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Google Cloud Native v0.32.0 published on Wednesday, Nov 29, 2023 by Pulumi
pulumi/pulumi-google-native

google-native.aiplatform/v1.EntityType

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Google Cloud Native v0.32.0 published on Wednesday, Nov 29, 2023 by Pulumi
pulumi/pulumi-google-native

    Creates a new EntityType in a given Featurestore.

    Create EntityType Resource

    Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.

    Constructor syntax

    new EntityType(name: string, args: EntityTypeArgs, opts?: CustomResourceOptions);
    @overload
def EntityType(resource_name: str,
               args: EntityTypeArgs,
               opts: Optional[ResourceOptions] = None)

@overload
def EntityType(resource_name: str,
               opts: Optional[ResourceOptions] = None,
               entity_type_id: Optional[str] = None,
               featurestore_id: Optional[str] = None,
               description: Optional[str] = None,
               etag: Optional[str] = None,
               labels: Optional[Mapping[str, str]] = None,
               location: Optional[str] = None,
               monitoring_config: Optional[GoogleCloudAiplatformV1FeaturestoreMonitoringConfigArgs] = None,
               name: Optional[str] = None,
               offline_storage_ttl_days: Optional[int] = None,
               project: Optional[str] = None)
    func NewEntityType(ctx *Context, name string, args EntityTypeArgs, opts ...ResourceOption) (*EntityType, error)
    public EntityType(string name, EntityTypeArgs args, CustomResourceOptions? opts = null)
    public EntityType(String name, EntityTypeArgs args)
public EntityType(String name, EntityTypeArgs args, CustomResourceOptions options)

    type: google-native:aiplatform/v1:EntityType
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.

    Parameters

    name string
    The unique name of the resource.
    args EntityTypeArgs
    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 EntityTypeArgs
    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 EntityTypeArgs
    The arguments to resource properties.
    opts ResourceOption
    Bag of options to control resource's behavior.
    name string
    The unique name of the resource.
    args EntityTypeArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    name String
    The unique name of the resource.
    args EntityTypeArgs
    The arguments to resource properties.
    options CustomResourceOptions
    Bag of options to control resource's behavior.

    Constructor example

    The following reference example uses placeholder values for all input properties.

    var entityTypeResource = new GoogleNative.Aiplatform.V1.EntityType("entityTypeResource", new()
{
    EntityTypeId = "string",
    FeaturestoreId = "string",
    Description = "string",
    Etag = "string",
    Labels = 
    {
        { "string", "string" },
    },
    Location = "string",
    MonitoringConfig = new GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigArgs
    {
        CategoricalThresholdConfig = new GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigArgs
        {
            Value = 0,
        },
        ImportFeaturesAnalysis = new GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisArgs
        {
            AnomalyDetectionBaseline = GoogleNative.Aiplatform.V1.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline.BaselineUnspecified,
            State = GoogleNative.Aiplatform.V1.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState.StateUnspecified,
        },
        NumericalThresholdConfig = new GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigArgs
        {
            Value = 0,
        },
        SnapshotAnalysis = new GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisArgs
        {
            Disabled = false,
            MonitoringIntervalDays = 0,
            StalenessDays = 0,
        },
    },
    Name = "string",
    OfflineStorageTtlDays = 0,
    Project = "string",
});

    example, err := aiplatform.NewEntityType(ctx, "entityTypeResource", &aiplatform.EntityTypeArgs{
	EntityTypeId:   pulumi.String("string"),
	FeaturestoreId: pulumi.String("string"),
	Description:    pulumi.String("string"),
	Etag:           pulumi.String("string"),
	Labels: pulumi.StringMap{
		"string": pulumi.String("string"),
	},
	Location: pulumi.String("string"),
	MonitoringConfig: &aiplatform.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigArgs{
		CategoricalThresholdConfig: &aiplatform.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigArgs{
			Value: pulumi.Float64(0),
		},
		ImportFeaturesAnalysis: &aiplatform.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisArgs{
			AnomalyDetectionBaseline: aiplatform.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineBaselineUnspecified,
			State:                    aiplatform.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateStateUnspecified,
		},
		NumericalThresholdConfig: &aiplatform.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigArgs{
			Value: pulumi.Float64(0),
		},
		SnapshotAnalysis: &aiplatform.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisArgs{
			Disabled:               pulumi.Bool(false),
			MonitoringIntervalDays: pulumi.Int(0),
			StalenessDays:          pulumi.Int(0),
		},
	},
	Name:                  pulumi.String("string"),
	OfflineStorageTtlDays: pulumi.Int(0),
	Project:               pulumi.String("string"),
})

    var entityTypeResource = new EntityType("entityTypeResource", EntityTypeArgs.builder()
    .entityTypeId("string")
    .featurestoreId("string")
    .description("string")
    .etag("string")
    .labels(Map.of("string", "string"))
    .location("string")
    .monitoringConfig(GoogleCloudAiplatformV1FeaturestoreMonitoringConfigArgs.builder()
        .categoricalThresholdConfig(GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigArgs.builder()
            .value(0)
            .build())
        .importFeaturesAnalysis(GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisArgs.builder()
            .anomalyDetectionBaseline("BASELINE_UNSPECIFIED")
            .state("STATE_UNSPECIFIED")
            .build())
        .numericalThresholdConfig(GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigArgs.builder()
            .value(0)
            .build())
        .snapshotAnalysis(GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisArgs.builder()
            .disabled(false)
            .monitoringIntervalDays(0)
            .stalenessDays(0)
            .build())
        .build())
    .name("string")
    .offlineStorageTtlDays(0)
    .project("string")
    .build());

    entity_type_resource = google_native.aiplatform.v1.EntityType("entityTypeResource",
    entity_type_id="string",
    featurestore_id="string",
    description="string",
    etag="string",
    labels={
        "string": "string",
    },
    location="string",
    monitoring_config=google_native.aiplatform.v1.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigArgs(
        categorical_threshold_config=google_native.aiplatform.v1.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigArgs(
            value=0,
        ),
        import_features_analysis=google_native.aiplatform.v1.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisArgs(
            anomaly_detection_baseline=google_native.aiplatform.v1.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline.BASELINE_UNSPECIFIED,
            state=google_native.aiplatform.v1.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState.STATE_UNSPECIFIED,
        ),
        numerical_threshold_config=google_native.aiplatform.v1.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigArgs(
            value=0,
        ),
        snapshot_analysis=google_native.aiplatform.v1.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisArgs(
            disabled=False,
            monitoring_interval_days=0,
            staleness_days=0,
        ),
    ),
    name="string",
    offline_storage_ttl_days=0,
    project="string")

    const entityTypeResource = new google_native.aiplatform.v1.EntityType("entityTypeResource", {
    entityTypeId: "string",
    featurestoreId: "string",
    description: "string",
    etag: "string",
    labels: {
        string: "string",
    },
    location: "string",
    monitoringConfig: {
        categoricalThresholdConfig: {
            value: 0,
        },
        importFeaturesAnalysis: {
            anomalyDetectionBaseline: google_native.aiplatform.v1.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline.BaselineUnspecified,
            state: google_native.aiplatform.v1.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState.StateUnspecified,
        },
        numericalThresholdConfig: {
            value: 0,
        },
        snapshotAnalysis: {
            disabled: false,
            monitoringIntervalDays: 0,
            stalenessDays: 0,
        },
    },
    name: "string",
    offlineStorageTtlDays: 0,
    project: "string",
});

    type: google-native:aiplatform/v1:EntityType
properties:
    description: string
    entityTypeId: string
    etag: string
    featurestoreId: string
    labels:
        string: string
    location: string
    monitoringConfig:
        categoricalThresholdConfig:
            value: 0
        importFeaturesAnalysis:
            anomalyDetectionBaseline: BASELINE_UNSPECIFIED
            state: STATE_UNSPECIFIED
        numericalThresholdConfig:
            value: 0
        snapshotAnalysis:
            disabled: false
            monitoringIntervalDays: 0
            stalenessDays: 0
    name: string
    offlineStorageTtlDays: 0
    project: string

    EntityType 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 EntityType resource accepts the following input properties:

    EntityTypeId string
    Required. The ID to use for the EntityType, which will become the final component of the EntityType's resource name. This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number. The value must be unique within a featurestore.
    FeaturestoreId string
    Description string
    Optional. Description of the EntityType.
    Etag string
    Optional. Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
    Labels Dictionary<string, string>
    Optional. The labels with user-defined metadata to organize your EntityTypes. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one EntityType (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
    Location string
    MonitoringConfig Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1FeaturestoreMonitoringConfig
    Optional. The default monitoring configuration for all Features with value type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 under this EntityType. If this is populated with [FeaturestoreMonitoringConfig.monitoring_interval] specified, snapshot analysis monitoring is enabled. Otherwise, snapshot analysis monitoring is disabled.
    Name string
    Immutable. Name of the EntityType. Format: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type} The last part entity_type is assigned by the client. The entity_type can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z and underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given a featurestore.
    OfflineStorageTtlDays int
    Optional. Config for data retention policy in offline storage. TTL in days for feature values that will be stored in offline storage. The Feature Store offline storage periodically removes obsolete feature values older than offline_storage_ttl_days since the feature generation time. If unset (or explicitly set to 0), default to 4000 days TTL.
    Project string
    EntityTypeId string
    Required. The ID to use for the EntityType, which will become the final component of the EntityType's resource name. This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number. The value must be unique within a featurestore.
    FeaturestoreId string
    Description string
    Optional. Description of the EntityType.
    Etag string
    Optional. Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
    Labels map[string]string
    Optional. The labels with user-defined metadata to organize your EntityTypes. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one EntityType (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
    Location string
    MonitoringConfig GoogleCloudAiplatformV1FeaturestoreMonitoringConfigArgs
    Optional. The default monitoring configuration for all Features with value type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 under this EntityType. If this is populated with [FeaturestoreMonitoringConfig.monitoring_interval] specified, snapshot analysis monitoring is enabled. Otherwise, snapshot analysis monitoring is disabled.
    Name string
    Immutable. Name of the EntityType. Format: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type} The last part entity_type is assigned by the client. The entity_type can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z and underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given a featurestore.
    OfflineStorageTtlDays int
    Optional. Config for data retention policy in offline storage. TTL in days for feature values that will be stored in offline storage. The Feature Store offline storage periodically removes obsolete feature values older than offline_storage_ttl_days since the feature generation time. If unset (or explicitly set to 0), default to 4000 days TTL.
    Project string
    entityTypeId String
    Required. The ID to use for the EntityType, which will become the final component of the EntityType's resource name. This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number. The value must be unique within a featurestore.
    featurestoreId String
    description String
    Optional. Description of the EntityType.
    etag String
    Optional. Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
    labels Map<String,String>
    Optional. The labels with user-defined metadata to organize your EntityTypes. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one EntityType (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
    location String
    monitoringConfig GoogleCloudAiplatformV1FeaturestoreMonitoringConfig
    Optional. The default monitoring configuration for all Features with value type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 under this EntityType. If this is populated with [FeaturestoreMonitoringConfig.monitoring_interval] specified, snapshot analysis monitoring is enabled. Otherwise, snapshot analysis monitoring is disabled.
    name String
    Immutable. Name of the EntityType. Format: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type} The last part entity_type is assigned by the client. The entity_type can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z and underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given a featurestore.
    offlineStorageTtlDays Integer
    Optional. Config for data retention policy in offline storage. TTL in days for feature values that will be stored in offline storage. The Feature Store offline storage periodically removes obsolete feature values older than offline_storage_ttl_days since the feature generation time. If unset (or explicitly set to 0), default to 4000 days TTL.
    project String
    entityTypeId string
    Required. The ID to use for the EntityType, which will become the final component of the EntityType's resource name. This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number. The value must be unique within a featurestore.
    featurestoreId string
    description string
    Optional. Description of the EntityType.
    etag string
    Optional. Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
    labels {[key: string]: string}
    Optional. The labels with user-defined metadata to organize your EntityTypes. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one EntityType (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
    location string
    monitoringConfig GoogleCloudAiplatformV1FeaturestoreMonitoringConfig
    Optional. The default monitoring configuration for all Features with value type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 under this EntityType. If this is populated with [FeaturestoreMonitoringConfig.monitoring_interval] specified, snapshot analysis monitoring is enabled. Otherwise, snapshot analysis monitoring is disabled.
    name string
    Immutable. Name of the EntityType. Format: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type} The last part entity_type is assigned by the client. The entity_type can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z and underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given a featurestore.
    offlineStorageTtlDays number
    Optional. Config for data retention policy in offline storage. TTL in days for feature values that will be stored in offline storage. The Feature Store offline storage periodically removes obsolete feature values older than offline_storage_ttl_days since the feature generation time. If unset (or explicitly set to 0), default to 4000 days TTL.
    project string
    entity_type_id str
    Required. The ID to use for the EntityType, which will become the final component of the EntityType's resource name. This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number. The value must be unique within a featurestore.
    featurestore_id str
    description str
    Optional. Description of the EntityType.
    etag str
    Optional. Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
    labels Mapping[str, str]
    Optional. The labels with user-defined metadata to organize your EntityTypes. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one EntityType (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
    location str
    monitoring_config GoogleCloudAiplatformV1FeaturestoreMonitoringConfigArgs
    Optional. The default monitoring configuration for all Features with value type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 under this EntityType. If this is populated with [FeaturestoreMonitoringConfig.monitoring_interval] specified, snapshot analysis monitoring is enabled. Otherwise, snapshot analysis monitoring is disabled.
    name str
    Immutable. Name of the EntityType. Format: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type} The last part entity_type is assigned by the client. The entity_type can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z and underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given a featurestore.
    offline_storage_ttl_days int
    Optional. Config for data retention policy in offline storage. TTL in days for feature values that will be stored in offline storage. The Feature Store offline storage periodically removes obsolete feature values older than offline_storage_ttl_days since the feature generation time. If unset (or explicitly set to 0), default to 4000 days TTL.
    project str
    entityTypeId String
    Required. The ID to use for the EntityType, which will become the final component of the EntityType's resource name. This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number. The value must be unique within a featurestore.
    featurestoreId String
    description String
    Optional. Description of the EntityType.
    etag String
    Optional. Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
    labels Map<String>
    Optional. The labels with user-defined metadata to organize your EntityTypes. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one EntityType (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
    location String
    monitoringConfig Property Map
    Optional. The default monitoring configuration for all Features with value type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 under this EntityType. If this is populated with [FeaturestoreMonitoringConfig.monitoring_interval] specified, snapshot analysis monitoring is enabled. Otherwise, snapshot analysis monitoring is disabled.
    name String
    Immutable. Name of the EntityType. Format: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type} The last part entity_type is assigned by the client. The entity_type can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z and underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given a featurestore.
    offlineStorageTtlDays Number
    Optional. Config for data retention policy in offline storage. TTL in days for feature values that will be stored in offline storage. The Feature Store offline storage periodically removes obsolete feature values older than offline_storage_ttl_days since the feature generation time. If unset (or explicitly set to 0), default to 4000 days TTL.
    project String

    Outputs

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

    CreateTime string
    Timestamp when this EntityType was created.
    Id string
    The provider-assigned unique ID for this managed resource.
    UpdateTime string
    Timestamp when this EntityType was most recently updated.
    CreateTime string
    Timestamp when this EntityType was created.
    Id string
    The provider-assigned unique ID for this managed resource.
    UpdateTime string
    Timestamp when this EntityType was most recently updated.
    createTime String
    Timestamp when this EntityType was created.
    id String
    The provider-assigned unique ID for this managed resource.
    updateTime String
    Timestamp when this EntityType was most recently updated.
    createTime string
    Timestamp when this EntityType was created.
    id string
    The provider-assigned unique ID for this managed resource.
    updateTime string
    Timestamp when this EntityType was most recently updated.
    create_time str
    Timestamp when this EntityType was created.
    id str
    The provider-assigned unique ID for this managed resource.
    update_time str
    Timestamp when this EntityType was most recently updated.
    createTime String
    Timestamp when this EntityType was created.
    id String
    The provider-assigned unique ID for this managed resource.
    updateTime String
    Timestamp when this EntityType was most recently updated.

    Supporting Types

    GoogleCloudAiplatformV1FeaturestoreMonitoringConfig, GoogleCloudAiplatformV1FeaturestoreMonitoringConfigArgs

    CategoricalThresholdConfig Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfig
    Threshold for categorical features of anomaly detection. This is shared by all types of Featurestore Monitoring for categorical features (i.e. Features with type (Feature.ValueType) BOOL or STRING).
    ImportFeaturesAnalysis Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysis
    The config for ImportFeatures Analysis Based Feature Monitoring.
    NumericalThresholdConfig Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfig
    Threshold for numerical features of anomaly detection. This is shared by all objectives of Featurestore Monitoring for numerical features (i.e. Features with type (Feature.ValueType) DOUBLE or INT64).
    SnapshotAnalysis Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysis
    The config for Snapshot Analysis Based Feature Monitoring.
    CategoricalThresholdConfig GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfig
    Threshold for categorical features of anomaly detection. This is shared by all types of Featurestore Monitoring for categorical features (i.e. Features with type (Feature.ValueType) BOOL or STRING).
    ImportFeaturesAnalysis GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysis
    The config for ImportFeatures Analysis Based Feature Monitoring.
    NumericalThresholdConfig GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfig
    Threshold for numerical features of anomaly detection. This is shared by all objectives of Featurestore Monitoring for numerical features (i.e. Features with type (Feature.ValueType) DOUBLE or INT64).
    SnapshotAnalysis GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysis
    The config for Snapshot Analysis Based Feature Monitoring.
    categoricalThresholdConfig GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfig
    Threshold for categorical features of anomaly detection. This is shared by all types of Featurestore Monitoring for categorical features (i.e. Features with type (Feature.ValueType) BOOL or STRING).
    importFeaturesAnalysis GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysis
    The config for ImportFeatures Analysis Based Feature Monitoring.
    numericalThresholdConfig GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfig
    Threshold for numerical features of anomaly detection. This is shared by all objectives of Featurestore Monitoring for numerical features (i.e. Features with type (Feature.ValueType) DOUBLE or INT64).
    snapshotAnalysis GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysis
    The config for Snapshot Analysis Based Feature Monitoring.
    categoricalThresholdConfig GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfig
    Threshold for categorical features of anomaly detection. This is shared by all types of Featurestore Monitoring for categorical features (i.e. Features with type (Feature.ValueType) BOOL or STRING).
    importFeaturesAnalysis GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysis
    The config for ImportFeatures Analysis Based Feature Monitoring.
    numericalThresholdConfig GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfig
    Threshold for numerical features of anomaly detection. This is shared by all objectives of Featurestore Monitoring for numerical features (i.e. Features with type (Feature.ValueType) DOUBLE or INT64).
    snapshotAnalysis GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysis
    The config for Snapshot Analysis Based Feature Monitoring.
    categorical_threshold_config GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfig
    Threshold for categorical features of anomaly detection. This is shared by all types of Featurestore Monitoring for categorical features (i.e. Features with type (Feature.ValueType) BOOL or STRING).
    import_features_analysis GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysis
    The config for ImportFeatures Analysis Based Feature Monitoring.
    numerical_threshold_config GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfig
    Threshold for numerical features of anomaly detection. This is shared by all objectives of Featurestore Monitoring for numerical features (i.e. Features with type (Feature.ValueType) DOUBLE or INT64).
    snapshot_analysis GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysis
    The config for Snapshot Analysis Based Feature Monitoring.
    categoricalThresholdConfig Property Map
    Threshold for categorical features of anomaly detection. This is shared by all types of Featurestore Monitoring for categorical features (i.e. Features with type (Feature.ValueType) BOOL or STRING).
    importFeaturesAnalysis Property Map
    The config for ImportFeatures Analysis Based Feature Monitoring.
    numericalThresholdConfig Property Map
    Threshold for numerical features of anomaly detection. This is shared by all objectives of Featurestore Monitoring for numerical features (i.e. Features with type (Feature.ValueType) DOUBLE or INT64).
    snapshotAnalysis Property Map
    The config for Snapshot Analysis Based Feature Monitoring.

    GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysis, GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisArgs

    AnomalyDetectionBaseline Pulumi.GoogleNative.Aiplatform.V1.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline
    The baseline used to do anomaly detection for the statistics generated by import features analysis.
    State Pulumi.GoogleNative.Aiplatform.V1.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState
    Whether to enable / disable / inherite default hebavior for import features analysis.
    AnomalyDetectionBaseline GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline
    The baseline used to do anomaly detection for the statistics generated by import features analysis.
    State GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState
    Whether to enable / disable / inherite default hebavior for import features analysis.
    anomalyDetectionBaseline GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline
    The baseline used to do anomaly detection for the statistics generated by import features analysis.
    state GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState
    Whether to enable / disable / inherite default hebavior for import features analysis.
    anomalyDetectionBaseline GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline
    The baseline used to do anomaly detection for the statistics generated by import features analysis.
    state GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState
    Whether to enable / disable / inherite default hebavior for import features analysis.
    anomaly_detection_baseline GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline
    The baseline used to do anomaly detection for the statistics generated by import features analysis.
    state GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState
    Whether to enable / disable / inherite default hebavior for import features analysis.
    anomalyDetectionBaseline "BASELINE_UNSPECIFIED" | "LATEST_STATS" | "MOST_RECENT_SNAPSHOT_STATS" | "PREVIOUS_IMPORT_FEATURES_STATS"
    The baseline used to do anomaly detection for the statistics generated by import features analysis.
    state "STATE_UNSPECIFIED" | "DEFAULT" | "ENABLED" | "DISABLED"
    Whether to enable / disable / inherite default hebavior for import features analysis.

    GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline, GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineArgs

    BaselineUnspecified
    BASELINE_UNSPECIFIEDShould not be used.
    LatestStats
    LATEST_STATSChoose the later one statistics generated by either most recent snapshot analysis or previous import features analysis. If non of them exists, skip anomaly detection and only generate a statistics.
    MostRecentSnapshotStats
    MOST_RECENT_SNAPSHOT_STATSUse the statistics generated by the most recent snapshot analysis if exists.
    PreviousImportFeaturesStats
    PREVIOUS_IMPORT_FEATURES_STATSUse the statistics generated by the previous import features analysis if exists.
    GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineBaselineUnspecified
    BASELINE_UNSPECIFIEDShould not be used.
    GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineLatestStats
    LATEST_STATSChoose the later one statistics generated by either most recent snapshot analysis or previous import features analysis. If non of them exists, skip anomaly detection and only generate a statistics.
    GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineMostRecentSnapshotStats
    MOST_RECENT_SNAPSHOT_STATSUse the statistics generated by the most recent snapshot analysis if exists.
    GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePreviousImportFeaturesStats
    PREVIOUS_IMPORT_FEATURES_STATSUse the statistics generated by the previous import features analysis if exists.
    BaselineUnspecified
    BASELINE_UNSPECIFIEDShould not be used.
    LatestStats
    LATEST_STATSChoose the later one statistics generated by either most recent snapshot analysis or previous import features analysis. If non of them exists, skip anomaly detection and only generate a statistics.
    MostRecentSnapshotStats
    MOST_RECENT_SNAPSHOT_STATSUse the statistics generated by the most recent snapshot analysis if exists.
    PreviousImportFeaturesStats
    PREVIOUS_IMPORT_FEATURES_STATSUse the statistics generated by the previous import features analysis if exists.
    BaselineUnspecified
    BASELINE_UNSPECIFIEDShould not be used.
    LatestStats
    LATEST_STATSChoose the later one statistics generated by either most recent snapshot analysis or previous import features analysis. If non of them exists, skip anomaly detection and only generate a statistics.
    MostRecentSnapshotStats
    MOST_RECENT_SNAPSHOT_STATSUse the statistics generated by the most recent snapshot analysis if exists.
    PreviousImportFeaturesStats
    PREVIOUS_IMPORT_FEATURES_STATSUse the statistics generated by the previous import features analysis if exists.
    BASELINE_UNSPECIFIED
    BASELINE_UNSPECIFIEDShould not be used.
    LATEST_STATS
    LATEST_STATSChoose the later one statistics generated by either most recent snapshot analysis or previous import features analysis. If non of them exists, skip anomaly detection and only generate a statistics.
    MOST_RECENT_SNAPSHOT_STATS
    MOST_RECENT_SNAPSHOT_STATSUse the statistics generated by the most recent snapshot analysis if exists.
    PREVIOUS_IMPORT_FEATURES_STATS
    PREVIOUS_IMPORT_FEATURES_STATSUse the statistics generated by the previous import features analysis if exists.
    "BASELINE_UNSPECIFIED"
    BASELINE_UNSPECIFIEDShould not be used.
    "LATEST_STATS"
    LATEST_STATSChoose the later one statistics generated by either most recent snapshot analysis or previous import features analysis. If non of them exists, skip anomaly detection and only generate a statistics.
    "MOST_RECENT_SNAPSHOT_STATS"
    MOST_RECENT_SNAPSHOT_STATSUse the statistics generated by the most recent snapshot analysis if exists.
    "PREVIOUS_IMPORT_FEATURES_STATS"
    PREVIOUS_IMPORT_FEATURES_STATSUse the statistics generated by the previous import features analysis if exists.

    GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisResponse, GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisResponseArgs

    AnomalyDetectionBaseline string
    The baseline used to do anomaly detection for the statistics generated by import features analysis.
    State string
    Whether to enable / disable / inherite default hebavior for import features analysis.
    AnomalyDetectionBaseline string
    The baseline used to do anomaly detection for the statistics generated by import features analysis.
    State string
    Whether to enable / disable / inherite default hebavior for import features analysis.
    anomalyDetectionBaseline String
    The baseline used to do anomaly detection for the statistics generated by import features analysis.
    state String
    Whether to enable / disable / inherite default hebavior for import features analysis.
    anomalyDetectionBaseline string
    The baseline used to do anomaly detection for the statistics generated by import features analysis.
    state string
    Whether to enable / disable / inherite default hebavior for import features analysis.
    anomaly_detection_baseline str
    The baseline used to do anomaly detection for the statistics generated by import features analysis.
    state str
    Whether to enable / disable / inherite default hebavior for import features analysis.
    anomalyDetectionBaseline String
    The baseline used to do anomaly detection for the statistics generated by import features analysis.
    state String
    Whether to enable / disable / inherite default hebavior for import features analysis.

    GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState, GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateArgs

    StateUnspecified
    STATE_UNSPECIFIEDShould not be used.
    Default
    DEFAULTThe default behavior of whether to enable the monitoring. EntityType-level config: disabled. Feature-level config: inherited from the configuration of EntityType this Feature belongs to.
    Enabled
    ENABLEDExplicitly enables import features analysis. EntityType-level config: by default enables import features analysis for all Features under it. Feature-level config: enables import features analysis regardless of the EntityType-level config.
    Disabled
    DISABLEDExplicitly disables import features analysis. EntityType-level config: by default disables import features analysis for all Features under it. Feature-level config: disables import features analysis regardless of the EntityType-level config.
    GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateStateUnspecified
    STATE_UNSPECIFIEDShould not be used.
    GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateDefault
    DEFAULTThe default behavior of whether to enable the monitoring. EntityType-level config: disabled. Feature-level config: inherited from the configuration of EntityType this Feature belongs to.
    GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateEnabled
    ENABLEDExplicitly enables import features analysis. EntityType-level config: by default enables import features analysis for all Features under it. Feature-level config: enables import features analysis regardless of the EntityType-level config.
    GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateDisabled
    DISABLEDExplicitly disables import features analysis. EntityType-level config: by default disables import features analysis for all Features under it. Feature-level config: disables import features analysis regardless of the EntityType-level config.
    StateUnspecified
    STATE_UNSPECIFIEDShould not be used.
    Default
    DEFAULTThe default behavior of whether to enable the monitoring. EntityType-level config: disabled. Feature-level config: inherited from the configuration of EntityType this Feature belongs to.
    Enabled
    ENABLEDExplicitly enables import features analysis. EntityType-level config: by default enables import features analysis for all Features under it. Feature-level config: enables import features analysis regardless of the EntityType-level config.
    Disabled
    DISABLEDExplicitly disables import features analysis. EntityType-level config: by default disables import features analysis for all Features under it. Feature-level config: disables import features analysis regardless of the EntityType-level config.
    StateUnspecified
    STATE_UNSPECIFIEDShould not be used.
    Default
    DEFAULTThe default behavior of whether to enable the monitoring. EntityType-level config: disabled. Feature-level config: inherited from the configuration of EntityType this Feature belongs to.
    Enabled
    ENABLEDExplicitly enables import features analysis. EntityType-level config: by default enables import features analysis for all Features under it. Feature-level config: enables import features analysis regardless of the EntityType-level config.
    Disabled
    DISABLEDExplicitly disables import features analysis. EntityType-level config: by default disables import features analysis for all Features under it. Feature-level config: disables import features analysis regardless of the EntityType-level config.
    STATE_UNSPECIFIED
    STATE_UNSPECIFIEDShould not be used.
    DEFAULT
    DEFAULTThe default behavior of whether to enable the monitoring. EntityType-level config: disabled. Feature-level config: inherited from the configuration of EntityType this Feature belongs to.
    ENABLED
    ENABLEDExplicitly enables import features analysis. EntityType-level config: by default enables import features analysis for all Features under it. Feature-level config: enables import features analysis regardless of the EntityType-level config.
    DISABLED
    DISABLEDExplicitly disables import features analysis. EntityType-level config: by default disables import features analysis for all Features under it. Feature-level config: disables import features analysis regardless of the EntityType-level config.
    "STATE_UNSPECIFIED"
    STATE_UNSPECIFIEDShould not be used.
    "DEFAULT"
    DEFAULTThe default behavior of whether to enable the monitoring. EntityType-level config: disabled. Feature-level config: inherited from the configuration of EntityType this Feature belongs to.
    "ENABLED"
    ENABLEDExplicitly enables import features analysis. EntityType-level config: by default enables import features analysis for all Features under it. Feature-level config: enables import features analysis regardless of the EntityType-level config.
    "DISABLED"
    DISABLEDExplicitly disables import features analysis. EntityType-level config: by default disables import features analysis for all Features under it. Feature-level config: disables import features analysis regardless of the EntityType-level config.

    GoogleCloudAiplatformV1FeaturestoreMonitoringConfigResponse, GoogleCloudAiplatformV1FeaturestoreMonitoringConfigResponseArgs

    CategoricalThresholdConfig Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponse
    Threshold for categorical features of anomaly detection. This is shared by all types of Featurestore Monitoring for categorical features (i.e. Features with type (Feature.ValueType) BOOL or STRING).
    ImportFeaturesAnalysis Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisResponse
    The config for ImportFeatures Analysis Based Feature Monitoring.
    NumericalThresholdConfig Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponse
    Threshold for numerical features of anomaly detection. This is shared by all objectives of Featurestore Monitoring for numerical features (i.e. Features with type (Feature.ValueType) DOUBLE or INT64).
    SnapshotAnalysis Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisResponse
    The config for Snapshot Analysis Based Feature Monitoring.
    CategoricalThresholdConfig GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponse
    Threshold for categorical features of anomaly detection. This is shared by all types of Featurestore Monitoring for categorical features (i.e. Features with type (Feature.ValueType) BOOL or STRING).
    ImportFeaturesAnalysis GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisResponse
    The config for ImportFeatures Analysis Based Feature Monitoring.
    NumericalThresholdConfig GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponse
    Threshold for numerical features of anomaly detection. This is shared by all objectives of Featurestore Monitoring for numerical features (i.e. Features with type (Feature.ValueType) DOUBLE or INT64).
    SnapshotAnalysis GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisResponse
    The config for Snapshot Analysis Based Feature Monitoring.
    categoricalThresholdConfig GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponse
    Threshold for categorical features of anomaly detection. This is shared by all types of Featurestore Monitoring for categorical features (i.e. Features with type (Feature.ValueType) BOOL or STRING).
    importFeaturesAnalysis GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisResponse
    The config for ImportFeatures Analysis Based Feature Monitoring.
    numericalThresholdConfig GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponse
    Threshold for numerical features of anomaly detection. This is shared by all objectives of Featurestore Monitoring for numerical features (i.e. Features with type (Feature.ValueType) DOUBLE or INT64).
    snapshotAnalysis GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisResponse
    The config for Snapshot Analysis Based Feature Monitoring.
    categoricalThresholdConfig GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponse
    Threshold for categorical features of anomaly detection. This is shared by all types of Featurestore Monitoring for categorical features (i.e. Features with type (Feature.ValueType) BOOL or STRING).
    importFeaturesAnalysis GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisResponse
    The config for ImportFeatures Analysis Based Feature Monitoring.
    numericalThresholdConfig GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponse
    Threshold for numerical features of anomaly detection. This is shared by all objectives of Featurestore Monitoring for numerical features (i.e. Features with type (Feature.ValueType) DOUBLE or INT64).
    snapshotAnalysis GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisResponse
    The config for Snapshot Analysis Based Feature Monitoring.
    categorical_threshold_config GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponse
    Threshold for categorical features of anomaly detection. This is shared by all types of Featurestore Monitoring for categorical features (i.e. Features with type (Feature.ValueType) BOOL or STRING).
    import_features_analysis GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisResponse
    The config for ImportFeatures Analysis Based Feature Monitoring.
    numerical_threshold_config GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponse
    Threshold for numerical features of anomaly detection. This is shared by all objectives of Featurestore Monitoring for numerical features (i.e. Features with type (Feature.ValueType) DOUBLE or INT64).
    snapshot_analysis GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisResponse
    The config for Snapshot Analysis Based Feature Monitoring.
    categoricalThresholdConfig Property Map
    Threshold for categorical features of anomaly detection. This is shared by all types of Featurestore Monitoring for categorical features (i.e. Features with type (Feature.ValueType) BOOL or STRING).
    importFeaturesAnalysis Property Map
    The config for ImportFeatures Analysis Based Feature Monitoring.
    numericalThresholdConfig Property Map
    Threshold for numerical features of anomaly detection. This is shared by all objectives of Featurestore Monitoring for numerical features (i.e. Features with type (Feature.ValueType) DOUBLE or INT64).
    snapshotAnalysis Property Map
    The config for Snapshot Analysis Based Feature Monitoring.

    GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysis, GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisArgs

    Disabled bool
    The monitoring schedule for snapshot analysis. For EntityType-level config: unset / disabled = true indicates disabled by default for Features under it; otherwise by default enable snapshot analysis monitoring with monitoring_interval for Features under it. Feature-level config: disabled = true indicates disabled regardless of the EntityType-level config; unset monitoring_interval indicates going with EntityType-level config; otherwise run snapshot analysis monitoring with monitoring_interval regardless of the EntityType-level config. Explicitly Disable the snapshot analysis based monitoring.
    MonitoringIntervalDays int
    Configuration of the snapshot analysis based monitoring pipeline running interval. The value indicates number of days.
    StalenessDays int
    Customized export features time window for snapshot analysis. Unit is one day. Default value is 3 weeks. Minimum value is 1 day. Maximum value is 4000 days.
    Disabled bool
    The monitoring schedule for snapshot analysis. For EntityType-level config: unset / disabled = true indicates disabled by default for Features under it; otherwise by default enable snapshot analysis monitoring with monitoring_interval for Features under it. Feature-level config: disabled = true indicates disabled regardless of the EntityType-level config; unset monitoring_interval indicates going with EntityType-level config; otherwise run snapshot analysis monitoring with monitoring_interval regardless of the EntityType-level config. Explicitly Disable the snapshot analysis based monitoring.
    MonitoringIntervalDays int
    Configuration of the snapshot analysis based monitoring pipeline running interval. The value indicates number of days.
    StalenessDays int
    Customized export features time window for snapshot analysis. Unit is one day. Default value is 3 weeks. Minimum value is 1 day. Maximum value is 4000 days.
    disabled Boolean
    The monitoring schedule for snapshot analysis. For EntityType-level config: unset / disabled = true indicates disabled by default for Features under it; otherwise by default enable snapshot analysis monitoring with monitoring_interval for Features under it. Feature-level config: disabled = true indicates disabled regardless of the EntityType-level config; unset monitoring_interval indicates going with EntityType-level config; otherwise run snapshot analysis monitoring with monitoring_interval regardless of the EntityType-level config. Explicitly Disable the snapshot analysis based monitoring.
    monitoringIntervalDays Integer
    Configuration of the snapshot analysis based monitoring pipeline running interval. The value indicates number of days.
    stalenessDays Integer
    Customized export features time window for snapshot analysis. Unit is one day. Default value is 3 weeks. Minimum value is 1 day. Maximum value is 4000 days.
    disabled boolean
    The monitoring schedule for snapshot analysis. For EntityType-level config: unset / disabled = true indicates disabled by default for Features under it; otherwise by default enable snapshot analysis monitoring with monitoring_interval for Features under it. Feature-level config: disabled = true indicates disabled regardless of the EntityType-level config; unset monitoring_interval indicates going with EntityType-level config; otherwise run snapshot analysis monitoring with monitoring_interval regardless of the EntityType-level config. Explicitly Disable the snapshot analysis based monitoring.
    monitoringIntervalDays number
    Configuration of the snapshot analysis based monitoring pipeline running interval. The value indicates number of days.
    stalenessDays number
    Customized export features time window for snapshot analysis. Unit is one day. Default value is 3 weeks. Minimum value is 1 day. Maximum value is 4000 days.
    disabled bool
    The monitoring schedule for snapshot analysis. For EntityType-level config: unset / disabled = true indicates disabled by default for Features under it; otherwise by default enable snapshot analysis monitoring with monitoring_interval for Features under it. Feature-level config: disabled = true indicates disabled regardless of the EntityType-level config; unset monitoring_interval indicates going with EntityType-level config; otherwise run snapshot analysis monitoring with monitoring_interval regardless of the EntityType-level config. Explicitly Disable the snapshot analysis based monitoring.
    monitoring_interval_days int
    Configuration of the snapshot analysis based monitoring pipeline running interval. The value indicates number of days.
    staleness_days int
    Customized export features time window for snapshot analysis. Unit is one day. Default value is 3 weeks. Minimum value is 1 day. Maximum value is 4000 days.
    disabled Boolean
    The monitoring schedule for snapshot analysis. For EntityType-level config: unset / disabled = true indicates disabled by default for Features under it; otherwise by default enable snapshot analysis monitoring with monitoring_interval for Features under it. Feature-level config: disabled = true indicates disabled regardless of the EntityType-level config; unset monitoring_interval indicates going with EntityType-level config; otherwise run snapshot analysis monitoring with monitoring_interval regardless of the EntityType-level config. Explicitly Disable the snapshot analysis based monitoring.
    monitoringIntervalDays Number
    Configuration of the snapshot analysis based monitoring pipeline running interval. The value indicates number of days.
    stalenessDays Number
    Customized export features time window for snapshot analysis. Unit is one day. Default value is 3 weeks. Minimum value is 1 day. Maximum value is 4000 days.

    GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisResponse, GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisResponseArgs

    Disabled bool
    The monitoring schedule for snapshot analysis. For EntityType-level config: unset / disabled = true indicates disabled by default for Features under it; otherwise by default enable snapshot analysis monitoring with monitoring_interval for Features under it. Feature-level config: disabled = true indicates disabled regardless of the EntityType-level config; unset monitoring_interval indicates going with EntityType-level config; otherwise run snapshot analysis monitoring with monitoring_interval regardless of the EntityType-level config. Explicitly Disable the snapshot analysis based monitoring.
    MonitoringIntervalDays int
    Configuration of the snapshot analysis based monitoring pipeline running interval. The value indicates number of days.
    StalenessDays int
    Customized export features time window for snapshot analysis. Unit is one day. Default value is 3 weeks. Minimum value is 1 day. Maximum value is 4000 days.
    Disabled bool
    The monitoring schedule for snapshot analysis. For EntityType-level config: unset / disabled = true indicates disabled by default for Features under it; otherwise by default enable snapshot analysis monitoring with monitoring_interval for Features under it. Feature-level config: disabled = true indicates disabled regardless of the EntityType-level config; unset monitoring_interval indicates going with EntityType-level config; otherwise run snapshot analysis monitoring with monitoring_interval regardless of the EntityType-level config. Explicitly Disable the snapshot analysis based monitoring.
    MonitoringIntervalDays int
    Configuration of the snapshot analysis based monitoring pipeline running interval. The value indicates number of days.
    StalenessDays int
    Customized export features time window for snapshot analysis. Unit is one day. Default value is 3 weeks. Minimum value is 1 day. Maximum value is 4000 days.
    disabled Boolean
    The monitoring schedule for snapshot analysis. For EntityType-level config: unset / disabled = true indicates disabled by default for Features under it; otherwise by default enable snapshot analysis monitoring with monitoring_interval for Features under it. Feature-level config: disabled = true indicates disabled regardless of the EntityType-level config; unset monitoring_interval indicates going with EntityType-level config; otherwise run snapshot analysis monitoring with monitoring_interval regardless of the EntityType-level config. Explicitly Disable the snapshot analysis based monitoring.
    monitoringIntervalDays Integer
    Configuration of the snapshot analysis based monitoring pipeline running interval. The value indicates number of days.
    stalenessDays Integer
    Customized export features time window for snapshot analysis. Unit is one day. Default value is 3 weeks. Minimum value is 1 day. Maximum value is 4000 days.
    disabled boolean
    The monitoring schedule for snapshot analysis. For EntityType-level config: unset / disabled = true indicates disabled by default for Features under it; otherwise by default enable snapshot analysis monitoring with monitoring_interval for Features under it. Feature-level config: disabled = true indicates disabled regardless of the EntityType-level config; unset monitoring_interval indicates going with EntityType-level config; otherwise run snapshot analysis monitoring with monitoring_interval regardless of the EntityType-level config. Explicitly Disable the snapshot analysis based monitoring.
    monitoringIntervalDays number
    Configuration of the snapshot analysis based monitoring pipeline running interval. The value indicates number of days.
    stalenessDays number
    Customized export features time window for snapshot analysis. Unit is one day. Default value is 3 weeks. Minimum value is 1 day. Maximum value is 4000 days.
    disabled bool
    The monitoring schedule for snapshot analysis. For EntityType-level config: unset / disabled = true indicates disabled by default for Features under it; otherwise by default enable snapshot analysis monitoring with monitoring_interval for Features under it. Feature-level config: disabled = true indicates disabled regardless of the EntityType-level config; unset monitoring_interval indicates going with EntityType-level config; otherwise run snapshot analysis monitoring with monitoring_interval regardless of the EntityType-level config. Explicitly Disable the snapshot analysis based monitoring.
    monitoring_interval_days int
    Configuration of the snapshot analysis based monitoring pipeline running interval. The value indicates number of days.
    staleness_days int
    Customized export features time window for snapshot analysis. Unit is one day. Default value is 3 weeks. Minimum value is 1 day. Maximum value is 4000 days.
    disabled Boolean
    The monitoring schedule for snapshot analysis. For EntityType-level config: unset / disabled = true indicates disabled by default for Features under it; otherwise by default enable snapshot analysis monitoring with monitoring_interval for Features under it. Feature-level config: disabled = true indicates disabled regardless of the EntityType-level config; unset monitoring_interval indicates going with EntityType-level config; otherwise run snapshot analysis monitoring with monitoring_interval regardless of the EntityType-level config. Explicitly Disable the snapshot analysis based monitoring.
    monitoringIntervalDays Number
    Configuration of the snapshot analysis based monitoring pipeline running interval. The value indicates number of days.
    stalenessDays Number
    Customized export features time window for snapshot analysis. Unit is one day. Default value is 3 weeks. Minimum value is 1 day. Maximum value is 4000 days.

    GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfig, GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigArgs

    Value double
    Specify a threshold value that can trigger the alert. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.
    Value float64
    Specify a threshold value that can trigger the alert. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.
    value Double
    Specify a threshold value that can trigger the alert. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.
    value number
    Specify a threshold value that can trigger the alert. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.
    value float
    Specify a threshold value that can trigger the alert. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.
    value Number
    Specify a threshold value that can trigger the alert. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.

    GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponse, GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponseArgs

    Value double
    Specify a threshold value that can trigger the alert. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.
    Value float64
    Specify a threshold value that can trigger the alert. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.
    value Double
    Specify a threshold value that can trigger the alert. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.
    value number
    Specify a threshold value that can trigger the alert. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.
    value float
    Specify a threshold value that can trigger the alert. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.
    value Number
    Specify a threshold value that can trigger the alert. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.

    Package Details

    Repository
    Google Cloud Native pulumi/pulumi-google-native
    License
    Apache-2.0
    google-native logo

    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
    pulumi/pulumi-google-native