Google Native

Pulumi Official
Package maintained by Pulumi
v0.22.0 published on Friday, Jul 29, 2022 by Pulumi

getAutoscaler

Returns the specified autoscaler resource. Gets a list of available autoscalers by making a list() request.

Using getAutoscaler

Two invocation forms are available. The direct form accepts plain arguments and either blocks until the result value is available, or returns a Promise-wrapped result. The output form accepts Input-wrapped arguments and returns an Output-wrapped result.

function getAutoscaler(args: GetAutoscalerArgs, opts?: InvokeOptions): Promise<GetAutoscalerResult>
function getAutoscalerOutput(args: GetAutoscalerOutputArgs, opts?: InvokeOptions): Output<GetAutoscalerResult>
def get_autoscaler(autoscaler: Optional[str] = None,
                   project: Optional[str] = None,
                   zone: Optional[str] = None,
                   opts: Optional[InvokeOptions] = None) -> GetAutoscalerResult
def get_autoscaler_output(autoscaler: Optional[pulumi.Input[str]] = None,
                   project: Optional[pulumi.Input[str]] = None,
                   zone: Optional[pulumi.Input[str]] = None,
                   opts: Optional[InvokeOptions] = None) -> Output[GetAutoscalerResult]
func LookupAutoscaler(ctx *Context, args *LookupAutoscalerArgs, opts ...InvokeOption) (*LookupAutoscalerResult, error)
func LookupAutoscalerOutput(ctx *Context, args *LookupAutoscalerOutputArgs, opts ...InvokeOption) LookupAutoscalerResultOutput

> Note: This function is named LookupAutoscaler in the Go SDK.

public static class GetAutoscaler 
{
    public static Task<GetAutoscalerResult> InvokeAsync(GetAutoscalerArgs args, InvokeOptions? opts = null)
    public static Output<GetAutoscalerResult> Invoke(GetAutoscalerInvokeArgs args, InvokeOptions? opts = null)
}
public static CompletableFuture<GetAutoscalerResult> getAutoscaler(GetAutoscalerArgs args, InvokeOptions options)
// Output-based functions aren't available in Java yet
Fn::Invoke:
  Function: google-native:compute/beta:getAutoscaler
  Arguments:
    # Arguments dictionary

The following arguments are supported:

Autoscaler string
Zone string
Project string
Autoscaler string
Zone string
Project string
autoscaler String
zone String
project String
autoscaler string
zone string
project string
autoscaler String
zone String
project String

getAutoscaler Result

The following output properties are available:

AutoscalingPolicy Pulumi.GoogleNative.Compute.Beta.Outputs.AutoscalingPolicyResponse

The configuration parameters for the autoscaling algorithm. You can define one or more signals for an autoscaler: cpuUtilization, customMetricUtilizations, and loadBalancingUtilization. If none of these are specified, the default will be to autoscale based on cpuUtilization to 0.6 or 60%.

CreationTimestamp string

Creation timestamp in RFC3339 text format.

Description string

An optional description of this resource. Provide this property when you create the resource.

Kind string

Type of the resource. Always compute#autoscaler for autoscalers.

Name string

Name of the resource. Provided by the client when the resource is created. The name must be 1-63 characters long, and comply with RFC1035. Specifically, the name must be 1-63 characters long and match the regular expression [a-z]([-a-z0-9]*[a-z0-9])? which means the first character must be a lowercase letter, and all following characters must be a dash, lowercase letter, or digit, except the last character, which cannot be a dash.

RecommendedSize int

Target recommended MIG size (number of instances) computed by autoscaler. Autoscaler calculates the recommended MIG size even when the autoscaling policy mode is different from ON. This field is empty when autoscaler is not connected to an existing managed instance group or autoscaler did not generate its prediction.

Region string

URL of the region where the instance group resides (for autoscalers living in regional scope).

ScalingScheduleStatus Dictionary<string, string>

Status information of existing scaling schedules.

SelfLink string

Server-defined URL for the resource.

Status string

The status of the autoscaler configuration. Current set of possible values: - PENDING: Autoscaler backend hasn't read new/updated configuration. - DELETING: Configuration is being deleted. - ACTIVE: Configuration is acknowledged to be effective. Some warnings might be present in the statusDetails field. - ERROR: Configuration has errors. Actionable for users. Details are present in the statusDetails field. New values might be added in the future.

StatusDetails List<Pulumi.GoogleNative.Compute.Beta.Outputs.AutoscalerStatusDetailsResponse>

Human-readable details about the current state of the autoscaler. Read the documentation for Commonly returned status messages for examples of status messages you might encounter.

Target string

URL of the managed instance group that this autoscaler will scale. This field is required when creating an autoscaler.

Zone string

URL of the zone where the instance group resides (for autoscalers living in zonal scope).

AutoscalingPolicy AutoscalingPolicyResponse

The configuration parameters for the autoscaling algorithm. You can define one or more signals for an autoscaler: cpuUtilization, customMetricUtilizations, and loadBalancingUtilization. If none of these are specified, the default will be to autoscale based on cpuUtilization to 0.6 or 60%.

CreationTimestamp string

Creation timestamp in RFC3339 text format.

Description string

An optional description of this resource. Provide this property when you create the resource.

Kind string

Type of the resource. Always compute#autoscaler for autoscalers.

Name string

Name of the resource. Provided by the client when the resource is created. The name must be 1-63 characters long, and comply with RFC1035. Specifically, the name must be 1-63 characters long and match the regular expression [a-z]([-a-z0-9]*[a-z0-9])? which means the first character must be a lowercase letter, and all following characters must be a dash, lowercase letter, or digit, except the last character, which cannot be a dash.

RecommendedSize int

Target recommended MIG size (number of instances) computed by autoscaler. Autoscaler calculates the recommended MIG size even when the autoscaling policy mode is different from ON. This field is empty when autoscaler is not connected to an existing managed instance group or autoscaler did not generate its prediction.

Region string

URL of the region where the instance group resides (for autoscalers living in regional scope).

ScalingScheduleStatus map[string]string

Status information of existing scaling schedules.

SelfLink string

Server-defined URL for the resource.

Status string

The status of the autoscaler configuration. Current set of possible values: - PENDING: Autoscaler backend hasn't read new/updated configuration. - DELETING: Configuration is being deleted. - ACTIVE: Configuration is acknowledged to be effective. Some warnings might be present in the statusDetails field. - ERROR: Configuration has errors. Actionable for users. Details are present in the statusDetails field. New values might be added in the future.

StatusDetails []AutoscalerStatusDetailsResponse

Human-readable details about the current state of the autoscaler. Read the documentation for Commonly returned status messages for examples of status messages you might encounter.

Target string

URL of the managed instance group that this autoscaler will scale. This field is required when creating an autoscaler.

Zone string

URL of the zone where the instance group resides (for autoscalers living in zonal scope).

autoscalingPolicy AutoscalingPolicyResponse

The configuration parameters for the autoscaling algorithm. You can define one or more signals for an autoscaler: cpuUtilization, customMetricUtilizations, and loadBalancingUtilization. If none of these are specified, the default will be to autoscale based on cpuUtilization to 0.6 or 60%.

creationTimestamp String

Creation timestamp in RFC3339 text format.

description String

An optional description of this resource. Provide this property when you create the resource.

kind String

Type of the resource. Always compute#autoscaler for autoscalers.

name String

Name of the resource. Provided by the client when the resource is created. The name must be 1-63 characters long, and comply with RFC1035. Specifically, the name must be 1-63 characters long and match the regular expression [a-z]([-a-z0-9]*[a-z0-9])? which means the first character must be a lowercase letter, and all following characters must be a dash, lowercase letter, or digit, except the last character, which cannot be a dash.

recommendedSize Integer

Target recommended MIG size (number of instances) computed by autoscaler. Autoscaler calculates the recommended MIG size even when the autoscaling policy mode is different from ON. This field is empty when autoscaler is not connected to an existing managed instance group or autoscaler did not generate its prediction.

region String

URL of the region where the instance group resides (for autoscalers living in regional scope).

scalingScheduleStatus Map<String,String>

Status information of existing scaling schedules.

selfLink String

Server-defined URL for the resource.

status String

The status of the autoscaler configuration. Current set of possible values: - PENDING: Autoscaler backend hasn't read new/updated configuration. - DELETING: Configuration is being deleted. - ACTIVE: Configuration is acknowledged to be effective. Some warnings might be present in the statusDetails field. - ERROR: Configuration has errors. Actionable for users. Details are present in the statusDetails field. New values might be added in the future.

statusDetails List<AutoscalerStatusDetailsResponse>

Human-readable details about the current state of the autoscaler. Read the documentation for Commonly returned status messages for examples of status messages you might encounter.

target String

URL of the managed instance group that this autoscaler will scale. This field is required when creating an autoscaler.

zone String

URL of the zone where the instance group resides (for autoscalers living in zonal scope).

autoscalingPolicy AutoscalingPolicyResponse

The configuration parameters for the autoscaling algorithm. You can define one or more signals for an autoscaler: cpuUtilization, customMetricUtilizations, and loadBalancingUtilization. If none of these are specified, the default will be to autoscale based on cpuUtilization to 0.6 or 60%.

creationTimestamp string

Creation timestamp in RFC3339 text format.

description string

An optional description of this resource. Provide this property when you create the resource.

kind string

Type of the resource. Always compute#autoscaler for autoscalers.

name string

Name of the resource. Provided by the client when the resource is created. The name must be 1-63 characters long, and comply with RFC1035. Specifically, the name must be 1-63 characters long and match the regular expression [a-z]([-a-z0-9]*[a-z0-9])? which means the first character must be a lowercase letter, and all following characters must be a dash, lowercase letter, or digit, except the last character, which cannot be a dash.

recommendedSize number

Target recommended MIG size (number of instances) computed by autoscaler. Autoscaler calculates the recommended MIG size even when the autoscaling policy mode is different from ON. This field is empty when autoscaler is not connected to an existing managed instance group or autoscaler did not generate its prediction.

region string

URL of the region where the instance group resides (for autoscalers living in regional scope).

scalingScheduleStatus {[key: string]: string}

Status information of existing scaling schedules.

selfLink string

Server-defined URL for the resource.

status string

The status of the autoscaler configuration. Current set of possible values: - PENDING: Autoscaler backend hasn't read new/updated configuration. - DELETING: Configuration is being deleted. - ACTIVE: Configuration is acknowledged to be effective. Some warnings might be present in the statusDetails field. - ERROR: Configuration has errors. Actionable for users. Details are present in the statusDetails field. New values might be added in the future.

statusDetails AutoscalerStatusDetailsResponse[]

Human-readable details about the current state of the autoscaler. Read the documentation for Commonly returned status messages for examples of status messages you might encounter.

target string

URL of the managed instance group that this autoscaler will scale. This field is required when creating an autoscaler.

zone string

URL of the zone where the instance group resides (for autoscalers living in zonal scope).

autoscaling_policy AutoscalingPolicyResponse

The configuration parameters for the autoscaling algorithm. You can define one or more signals for an autoscaler: cpuUtilization, customMetricUtilizations, and loadBalancingUtilization. If none of these are specified, the default will be to autoscale based on cpuUtilization to 0.6 or 60%.

creation_timestamp str

Creation timestamp in RFC3339 text format.

description str

An optional description of this resource. Provide this property when you create the resource.

kind str

Type of the resource. Always compute#autoscaler for autoscalers.

name str

Name of the resource. Provided by the client when the resource is created. The name must be 1-63 characters long, and comply with RFC1035. Specifically, the name must be 1-63 characters long and match the regular expression [a-z]([-a-z0-9]*[a-z0-9])? which means the first character must be a lowercase letter, and all following characters must be a dash, lowercase letter, or digit, except the last character, which cannot be a dash.

recommended_size int

Target recommended MIG size (number of instances) computed by autoscaler. Autoscaler calculates the recommended MIG size even when the autoscaling policy mode is different from ON. This field is empty when autoscaler is not connected to an existing managed instance group or autoscaler did not generate its prediction.

region str

URL of the region where the instance group resides (for autoscalers living in regional scope).

scaling_schedule_status Mapping[str, str]

Status information of existing scaling schedules.

self_link str

Server-defined URL for the resource.

status str

The status of the autoscaler configuration. Current set of possible values: - PENDING: Autoscaler backend hasn't read new/updated configuration. - DELETING: Configuration is being deleted. - ACTIVE: Configuration is acknowledged to be effective. Some warnings might be present in the statusDetails field. - ERROR: Configuration has errors. Actionable for users. Details are present in the statusDetails field. New values might be added in the future.

status_details Sequence[AutoscalerStatusDetailsResponse]

Human-readable details about the current state of the autoscaler. Read the documentation for Commonly returned status messages for examples of status messages you might encounter.

target str

URL of the managed instance group that this autoscaler will scale. This field is required when creating an autoscaler.

zone str

URL of the zone where the instance group resides (for autoscalers living in zonal scope).

autoscalingPolicy Property Map

The configuration parameters for the autoscaling algorithm. You can define one or more signals for an autoscaler: cpuUtilization, customMetricUtilizations, and loadBalancingUtilization. If none of these are specified, the default will be to autoscale based on cpuUtilization to 0.6 or 60%.

creationTimestamp String

Creation timestamp in RFC3339 text format.

description String

An optional description of this resource. Provide this property when you create the resource.

kind String

Type of the resource. Always compute#autoscaler for autoscalers.

name String

Name of the resource. Provided by the client when the resource is created. The name must be 1-63 characters long, and comply with RFC1035. Specifically, the name must be 1-63 characters long and match the regular expression [a-z]([-a-z0-9]*[a-z0-9])? which means the first character must be a lowercase letter, and all following characters must be a dash, lowercase letter, or digit, except the last character, which cannot be a dash.

recommendedSize Number

Target recommended MIG size (number of instances) computed by autoscaler. Autoscaler calculates the recommended MIG size even when the autoscaling policy mode is different from ON. This field is empty when autoscaler is not connected to an existing managed instance group or autoscaler did not generate its prediction.

region String

URL of the region where the instance group resides (for autoscalers living in regional scope).

scalingScheduleStatus Map<String>

Status information of existing scaling schedules.

selfLink String

Server-defined URL for the resource.

status String

The status of the autoscaler configuration. Current set of possible values: - PENDING: Autoscaler backend hasn't read new/updated configuration. - DELETING: Configuration is being deleted. - ACTIVE: Configuration is acknowledged to be effective. Some warnings might be present in the statusDetails field. - ERROR: Configuration has errors. Actionable for users. Details are present in the statusDetails field. New values might be added in the future.

statusDetails List<Property Map>

Human-readable details about the current state of the autoscaler. Read the documentation for Commonly returned status messages for examples of status messages you might encounter.

target String

URL of the managed instance group that this autoscaler will scale. This field is required when creating an autoscaler.

zone String

URL of the zone where the instance group resides (for autoscalers living in zonal scope).

Supporting Types

AutoscalerStatusDetailsResponse

Message string

The status message.

Type string

The type of error, warning, or notice returned. Current set of possible values: - ALL_INSTANCES_UNHEALTHY (WARNING): All instances in the instance group are unhealthy (not in RUNNING state). - BACKEND_SERVICE_DOES_NOT_EXIST (ERROR): There is no backend service attached to the instance group. - CAPPED_AT_MAX_NUM_REPLICAS (WARNING): Autoscaler recommends a size greater than maxNumReplicas. - CUSTOM_METRIC_DATA_POINTS_TOO_SPARSE (WARNING): The custom metric samples are not exported often enough to be a credible base for autoscaling. - CUSTOM_METRIC_INVALID (ERROR): The custom metric that was specified does not exist or does not have the necessary labels. - MIN_EQUALS_MAX (WARNING): The minNumReplicas is equal to maxNumReplicas. This means the autoscaler cannot add or remove instances from the instance group. - MISSING_CUSTOM_METRIC_DATA_POINTS (WARNING): The autoscaler did not receive any data from the custom metric configured for autoscaling. - MISSING_LOAD_BALANCING_DATA_POINTS (WARNING): The autoscaler is configured to scale based on a load balancing signal but the instance group has not received any requests from the load balancer. - MODE_OFF (WARNING): Autoscaling is turned off. The number of instances in the group won't change automatically. The autoscaling configuration is preserved. - MODE_ONLY_UP (WARNING): Autoscaling is in the "Autoscale only out" mode. The autoscaler can add instances but not remove any. - MORE_THAN_ONE_BACKEND_SERVICE (ERROR): The instance group cannot be autoscaled because it has more than one backend service attached to it. - NOT_ENOUGH_QUOTA_AVAILABLE (ERROR): There is insufficient quota for the necessary resources, such as CPU or number of instances. - REGION_RESOURCE_STOCKOUT (ERROR): Shown only for regional autoscalers: there is a resource stockout in the chosen region. - SCALING_TARGET_DOES_NOT_EXIST (ERROR): The target to be scaled does not exist. - UNSUPPORTED_MAX_RATE_LOAD_BALANCING_CONFIGURATION (ERROR): Autoscaling does not work with an HTTP/S load balancer that has been configured for maxRate. - ZONE_RESOURCE_STOCKOUT (ERROR): For zonal autoscalers: there is a resource stockout in the chosen zone. For regional autoscalers: in at least one of the zones you're using there is a resource stockout. New values might be added in the future. Some of the values might not be available in all API versions.

Message string

The status message.

Type string

The type of error, warning, or notice returned. Current set of possible values: - ALL_INSTANCES_UNHEALTHY (WARNING): All instances in the instance group are unhealthy (not in RUNNING state). - BACKEND_SERVICE_DOES_NOT_EXIST (ERROR): There is no backend service attached to the instance group. - CAPPED_AT_MAX_NUM_REPLICAS (WARNING): Autoscaler recommends a size greater than maxNumReplicas. - CUSTOM_METRIC_DATA_POINTS_TOO_SPARSE (WARNING): The custom metric samples are not exported often enough to be a credible base for autoscaling. - CUSTOM_METRIC_INVALID (ERROR): The custom metric that was specified does not exist or does not have the necessary labels. - MIN_EQUALS_MAX (WARNING): The minNumReplicas is equal to maxNumReplicas. This means the autoscaler cannot add or remove instances from the instance group. - MISSING_CUSTOM_METRIC_DATA_POINTS (WARNING): The autoscaler did not receive any data from the custom metric configured for autoscaling. - MISSING_LOAD_BALANCING_DATA_POINTS (WARNING): The autoscaler is configured to scale based on a load balancing signal but the instance group has not received any requests from the load balancer. - MODE_OFF (WARNING): Autoscaling is turned off. The number of instances in the group won't change automatically. The autoscaling configuration is preserved. - MODE_ONLY_UP (WARNING): Autoscaling is in the "Autoscale only out" mode. The autoscaler can add instances but not remove any. - MORE_THAN_ONE_BACKEND_SERVICE (ERROR): The instance group cannot be autoscaled because it has more than one backend service attached to it. - NOT_ENOUGH_QUOTA_AVAILABLE (ERROR): There is insufficient quota for the necessary resources, such as CPU or number of instances. - REGION_RESOURCE_STOCKOUT (ERROR): Shown only for regional autoscalers: there is a resource stockout in the chosen region. - SCALING_TARGET_DOES_NOT_EXIST (ERROR): The target to be scaled does not exist. - UNSUPPORTED_MAX_RATE_LOAD_BALANCING_CONFIGURATION (ERROR): Autoscaling does not work with an HTTP/S load balancer that has been configured for maxRate. - ZONE_RESOURCE_STOCKOUT (ERROR): For zonal autoscalers: there is a resource stockout in the chosen zone. For regional autoscalers: in at least one of the zones you're using there is a resource stockout. New values might be added in the future. Some of the values might not be available in all API versions.

message String

The status message.

type String

The type of error, warning, or notice returned. Current set of possible values: - ALL_INSTANCES_UNHEALTHY (WARNING): All instances in the instance group are unhealthy (not in RUNNING state). - BACKEND_SERVICE_DOES_NOT_EXIST (ERROR): There is no backend service attached to the instance group. - CAPPED_AT_MAX_NUM_REPLICAS (WARNING): Autoscaler recommends a size greater than maxNumReplicas. - CUSTOM_METRIC_DATA_POINTS_TOO_SPARSE (WARNING): The custom metric samples are not exported often enough to be a credible base for autoscaling. - CUSTOM_METRIC_INVALID (ERROR): The custom metric that was specified does not exist or does not have the necessary labels. - MIN_EQUALS_MAX (WARNING): The minNumReplicas is equal to maxNumReplicas. This means the autoscaler cannot add or remove instances from the instance group. - MISSING_CUSTOM_METRIC_DATA_POINTS (WARNING): The autoscaler did not receive any data from the custom metric configured for autoscaling. - MISSING_LOAD_BALANCING_DATA_POINTS (WARNING): The autoscaler is configured to scale based on a load balancing signal but the instance group has not received any requests from the load balancer. - MODE_OFF (WARNING): Autoscaling is turned off. The number of instances in the group won't change automatically. The autoscaling configuration is preserved. - MODE_ONLY_UP (WARNING): Autoscaling is in the "Autoscale only out" mode. The autoscaler can add instances but not remove any. - MORE_THAN_ONE_BACKEND_SERVICE (ERROR): The instance group cannot be autoscaled because it has more than one backend service attached to it. - NOT_ENOUGH_QUOTA_AVAILABLE (ERROR): There is insufficient quota for the necessary resources, such as CPU or number of instances. - REGION_RESOURCE_STOCKOUT (ERROR): Shown only for regional autoscalers: there is a resource stockout in the chosen region. - SCALING_TARGET_DOES_NOT_EXIST (ERROR): The target to be scaled does not exist. - UNSUPPORTED_MAX_RATE_LOAD_BALANCING_CONFIGURATION (ERROR): Autoscaling does not work with an HTTP/S load balancer that has been configured for maxRate. - ZONE_RESOURCE_STOCKOUT (ERROR): For zonal autoscalers: there is a resource stockout in the chosen zone. For regional autoscalers: in at least one of the zones you're using there is a resource stockout. New values might be added in the future. Some of the values might not be available in all API versions.

message string

The status message.

type string

The type of error, warning, or notice returned. Current set of possible values: - ALL_INSTANCES_UNHEALTHY (WARNING): All instances in the instance group are unhealthy (not in RUNNING state). - BACKEND_SERVICE_DOES_NOT_EXIST (ERROR): There is no backend service attached to the instance group. - CAPPED_AT_MAX_NUM_REPLICAS (WARNING): Autoscaler recommends a size greater than maxNumReplicas. - CUSTOM_METRIC_DATA_POINTS_TOO_SPARSE (WARNING): The custom metric samples are not exported often enough to be a credible base for autoscaling. - CUSTOM_METRIC_INVALID (ERROR): The custom metric that was specified does not exist or does not have the necessary labels. - MIN_EQUALS_MAX (WARNING): The minNumReplicas is equal to maxNumReplicas. This means the autoscaler cannot add or remove instances from the instance group. - MISSING_CUSTOM_METRIC_DATA_POINTS (WARNING): The autoscaler did not receive any data from the custom metric configured for autoscaling. - MISSING_LOAD_BALANCING_DATA_POINTS (WARNING): The autoscaler is configured to scale based on a load balancing signal but the instance group has not received any requests from the load balancer. - MODE_OFF (WARNING): Autoscaling is turned off. The number of instances in the group won't change automatically. The autoscaling configuration is preserved. - MODE_ONLY_UP (WARNING): Autoscaling is in the "Autoscale only out" mode. The autoscaler can add instances but not remove any. - MORE_THAN_ONE_BACKEND_SERVICE (ERROR): The instance group cannot be autoscaled because it has more than one backend service attached to it. - NOT_ENOUGH_QUOTA_AVAILABLE (ERROR): There is insufficient quota for the necessary resources, such as CPU or number of instances. - REGION_RESOURCE_STOCKOUT (ERROR): Shown only for regional autoscalers: there is a resource stockout in the chosen region. - SCALING_TARGET_DOES_NOT_EXIST (ERROR): The target to be scaled does not exist. - UNSUPPORTED_MAX_RATE_LOAD_BALANCING_CONFIGURATION (ERROR): Autoscaling does not work with an HTTP/S load balancer that has been configured for maxRate. - ZONE_RESOURCE_STOCKOUT (ERROR): For zonal autoscalers: there is a resource stockout in the chosen zone. For regional autoscalers: in at least one of the zones you're using there is a resource stockout. New values might be added in the future. Some of the values might not be available in all API versions.

message str

The status message.

type str

The type of error, warning, or notice returned. Current set of possible values: - ALL_INSTANCES_UNHEALTHY (WARNING): All instances in the instance group are unhealthy (not in RUNNING state). - BACKEND_SERVICE_DOES_NOT_EXIST (ERROR): There is no backend service attached to the instance group. - CAPPED_AT_MAX_NUM_REPLICAS (WARNING): Autoscaler recommends a size greater than maxNumReplicas. - CUSTOM_METRIC_DATA_POINTS_TOO_SPARSE (WARNING): The custom metric samples are not exported often enough to be a credible base for autoscaling. - CUSTOM_METRIC_INVALID (ERROR): The custom metric that was specified does not exist or does not have the necessary labels. - MIN_EQUALS_MAX (WARNING): The minNumReplicas is equal to maxNumReplicas. This means the autoscaler cannot add or remove instances from the instance group. - MISSING_CUSTOM_METRIC_DATA_POINTS (WARNING): The autoscaler did not receive any data from the custom metric configured for autoscaling. - MISSING_LOAD_BALANCING_DATA_POINTS (WARNING): The autoscaler is configured to scale based on a load balancing signal but the instance group has not received any requests from the load balancer. - MODE_OFF (WARNING): Autoscaling is turned off. The number of instances in the group won't change automatically. The autoscaling configuration is preserved. - MODE_ONLY_UP (WARNING): Autoscaling is in the "Autoscale only out" mode. The autoscaler can add instances but not remove any. - MORE_THAN_ONE_BACKEND_SERVICE (ERROR): The instance group cannot be autoscaled because it has more than one backend service attached to it. - NOT_ENOUGH_QUOTA_AVAILABLE (ERROR): There is insufficient quota for the necessary resources, such as CPU or number of instances. - REGION_RESOURCE_STOCKOUT (ERROR): Shown only for regional autoscalers: there is a resource stockout in the chosen region. - SCALING_TARGET_DOES_NOT_EXIST (ERROR): The target to be scaled does not exist. - UNSUPPORTED_MAX_RATE_LOAD_BALANCING_CONFIGURATION (ERROR): Autoscaling does not work with an HTTP/S load balancer that has been configured for maxRate. - ZONE_RESOURCE_STOCKOUT (ERROR): For zonal autoscalers: there is a resource stockout in the chosen zone. For regional autoscalers: in at least one of the zones you're using there is a resource stockout. New values might be added in the future. Some of the values might not be available in all API versions.

message String

The status message.

type String

The type of error, warning, or notice returned. Current set of possible values: - ALL_INSTANCES_UNHEALTHY (WARNING): All instances in the instance group are unhealthy (not in RUNNING state). - BACKEND_SERVICE_DOES_NOT_EXIST (ERROR): There is no backend service attached to the instance group. - CAPPED_AT_MAX_NUM_REPLICAS (WARNING): Autoscaler recommends a size greater than maxNumReplicas. - CUSTOM_METRIC_DATA_POINTS_TOO_SPARSE (WARNING): The custom metric samples are not exported often enough to be a credible base for autoscaling. - CUSTOM_METRIC_INVALID (ERROR): The custom metric that was specified does not exist or does not have the necessary labels. - MIN_EQUALS_MAX (WARNING): The minNumReplicas is equal to maxNumReplicas. This means the autoscaler cannot add or remove instances from the instance group. - MISSING_CUSTOM_METRIC_DATA_POINTS (WARNING): The autoscaler did not receive any data from the custom metric configured for autoscaling. - MISSING_LOAD_BALANCING_DATA_POINTS (WARNING): The autoscaler is configured to scale based on a load balancing signal but the instance group has not received any requests from the load balancer. - MODE_OFF (WARNING): Autoscaling is turned off. The number of instances in the group won't change automatically. The autoscaling configuration is preserved. - MODE_ONLY_UP (WARNING): Autoscaling is in the "Autoscale only out" mode. The autoscaler can add instances but not remove any. - MORE_THAN_ONE_BACKEND_SERVICE (ERROR): The instance group cannot be autoscaled because it has more than one backend service attached to it. - NOT_ENOUGH_QUOTA_AVAILABLE (ERROR): There is insufficient quota for the necessary resources, such as CPU or number of instances. - REGION_RESOURCE_STOCKOUT (ERROR): Shown only for regional autoscalers: there is a resource stockout in the chosen region. - SCALING_TARGET_DOES_NOT_EXIST (ERROR): The target to be scaled does not exist. - UNSUPPORTED_MAX_RATE_LOAD_BALANCING_CONFIGURATION (ERROR): Autoscaling does not work with an HTTP/S load balancer that has been configured for maxRate. - ZONE_RESOURCE_STOCKOUT (ERROR): For zonal autoscalers: there is a resource stockout in the chosen zone. For regional autoscalers: in at least one of the zones you're using there is a resource stockout. New values might be added in the future. Some of the values might not be available in all API versions.

AutoscalingPolicyCpuUtilizationResponse

PredictiveMethod string

Indicates whether predictive autoscaling based on CPU metric is enabled. Valid values are: * NONE (default). No predictive method is used. The autoscaler scales the group to meet current demand based on real-time metrics. * OPTIMIZE_AVAILABILITY. Predictive autoscaling improves availability by monitoring daily and weekly load patterns and scaling out ahead of anticipated demand.

UtilizationTarget double

The target CPU utilization that the autoscaler maintains. Must be a float value in the range (0, 1]. If not specified, the default is 0.6. If the CPU level is below the target utilization, the autoscaler scales in the number of instances until it reaches the minimum number of instances you specified or until the average CPU of your instances reaches the target utilization. If the average CPU is above the target utilization, the autoscaler scales out until it reaches the maximum number of instances you specified or until the average utilization reaches the target utilization.

PredictiveMethod string

Indicates whether predictive autoscaling based on CPU metric is enabled. Valid values are: * NONE (default). No predictive method is used. The autoscaler scales the group to meet current demand based on real-time metrics. * OPTIMIZE_AVAILABILITY. Predictive autoscaling improves availability by monitoring daily and weekly load patterns and scaling out ahead of anticipated demand.

UtilizationTarget float64

The target CPU utilization that the autoscaler maintains. Must be a float value in the range (0, 1]. If not specified, the default is 0.6. If the CPU level is below the target utilization, the autoscaler scales in the number of instances until it reaches the minimum number of instances you specified or until the average CPU of your instances reaches the target utilization. If the average CPU is above the target utilization, the autoscaler scales out until it reaches the maximum number of instances you specified or until the average utilization reaches the target utilization.

predictiveMethod String

Indicates whether predictive autoscaling based on CPU metric is enabled. Valid values are: * NONE (default). No predictive method is used. The autoscaler scales the group to meet current demand based on real-time metrics. * OPTIMIZE_AVAILABILITY. Predictive autoscaling improves availability by monitoring daily and weekly load patterns and scaling out ahead of anticipated demand.

utilizationTarget Double

The target CPU utilization that the autoscaler maintains. Must be a float value in the range (0, 1]. If not specified, the default is 0.6. If the CPU level is below the target utilization, the autoscaler scales in the number of instances until it reaches the minimum number of instances you specified or until the average CPU of your instances reaches the target utilization. If the average CPU is above the target utilization, the autoscaler scales out until it reaches the maximum number of instances you specified or until the average utilization reaches the target utilization.

predictiveMethod string

Indicates whether predictive autoscaling based on CPU metric is enabled. Valid values are: * NONE (default). No predictive method is used. The autoscaler scales the group to meet current demand based on real-time metrics. * OPTIMIZE_AVAILABILITY. Predictive autoscaling improves availability by monitoring daily and weekly load patterns and scaling out ahead of anticipated demand.

utilizationTarget number

The target CPU utilization that the autoscaler maintains. Must be a float value in the range (0, 1]. If not specified, the default is 0.6. If the CPU level is below the target utilization, the autoscaler scales in the number of instances until it reaches the minimum number of instances you specified or until the average CPU of your instances reaches the target utilization. If the average CPU is above the target utilization, the autoscaler scales out until it reaches the maximum number of instances you specified or until the average utilization reaches the target utilization.

predictive_method str

Indicates whether predictive autoscaling based on CPU metric is enabled. Valid values are: * NONE (default). No predictive method is used. The autoscaler scales the group to meet current demand based on real-time metrics. * OPTIMIZE_AVAILABILITY. Predictive autoscaling improves availability by monitoring daily and weekly load patterns and scaling out ahead of anticipated demand.

utilization_target float

The target CPU utilization that the autoscaler maintains. Must be a float value in the range (0, 1]. If not specified, the default is 0.6. If the CPU level is below the target utilization, the autoscaler scales in the number of instances until it reaches the minimum number of instances you specified or until the average CPU of your instances reaches the target utilization. If the average CPU is above the target utilization, the autoscaler scales out until it reaches the maximum number of instances you specified or until the average utilization reaches the target utilization.

predictiveMethod String

Indicates whether predictive autoscaling based on CPU metric is enabled. Valid values are: * NONE (default). No predictive method is used. The autoscaler scales the group to meet current demand based on real-time metrics. * OPTIMIZE_AVAILABILITY. Predictive autoscaling improves availability by monitoring daily and weekly load patterns and scaling out ahead of anticipated demand.

utilizationTarget Number

The target CPU utilization that the autoscaler maintains. Must be a float value in the range (0, 1]. If not specified, the default is 0.6. If the CPU level is below the target utilization, the autoscaler scales in the number of instances until it reaches the minimum number of instances you specified or until the average CPU of your instances reaches the target utilization. If the average CPU is above the target utilization, the autoscaler scales out until it reaches the maximum number of instances you specified or until the average utilization reaches the target utilization.

AutoscalingPolicyCustomMetricUtilizationResponse

Filter string

A filter string, compatible with a Stackdriver Monitoring filter string for TimeSeries.list API call. This filter is used to select a specific TimeSeries for the purpose of autoscaling and to determine whether the metric is exporting per-instance or per-group data. For the filter to be valid for autoscaling purposes, the following rules apply: - You can only use the AND operator for joining selectors. - You can only use direct equality comparison operator (=) without any functions for each selector. - You can specify the metric in both the filter string and in the metric field. However, if specified in both places, the metric must be identical. - The monitored resource type determines what kind of values are expected for the metric. If it is a gce_instance, the autoscaler expects the metric to include a separate TimeSeries for each instance in a group. In such a case, you cannot filter on resource labels. If the resource type is any other value, the autoscaler expects this metric to contain values that apply to the entire autoscaled instance group and resource label filtering can be performed to point autoscaler at the correct TimeSeries to scale upon. This is called a per-group metric for the purpose of autoscaling. If not specified, the type defaults to gce_instance. Try to provide a filter that is selective enough to pick just one TimeSeries for the autoscaled group or for each of the instances (if you are using gce_instance resource type). If multiple TimeSeries are returned upon the query execution, the autoscaler will sum their respective values to obtain its scaling value.

Metric string

The identifier (type) of the Stackdriver Monitoring metric. The metric cannot have negative values. The metric must have a value type of INT64 or DOUBLE.

SingleInstanceAssignment double

If scaling is based on a per-group metric value that represents the total amount of work to be done or resource usage, set this value to an amount assigned for a single instance of the scaled group. Autoscaler keeps the number of instances proportional to the value of this metric. The metric itself does not change value due to group resizing. A good metric to use with the target is for example pubsub.googleapis.com/subscription/num_undelivered_messages or a custom metric exporting the total number of requests coming to your instances. A bad example would be a metric exporting an average or median latency, since this value can't include a chunk assignable to a single instance, it could be better used with utilization_target instead.

UtilizationTarget double

The target value of the metric that autoscaler maintains. This must be a positive value. A utilization metric scales number of virtual machines handling requests to increase or decrease proportionally to the metric. For example, a good metric to use as a utilization_target is https://www.googleapis.com/compute/v1/instance/network/received_bytes_count. The autoscaler works to keep this value constant for each of the instances.

UtilizationTargetType string

Defines how target utilization value is expressed for a Stackdriver Monitoring metric. Either GAUGE, DELTA_PER_SECOND, or DELTA_PER_MINUTE.

Filter string

A filter string, compatible with a Stackdriver Monitoring filter string for TimeSeries.list API call. This filter is used to select a specific TimeSeries for the purpose of autoscaling and to determine whether the metric is exporting per-instance or per-group data. For the filter to be valid for autoscaling purposes, the following rules apply: - You can only use the AND operator for joining selectors. - You can only use direct equality comparison operator (=) without any functions for each selector. - You can specify the metric in both the filter string and in the metric field. However, if specified in both places, the metric must be identical. - The monitored resource type determines what kind of values are expected for the metric. If it is a gce_instance, the autoscaler expects the metric to include a separate TimeSeries for each instance in a group. In such a case, you cannot filter on resource labels. If the resource type is any other value, the autoscaler expects this metric to contain values that apply to the entire autoscaled instance group and resource label filtering can be performed to point autoscaler at the correct TimeSeries to scale upon. This is called a per-group metric for the purpose of autoscaling. If not specified, the type defaults to gce_instance. Try to provide a filter that is selective enough to pick just one TimeSeries for the autoscaled group or for each of the instances (if you are using gce_instance resource type). If multiple TimeSeries are returned upon the query execution, the autoscaler will sum their respective values to obtain its scaling value.

Metric string

The identifier (type) of the Stackdriver Monitoring metric. The metric cannot have negative values. The metric must have a value type of INT64 or DOUBLE.

SingleInstanceAssignment float64

If scaling is based on a per-group metric value that represents the total amount of work to be done or resource usage, set this value to an amount assigned for a single instance of the scaled group. Autoscaler keeps the number of instances proportional to the value of this metric. The metric itself does not change value due to group resizing. A good metric to use with the target is for example pubsub.googleapis.com/subscription/num_undelivered_messages or a custom metric exporting the total number of requests coming to your instances. A bad example would be a metric exporting an average or median latency, since this value can't include a chunk assignable to a single instance, it could be better used with utilization_target instead.

UtilizationTarget float64

The target value of the metric that autoscaler maintains. This must be a positive value. A utilization metric scales number of virtual machines handling requests to increase or decrease proportionally to the metric. For example, a good metric to use as a utilization_target is https://www.googleapis.com/compute/v1/instance/network/received_bytes_count. The autoscaler works to keep this value constant for each of the instances.

UtilizationTargetType string

Defines how target utilization value is expressed for a Stackdriver Monitoring metric. Either GAUGE, DELTA_PER_SECOND, or DELTA_PER_MINUTE.

filter String

A filter string, compatible with a Stackdriver Monitoring filter string for TimeSeries.list API call. This filter is used to select a specific TimeSeries for the purpose of autoscaling and to determine whether the metric is exporting per-instance or per-group data. For the filter to be valid for autoscaling purposes, the following rules apply: - You can only use the AND operator for joining selectors. - You can only use direct equality comparison operator (=) without any functions for each selector. - You can specify the metric in both the filter string and in the metric field. However, if specified in both places, the metric must be identical. - The monitored resource type determines what kind of values are expected for the metric. If it is a gce_instance, the autoscaler expects the metric to include a separate TimeSeries for each instance in a group. In such a case, you cannot filter on resource labels. If the resource type is any other value, the autoscaler expects this metric to contain values that apply to the entire autoscaled instance group and resource label filtering can be performed to point autoscaler at the correct TimeSeries to scale upon. This is called a per-group metric for the purpose of autoscaling. If not specified, the type defaults to gce_instance. Try to provide a filter that is selective enough to pick just one TimeSeries for the autoscaled group or for each of the instances (if you are using gce_instance resource type). If multiple TimeSeries are returned upon the query execution, the autoscaler will sum their respective values to obtain its scaling value.

metric String

The identifier (type) of the Stackdriver Monitoring metric. The metric cannot have negative values. The metric must have a value type of INT64 or DOUBLE.

singleInstanceAssignment Double

If scaling is based on a per-group metric value that represents the total amount of work to be done or resource usage, set this value to an amount assigned for a single instance of the scaled group. Autoscaler keeps the number of instances proportional to the value of this metric. The metric itself does not change value due to group resizing. A good metric to use with the target is for example pubsub.googleapis.com/subscription/num_undelivered_messages or a custom metric exporting the total number of requests coming to your instances. A bad example would be a metric exporting an average or median latency, since this value can't include a chunk assignable to a single instance, it could be better used with utilization_target instead.

utilizationTarget Double

The target value of the metric that autoscaler maintains. This must be a positive value. A utilization metric scales number of virtual machines handling requests to increase or decrease proportionally to the metric. For example, a good metric to use as a utilization_target is https://www.googleapis.com/compute/v1/instance/network/received_bytes_count. The autoscaler works to keep this value constant for each of the instances.

utilizationTargetType String

Defines how target utilization value is expressed for a Stackdriver Monitoring metric. Either GAUGE, DELTA_PER_SECOND, or DELTA_PER_MINUTE.

filter string

A filter string, compatible with a Stackdriver Monitoring filter string for TimeSeries.list API call. This filter is used to select a specific TimeSeries for the purpose of autoscaling and to determine whether the metric is exporting per-instance or per-group data. For the filter to be valid for autoscaling purposes, the following rules apply: - You can only use the AND operator for joining selectors. - You can only use direct equality comparison operator (=) without any functions for each selector. - You can specify the metric in both the filter string and in the metric field. However, if specified in both places, the metric must be identical. - The monitored resource type determines what kind of values are expected for the metric. If it is a gce_instance, the autoscaler expects the metric to include a separate TimeSeries for each instance in a group. In such a case, you cannot filter on resource labels. If the resource type is any other value, the autoscaler expects this metric to contain values that apply to the entire autoscaled instance group and resource label filtering can be performed to point autoscaler at the correct TimeSeries to scale upon. This is called a per-group metric for the purpose of autoscaling. If not specified, the type defaults to gce_instance. Try to provide a filter that is selective enough to pick just one TimeSeries for the autoscaled group or for each of the instances (if you are using gce_instance resource type). If multiple TimeSeries are returned upon the query execution, the autoscaler will sum their respective values to obtain its scaling value.

metric string

The identifier (type) of the Stackdriver Monitoring metric. The metric cannot have negative values. The metric must have a value type of INT64 or DOUBLE.

singleInstanceAssignment number

If scaling is based on a per-group metric value that represents the total amount of work to be done or resource usage, set this value to an amount assigned for a single instance of the scaled group. Autoscaler keeps the number of instances proportional to the value of this metric. The metric itself does not change value due to group resizing. A good metric to use with the target is for example pubsub.googleapis.com/subscription/num_undelivered_messages or a custom metric exporting the total number of requests coming to your instances. A bad example would be a metric exporting an average or median latency, since this value can't include a chunk assignable to a single instance, it could be better used with utilization_target instead.

utilizationTarget number

The target value of the metric that autoscaler maintains. This must be a positive value. A utilization metric scales number of virtual machines handling requests to increase or decrease proportionally to the metric. For example, a good metric to use as a utilization_target is https://www.googleapis.com/compute/v1/instance/network/received_bytes_count. The autoscaler works to keep this value constant for each of the instances.

utilizationTargetType string

Defines how target utilization value is expressed for a Stackdriver Monitoring metric. Either GAUGE, DELTA_PER_SECOND, or DELTA_PER_MINUTE.

filter str

A filter string, compatible with a Stackdriver Monitoring filter string for TimeSeries.list API call. This filter is used to select a specific TimeSeries for the purpose of autoscaling and to determine whether the metric is exporting per-instance or per-group data. For the filter to be valid for autoscaling purposes, the following rules apply: - You can only use the AND operator for joining selectors. - You can only use direct equality comparison operator (=) without any functions for each selector. - You can specify the metric in both the filter string and in the metric field. However, if specified in both places, the metric must be identical. - The monitored resource type determines what kind of values are expected for the metric. If it is a gce_instance, the autoscaler expects the metric to include a separate TimeSeries for each instance in a group. In such a case, you cannot filter on resource labels. If the resource type is any other value, the autoscaler expects this metric to contain values that apply to the entire autoscaled instance group and resource label filtering can be performed to point autoscaler at the correct TimeSeries to scale upon. This is called a per-group metric for the purpose of autoscaling. If not specified, the type defaults to gce_instance. Try to provide a filter that is selective enough to pick just one TimeSeries for the autoscaled group or for each of the instances (if you are using gce_instance resource type). If multiple TimeSeries are returned upon the query execution, the autoscaler will sum their respective values to obtain its scaling value.

metric str

The identifier (type) of the Stackdriver Monitoring metric. The metric cannot have negative values. The metric must have a value type of INT64 or DOUBLE.

single_instance_assignment float

If scaling is based on a per-group metric value that represents the total amount of work to be done or resource usage, set this value to an amount assigned for a single instance of the scaled group. Autoscaler keeps the number of instances proportional to the value of this metric. The metric itself does not change value due to group resizing. A good metric to use with the target is for example pubsub.googleapis.com/subscription/num_undelivered_messages or a custom metric exporting the total number of requests coming to your instances. A bad example would be a metric exporting an average or median latency, since this value can't include a chunk assignable to a single instance, it could be better used with utilization_target instead.

utilization_target float

The target value of the metric that autoscaler maintains. This must be a positive value. A utilization metric scales number of virtual machines handling requests to increase or decrease proportionally to the metric. For example, a good metric to use as a utilization_target is https://www.googleapis.com/compute/v1/instance/network/received_bytes_count. The autoscaler works to keep this value constant for each of the instances.

utilization_target_type str

Defines how target utilization value is expressed for a Stackdriver Monitoring metric. Either GAUGE, DELTA_PER_SECOND, or DELTA_PER_MINUTE.

filter String

A filter string, compatible with a Stackdriver Monitoring filter string for TimeSeries.list API call. This filter is used to select a specific TimeSeries for the purpose of autoscaling and to determine whether the metric is exporting per-instance or per-group data. For the filter to be valid for autoscaling purposes, the following rules apply: - You can only use the AND operator for joining selectors. - You can only use direct equality comparison operator (=) without any functions for each selector. - You can specify the metric in both the filter string and in the metric field. However, if specified in both places, the metric must be identical. - The monitored resource type determines what kind of values are expected for the metric. If it is a gce_instance, the autoscaler expects the metric to include a separate TimeSeries for each instance in a group. In such a case, you cannot filter on resource labels. If the resource type is any other value, the autoscaler expects this metric to contain values that apply to the entire autoscaled instance group and resource label filtering can be performed to point autoscaler at the correct TimeSeries to scale upon. This is called a per-group metric for the purpose of autoscaling. If not specified, the type defaults to gce_instance. Try to provide a filter that is selective enough to pick just one TimeSeries for the autoscaled group or for each of the instances (if you are using gce_instance resource type). If multiple TimeSeries are returned upon the query execution, the autoscaler will sum their respective values to obtain its scaling value.

metric String

The identifier (type) of the Stackdriver Monitoring metric. The metric cannot have negative values. The metric must have a value type of INT64 or DOUBLE.

singleInstanceAssignment Number

If scaling is based on a per-group metric value that represents the total amount of work to be done or resource usage, set this value to an amount assigned for a single instance of the scaled group. Autoscaler keeps the number of instances proportional to the value of this metric. The metric itself does not change value due to group resizing. A good metric to use with the target is for example pubsub.googleapis.com/subscription/num_undelivered_messages or a custom metric exporting the total number of requests coming to your instances. A bad example would be a metric exporting an average or median latency, since this value can't include a chunk assignable to a single instance, it could be better used with utilization_target instead.

utilizationTarget Number

The target value of the metric that autoscaler maintains. This must be a positive value. A utilization metric scales number of virtual machines handling requests to increase or decrease proportionally to the metric. For example, a good metric to use as a utilization_target is https://www.googleapis.com/compute/v1/instance/network/received_bytes_count. The autoscaler works to keep this value constant for each of the instances.

utilizationTargetType String

Defines how target utilization value is expressed for a Stackdriver Monitoring metric. Either GAUGE, DELTA_PER_SECOND, or DELTA_PER_MINUTE.

AutoscalingPolicyLoadBalancingUtilizationResponse

UtilizationTarget double

Fraction of backend capacity utilization (set in HTTP(S) load balancing configuration) that the autoscaler maintains. Must be a positive float value. If not defined, the default is 0.8.

UtilizationTarget float64

Fraction of backend capacity utilization (set in HTTP(S) load balancing configuration) that the autoscaler maintains. Must be a positive float value. If not defined, the default is 0.8.

utilizationTarget Double

Fraction of backend capacity utilization (set in HTTP(S) load balancing configuration) that the autoscaler maintains. Must be a positive float value. If not defined, the default is 0.8.

utilizationTarget number

Fraction of backend capacity utilization (set in HTTP(S) load balancing configuration) that the autoscaler maintains. Must be a positive float value. If not defined, the default is 0.8.

utilization_target float

Fraction of backend capacity utilization (set in HTTP(S) load balancing configuration) that the autoscaler maintains. Must be a positive float value. If not defined, the default is 0.8.

utilizationTarget Number

Fraction of backend capacity utilization (set in HTTP(S) load balancing configuration) that the autoscaler maintains. Must be a positive float value. If not defined, the default is 0.8.

AutoscalingPolicyResponse

CoolDownPeriodSec int

The number of seconds that the autoscaler waits before it starts collecting information from a new instance. This prevents the autoscaler from collecting information when the instance is initializing, during which the collected usage would not be reliable. The default time autoscaler waits is 60 seconds. Virtual machine initialization times might vary because of numerous factors. We recommend that you test how long an instance may take to initialize. To do this, create an instance and time the startup process.

CpuUtilization Pulumi.GoogleNative.Compute.Beta.Inputs.AutoscalingPolicyCpuUtilizationResponse

Defines the CPU utilization policy that allows the autoscaler to scale based on the average CPU utilization of a managed instance group.

CustomMetricUtilizations List<Pulumi.GoogleNative.Compute.Beta.Inputs.AutoscalingPolicyCustomMetricUtilizationResponse>

Configuration parameters of autoscaling based on a custom metric.

LoadBalancingUtilization Pulumi.GoogleNative.Compute.Beta.Inputs.AutoscalingPolicyLoadBalancingUtilizationResponse

Configuration parameters of autoscaling based on load balancer.

MaxNumReplicas int

The maximum number of instances that the autoscaler can scale out to. This is required when creating or updating an autoscaler. The maximum number of replicas must not be lower than minimal number of replicas.

MinNumReplicas int

The minimum number of replicas that the autoscaler can scale in to. This cannot be less than 0. If not provided, autoscaler chooses a default value depending on maximum number of instances allowed.

Mode string

Defines operating mode for this policy.

ScaleDownControl Pulumi.GoogleNative.Compute.Beta.Inputs.AutoscalingPolicyScaleDownControlResponse
ScaleInControl Pulumi.GoogleNative.Compute.Beta.Inputs.AutoscalingPolicyScaleInControlResponse
ScalingSchedules Dictionary<string, string>

Scaling schedules defined for an autoscaler. Multiple schedules can be set on an autoscaler, and they can overlap. During overlapping periods the greatest min_required_replicas of all scaling schedules is applied. Up to 128 scaling schedules are allowed.

CoolDownPeriodSec int

The number of seconds that the autoscaler waits before it starts collecting information from a new instance. This prevents the autoscaler from collecting information when the instance is initializing, during which the collected usage would not be reliable. The default time autoscaler waits is 60 seconds. Virtual machine initialization times might vary because of numerous factors. We recommend that you test how long an instance may take to initialize. To do this, create an instance and time the startup process.

CpuUtilization AutoscalingPolicyCpuUtilizationResponse

Defines the CPU utilization policy that allows the autoscaler to scale based on the average CPU utilization of a managed instance group.

CustomMetricUtilizations []AutoscalingPolicyCustomMetricUtilizationResponse

Configuration parameters of autoscaling based on a custom metric.

LoadBalancingUtilization AutoscalingPolicyLoadBalancingUtilizationResponse

Configuration parameters of autoscaling based on load balancer.

MaxNumReplicas int

The maximum number of instances that the autoscaler can scale out to. This is required when creating or updating an autoscaler. The maximum number of replicas must not be lower than minimal number of replicas.

MinNumReplicas int

The minimum number of replicas that the autoscaler can scale in to. This cannot be less than 0. If not provided, autoscaler chooses a default value depending on maximum number of instances allowed.

Mode string

Defines operating mode for this policy.

ScaleDownControl AutoscalingPolicyScaleDownControlResponse
ScaleInControl AutoscalingPolicyScaleInControlResponse
ScalingSchedules map[string]string

Scaling schedules defined for an autoscaler. Multiple schedules can be set on an autoscaler, and they can overlap. During overlapping periods the greatest min_required_replicas of all scaling schedules is applied. Up to 128 scaling schedules are allowed.

coolDownPeriodSec Integer

The number of seconds that the autoscaler waits before it starts collecting information from a new instance. This prevents the autoscaler from collecting information when the instance is initializing, during which the collected usage would not be reliable. The default time autoscaler waits is 60 seconds. Virtual machine initialization times might vary because of numerous factors. We recommend that you test how long an instance may take to initialize. To do this, create an instance and time the startup process.

cpuUtilization AutoscalingPolicyCpuUtilizationResponse

Defines the CPU utilization policy that allows the autoscaler to scale based on the average CPU utilization of a managed instance group.

customMetricUtilizations List<AutoscalingPolicyCustomMetricUtilizationResponse>

Configuration parameters of autoscaling based on a custom metric.

loadBalancingUtilization AutoscalingPolicyLoadBalancingUtilizationResponse

Configuration parameters of autoscaling based on load balancer.

maxNumReplicas Integer

The maximum number of instances that the autoscaler can scale out to. This is required when creating or updating an autoscaler. The maximum number of replicas must not be lower than minimal number of replicas.

minNumReplicas Integer

The minimum number of replicas that the autoscaler can scale in to. This cannot be less than 0. If not provided, autoscaler chooses a default value depending on maximum number of instances allowed.

mode String

Defines operating mode for this policy.

scaleDownControl AutoscalingPolicyScaleDownControlResponse
scaleInControl AutoscalingPolicyScaleInControlResponse
scalingSchedules Map<String,String>

Scaling schedules defined for an autoscaler. Multiple schedules can be set on an autoscaler, and they can overlap. During overlapping periods the greatest min_required_replicas of all scaling schedules is applied. Up to 128 scaling schedules are allowed.

coolDownPeriodSec number

The number of seconds that the autoscaler waits before it starts collecting information from a new instance. This prevents the autoscaler from collecting information when the instance is initializing, during which the collected usage would not be reliable. The default time autoscaler waits is 60 seconds. Virtual machine initialization times might vary because of numerous factors. We recommend that you test how long an instance may take to initialize. To do this, create an instance and time the startup process.

cpuUtilization AutoscalingPolicyCpuUtilizationResponse

Defines the CPU utilization policy that allows the autoscaler to scale based on the average CPU utilization of a managed instance group.

customMetricUtilizations AutoscalingPolicyCustomMetricUtilizationResponse[]

Configuration parameters of autoscaling based on a custom metric.

loadBalancingUtilization AutoscalingPolicyLoadBalancingUtilizationResponse

Configuration parameters of autoscaling based on load balancer.

maxNumReplicas number

The maximum number of instances that the autoscaler can scale out to. This is required when creating or updating an autoscaler. The maximum number of replicas must not be lower than minimal number of replicas.

minNumReplicas number

The minimum number of replicas that the autoscaler can scale in to. This cannot be less than 0. If not provided, autoscaler chooses a default value depending on maximum number of instances allowed.

mode string

Defines operating mode for this policy.

scaleDownControl AutoscalingPolicyScaleDownControlResponse
scaleInControl AutoscalingPolicyScaleInControlResponse
scalingSchedules {[key: string]: string}

Scaling schedules defined for an autoscaler. Multiple schedules can be set on an autoscaler, and they can overlap. During overlapping periods the greatest min_required_replicas of all scaling schedules is applied. Up to 128 scaling schedules are allowed.

cool_down_period_sec int

The number of seconds that the autoscaler waits before it starts collecting information from a new instance. This prevents the autoscaler from collecting information when the instance is initializing, during which the collected usage would not be reliable. The default time autoscaler waits is 60 seconds. Virtual machine initialization times might vary because of numerous factors. We recommend that you test how long an instance may take to initialize. To do this, create an instance and time the startup process.

cpu_utilization AutoscalingPolicyCpuUtilizationResponse

Defines the CPU utilization policy that allows the autoscaler to scale based on the average CPU utilization of a managed instance group.

custom_metric_utilizations Sequence[AutoscalingPolicyCustomMetricUtilizationResponse]

Configuration parameters of autoscaling based on a custom metric.

load_balancing_utilization AutoscalingPolicyLoadBalancingUtilizationResponse

Configuration parameters of autoscaling based on load balancer.

max_num_replicas int

The maximum number of instances that the autoscaler can scale out to. This is required when creating or updating an autoscaler. The maximum number of replicas must not be lower than minimal number of replicas.

min_num_replicas int

The minimum number of replicas that the autoscaler can scale in to. This cannot be less than 0. If not provided, autoscaler chooses a default value depending on maximum number of instances allowed.

mode str

Defines operating mode for this policy.

scale_down_control AutoscalingPolicyScaleDownControlResponse
scale_in_control AutoscalingPolicyScaleInControlResponse
scaling_schedules Mapping[str, str]

Scaling schedules defined for an autoscaler. Multiple schedules can be set on an autoscaler, and they can overlap. During overlapping periods the greatest min_required_replicas of all scaling schedules is applied. Up to 128 scaling schedules are allowed.

coolDownPeriodSec Number

The number of seconds that the autoscaler waits before it starts collecting information from a new instance. This prevents the autoscaler from collecting information when the instance is initializing, during which the collected usage would not be reliable. The default time autoscaler waits is 60 seconds. Virtual machine initialization times might vary because of numerous factors. We recommend that you test how long an instance may take to initialize. To do this, create an instance and time the startup process.

cpuUtilization Property Map

Defines the CPU utilization policy that allows the autoscaler to scale based on the average CPU utilization of a managed instance group.

customMetricUtilizations List<Property Map>

Configuration parameters of autoscaling based on a custom metric.

loadBalancingUtilization Property Map

Configuration parameters of autoscaling based on load balancer.

maxNumReplicas Number

The maximum number of instances that the autoscaler can scale out to. This is required when creating or updating an autoscaler. The maximum number of replicas must not be lower than minimal number of replicas.

minNumReplicas Number

The minimum number of replicas that the autoscaler can scale in to. This cannot be less than 0. If not provided, autoscaler chooses a default value depending on maximum number of instances allowed.

mode String

Defines operating mode for this policy.

scaleDownControl Property Map
scaleInControl Property Map
scalingSchedules Map<String>

Scaling schedules defined for an autoscaler. Multiple schedules can be set on an autoscaler, and they can overlap. During overlapping periods the greatest min_required_replicas of all scaling schedules is applied. Up to 128 scaling schedules are allowed.

AutoscalingPolicyScaleDownControlResponse

MaxScaledDownReplicas Pulumi.GoogleNative.Compute.Beta.Inputs.FixedOrPercentResponse

Maximum allowed number (or %) of VMs that can be deducted from the peak recommendation during the window autoscaler looks at when computing recommendations. Possibly all these VMs can be deleted at once so user service needs to be prepared to lose that many VMs in one step.

TimeWindowSec int

How far back autoscaling looks when computing recommendations to include directives regarding slower scale in, as described above.

MaxScaledDownReplicas FixedOrPercentResponse

Maximum allowed number (or %) of VMs that can be deducted from the peak recommendation during the window autoscaler looks at when computing recommendations. Possibly all these VMs can be deleted at once so user service needs to be prepared to lose that many VMs in one step.

TimeWindowSec int

How far back autoscaling looks when computing recommendations to include directives regarding slower scale in, as described above.

maxScaledDownReplicas FixedOrPercentResponse

Maximum allowed number (or %) of VMs that can be deducted from the peak recommendation during the window autoscaler looks at when computing recommendations. Possibly all these VMs can be deleted at once so user service needs to be prepared to lose that many VMs in one step.

timeWindowSec Integer

How far back autoscaling looks when computing recommendations to include directives regarding slower scale in, as described above.

maxScaledDownReplicas FixedOrPercentResponse

Maximum allowed number (or %) of VMs that can be deducted from the peak recommendation during the window autoscaler looks at when computing recommendations. Possibly all these VMs can be deleted at once so user service needs to be prepared to lose that many VMs in one step.

timeWindowSec number

How far back autoscaling looks when computing recommendations to include directives regarding slower scale in, as described above.

max_scaled_down_replicas FixedOrPercentResponse

Maximum allowed number (or %) of VMs that can be deducted from the peak recommendation during the window autoscaler looks at when computing recommendations. Possibly all these VMs can be deleted at once so user service needs to be prepared to lose that many VMs in one step.

time_window_sec int

How far back autoscaling looks when computing recommendations to include directives regarding slower scale in, as described above.

maxScaledDownReplicas Property Map

Maximum allowed number (or %) of VMs that can be deducted from the peak recommendation during the window autoscaler looks at when computing recommendations. Possibly all these VMs can be deleted at once so user service needs to be prepared to lose that many VMs in one step.

timeWindowSec Number

How far back autoscaling looks when computing recommendations to include directives regarding slower scale in, as described above.

AutoscalingPolicyScaleInControlResponse

MaxScaledInReplicas Pulumi.GoogleNative.Compute.Beta.Inputs.FixedOrPercentResponse

Maximum allowed number (or %) of VMs that can be deducted from the peak recommendation during the window autoscaler looks at when computing recommendations. Possibly all these VMs can be deleted at once so user service needs to be prepared to lose that many VMs in one step.

TimeWindowSec int

How far back autoscaling looks when computing recommendations to include directives regarding slower scale in, as described above.

MaxScaledInReplicas FixedOrPercentResponse

Maximum allowed number (or %) of VMs that can be deducted from the peak recommendation during the window autoscaler looks at when computing recommendations. Possibly all these VMs can be deleted at once so user service needs to be prepared to lose that many VMs in one step.

TimeWindowSec int

How far back autoscaling looks when computing recommendations to include directives regarding slower scale in, as described above.

maxScaledInReplicas FixedOrPercentResponse

Maximum allowed number (or %) of VMs that can be deducted from the peak recommendation during the window autoscaler looks at when computing recommendations. Possibly all these VMs can be deleted at once so user service needs to be prepared to lose that many VMs in one step.

timeWindowSec Integer

How far back autoscaling looks when computing recommendations to include directives regarding slower scale in, as described above.

maxScaledInReplicas FixedOrPercentResponse

Maximum allowed number (or %) of VMs that can be deducted from the peak recommendation during the window autoscaler looks at when computing recommendations. Possibly all these VMs can be deleted at once so user service needs to be prepared to lose that many VMs in one step.

timeWindowSec number

How far back autoscaling looks when computing recommendations to include directives regarding slower scale in, as described above.

max_scaled_in_replicas FixedOrPercentResponse

Maximum allowed number (or %) of VMs that can be deducted from the peak recommendation during the window autoscaler looks at when computing recommendations. Possibly all these VMs can be deleted at once so user service needs to be prepared to lose that many VMs in one step.

time_window_sec int

How far back autoscaling looks when computing recommendations to include directives regarding slower scale in, as described above.

maxScaledInReplicas Property Map

Maximum allowed number (or %) of VMs that can be deducted from the peak recommendation during the window autoscaler looks at when computing recommendations. Possibly all these VMs can be deleted at once so user service needs to be prepared to lose that many VMs in one step.

timeWindowSec Number

How far back autoscaling looks when computing recommendations to include directives regarding slower scale in, as described above.

FixedOrPercentResponse

Calculated int

Absolute value of VM instances calculated based on the specific mode. - If the value is fixed, then the calculated value is equal to the fixed value. - If the value is a percent, then the calculated value is percent/100 * targetSize. For example, the calculated value of a 80% of a managed instance group with 150 instances would be (80/100 * 150) = 120 VM instances. If there is a remainder, the number is rounded.

Fixed int

Specifies a fixed number of VM instances. This must be a positive integer.

Percent int

Specifies a percentage of instances between 0 to 100%, inclusive. For example, specify 80 for 80%.

Calculated int

Absolute value of VM instances calculated based on the specific mode. - If the value is fixed, then the calculated value is equal to the fixed value. - If the value is a percent, then the calculated value is percent/100 * targetSize. For example, the calculated value of a 80% of a managed instance group with 150 instances would be (80/100 * 150) = 120 VM instances. If there is a remainder, the number is rounded.

Fixed int

Specifies a fixed number of VM instances. This must be a positive integer.

Percent int

Specifies a percentage of instances between 0 to 100%, inclusive. For example, specify 80 for 80%.

calculated Integer

Absolute value of VM instances calculated based on the specific mode. - If the value is fixed, then the calculated value is equal to the fixed value. - If the value is a percent, then the calculated value is percent/100 * targetSize. For example, the calculated value of a 80% of a managed instance group with 150 instances would be (80/100 * 150) = 120 VM instances. If there is a remainder, the number is rounded.

fixed Integer

Specifies a fixed number of VM instances. This must be a positive integer.

percent Integer

Specifies a percentage of instances between 0 to 100%, inclusive. For example, specify 80 for 80%.

calculated number

Absolute value of VM instances calculated based on the specific mode. - If the value is fixed, then the calculated value is equal to the fixed value. - If the value is a percent, then the calculated value is percent/100 * targetSize. For example, the calculated value of a 80% of a managed instance group with 150 instances would be (80/100 * 150) = 120 VM instances. If there is a remainder, the number is rounded.

fixed number

Specifies a fixed number of VM instances. This must be a positive integer.

percent number

Specifies a percentage of instances between 0 to 100%, inclusive. For example, specify 80 for 80%.

calculated int

Absolute value of VM instances calculated based on the specific mode. - If the value is fixed, then the calculated value is equal to the fixed value. - If the value is a percent, then the calculated value is percent/100 * targetSize. For example, the calculated value of a 80% of a managed instance group with 150 instances would be (80/100 * 150) = 120 VM instances. If there is a remainder, the number is rounded.

fixed int

Specifies a fixed number of VM instances. This must be a positive integer.

percent int

Specifies a percentage of instances between 0 to 100%, inclusive. For example, specify 80 for 80%.

calculated Number

Absolute value of VM instances calculated based on the specific mode. - If the value is fixed, then the calculated value is equal to the fixed value. - If the value is a percent, then the calculated value is percent/100 * targetSize. For example, the calculated value of a 80% of a managed instance group with 150 instances would be (80/100 * 150) = 120 VM instances. If there is a remainder, the number is rounded.

fixed Number

Specifies a fixed number of VM instances. This must be a positive integer.

percent Number

Specifies a percentage of instances between 0 to 100%, inclusive. For example, specify 80 for 80%.

Package Details

Repository
https://github.com/pulumi/pulumi-google-native
License
Apache-2.0