.Monitoring.V1.Inputs.TableDataSetResponse>
    The data displayed in this table.
    MetricVisualization string
    Optional. Store rendering strategy
    ColumnSettings []ColumnSettingsResponse
    Optional. The list of the persistent column settings for the table.
    DataSets []TableDataSetResponse
    The data displayed in this table.
    MetricVisualization string
    Optional. Store rendering strategy
    columnSettings List<ColumnSettingsResponse>
    Optional. The list of the persistent column settings for the table.
    dataSets List<TableDataSetResponse>
    The data displayed in this table.
    metricVisualization String
    Optional. Store rendering strategy
    columnSettings ColumnSettingsResponse[]
    Optional. The list of the persistent column settings for the table.
    dataSets TableDataSetResponse[]
    The data displayed in this table.
    metricVisualization string
    Optional. Store rendering strategy
    column_settings Sequence[ColumnSettingsResponse]
    Optional. The list of the persistent column settings for the table.
    data_sets Sequence[TableDataSetResponse]
    The data displayed in this table.
    metric_visualization str
    Optional. Store rendering strategy
    columnSettings List<Property Map>
    Optional. The list of the persistent column settings for the table.
    dataSets List<Property Map>
    The data displayed in this table.
    metricVisualization String
    Optional. Store rendering strategy

    Widget, WidgetArgs

    AlertChart Pulumi.GoogleNative.Monitoring.V1.Inputs.AlertChart
    A chart of alert policy data.
    Blank Pulumi.GoogleNative.Monitoring.V1.Inputs.Empty
    A blank space.
    CollapsibleGroup Pulumi.GoogleNative.Monitoring.V1.Inputs.CollapsibleGroup
    A widget that groups the other widgets. All widgets that are within the area spanned by the grouping widget are considered member widgets.
    ErrorReportingPanel Pulumi.GoogleNative.Monitoring.V1.Inputs.ErrorReportingPanel
    A widget that displays a list of error groups.
    Id string
    Optional. The widget id. Ids may be made up of alphanumerics, dashes and underscores. Widget ids are optional.
    IncidentList Pulumi.GoogleNative.Monitoring.V1.Inputs.IncidentList
    A widget that shows list of incidents.
    LogsPanel Pulumi.GoogleNative.Monitoring.V1.Inputs.LogsPanel
    A widget that shows a stream of logs.
    PieChart Pulumi.GoogleNative.Monitoring.V1.Inputs.PieChart
    A widget that displays timeseries data as a pie chart.
    Scorecard Pulumi.GoogleNative.Monitoring.V1.Inputs.Scorecard
    A scorecard summarizing time series data.
    Text Pulumi.GoogleNative.Monitoring.V1.Inputs.Text
    A raw string or markdown displaying textual content.
    TimeSeriesTable Pulumi.GoogleNative.Monitoring.V1.Inputs.TimeSeriesTable
    A widget that displays time series data in a tabular format.
    Title string
    Optional. The title of the widget.
    XyChart Pulumi.GoogleNative.Monitoring.V1.Inputs.XyChart
    A chart of time series data.
    AlertChart AlertChart
    A chart of alert policy data.
    Blank Empty
    A blank space.
    CollapsibleGroup CollapsibleGroup
    A widget that groups the other widgets. All widgets that are within the area spanned by the grouping widget are considered member widgets.
    ErrorReportingPanel ErrorReportingPanel
    A widget that displays a list of error groups.
    Id string
    Optional. The widget id. Ids may be made up of alphanumerics, dashes and underscores. Widget ids are optional.
    IncidentList IncidentList
    A widget that shows list of incidents.
    LogsPanel LogsPanel
    A widget that shows a stream of logs.
    PieChart PieChart
    A widget that displays timeseries data as a pie chart.
    Scorecard Scorecard
    A scorecard summarizing time series data.
    Text Text
    A raw string or markdown displaying textual content.
    TimeSeriesTable TimeSeriesTable
    A widget that displays time series data in a tabular format.
    Title string
    Optional. The title of the widget.
    XyChart XyChart
    A chart of time series data.
    alertChart AlertChart
    A chart of alert policy data.
    blank Empty
    A blank space.
    collapsibleGroup CollapsibleGroup
    A widget that groups the other widgets. All widgets that are within the area spanned by the grouping widget are considered member widgets.
    errorReportingPanel ErrorReportingPanel
    A widget that displays a list of error groups.
    id String
    Optional. The widget id. Ids may be made up of alphanumerics, dashes and underscores. Widget ids are optional.
    incidentList IncidentList
    A widget that shows list of incidents.
    logsPanel LogsPanel
    A widget that shows a stream of logs.
    pieChart PieChart
    A widget that displays timeseries data as a pie chart.
    scorecard Scorecard
    A scorecard summarizing time series data.
    text Text
    A raw string or markdown displaying textual content.
    timeSeriesTable TimeSeriesTable
    A widget that displays time series data in a tabular format.
    title String
    Optional. The title of the widget.
    xyChart XyChart
    A chart of time series data.
    alertChart AlertChart
    A chart of alert policy data.
    blank Empty
    A blank space.
    collapsibleGroup CollapsibleGroup
    A widget that groups the other widgets. All widgets that are within the area spanned by the grouping widget are considered member widgets.
    errorReportingPanel ErrorReportingPanel
    A widget that displays a list of error groups.
    id string
    Optional. The widget id. Ids may be made up of alphanumerics, dashes and underscores. Widget ids are optional.
    incidentList IncidentList
    A widget that shows list of incidents.
    logsPanel LogsPanel
    A widget that shows a stream of logs.
    pieChart PieChart
    A widget that displays timeseries data as a pie chart.
    scorecard Scorecard
    A scorecard summarizing time series data.
    text Text
    A raw string or markdown displaying textual content.
    timeSeriesTable TimeSeriesTable
    A widget that displays time series data in a tabular format.
    title string
    Optional. The title of the widget.
    xyChart XyChart
    A chart of time series data.
    alert_chart AlertChart
    A chart of alert policy data.
    blank Empty
    A blank space.
    collapsible_group CollapsibleGroup
    A widget that groups the other widgets. All widgets that are within the area spanned by the grouping widget are considered member widgets.