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
google-native.dataproc/v1beta2.getAutoscalingPolicy
Explore with Pulumi AI
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
Retrieves autoscaling policy.
Using getAutoscalingPolicy
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 getAutoscalingPolicy(args: GetAutoscalingPolicyArgs, opts?: InvokeOptions): Promise<GetAutoscalingPolicyResult>
function getAutoscalingPolicyOutput(args: GetAutoscalingPolicyOutputArgs, opts?: InvokeOptions): Output<GetAutoscalingPolicyResult>
def get_autoscaling_policy(autoscaling_policy_id: Optional[str] = None,
location: Optional[str] = None,
project: Optional[str] = None,
opts: Optional[InvokeOptions] = None) -> GetAutoscalingPolicyResult
def get_autoscaling_policy_output(autoscaling_policy_id: Optional[pulumi.Input[str]] = None,
location: Optional[pulumi.Input[str]] = None,
project: Optional[pulumi.Input[str]] = None,
opts: Optional[InvokeOptions] = None) -> Output[GetAutoscalingPolicyResult]
func LookupAutoscalingPolicy(ctx *Context, args *LookupAutoscalingPolicyArgs, opts ...InvokeOption) (*LookupAutoscalingPolicyResult, error)
func LookupAutoscalingPolicyOutput(ctx *Context, args *LookupAutoscalingPolicyOutputArgs, opts ...InvokeOption) LookupAutoscalingPolicyResultOutput
> Note: This function is named LookupAutoscalingPolicy
in the Go SDK.
public static class GetAutoscalingPolicy
{
public static Task<GetAutoscalingPolicyResult> InvokeAsync(GetAutoscalingPolicyArgs args, InvokeOptions? opts = null)
public static Output<GetAutoscalingPolicyResult> Invoke(GetAutoscalingPolicyInvokeArgs args, InvokeOptions? opts = null)
}
public static CompletableFuture<GetAutoscalingPolicyResult> getAutoscalingPolicy(GetAutoscalingPolicyArgs args, InvokeOptions options)
// Output-based functions aren't available in Java yet
fn::invoke:
function: google-native:dataproc/v1beta2:getAutoscalingPolicy
arguments:
# arguments dictionary
The following arguments are supported:
- Autoscaling
Policy stringId - Location string
- Project string
- Autoscaling
Policy stringId - Location string
- Project string
- autoscaling
Policy StringId - location String
- project String
- autoscaling
Policy stringId - location string
- project string
- autoscaling_
policy_ strid - location str
- project str
- autoscaling
Policy StringId - location String
- project String
getAutoscalingPolicy Result
The following output properties are available:
- Basic
Algorithm Pulumi.Google Native. Dataproc. V1Beta2. Outputs. Basic Autoscaling Algorithm Response - Name string
- The "resource name" of the autoscaling policy, as described in https://cloud.google.com/apis/design/resource_names. For projects.regions.autoscalingPolicies, the resource name of the policy has the following format: projects/{project_id}/regions/{region}/autoscalingPolicies/{policy_id} For projects.locations.autoscalingPolicies, the resource name of the policy has the following format: projects/{project_id}/locations/{location}/autoscalingPolicies/{policy_id}
- Secondary
Worker Pulumi.Config Google Native. Dataproc. V1Beta2. Outputs. Instance Group Autoscaling Policy Config Response - Optional. Describes how the autoscaler will operate for secondary workers.
- Worker
Config Pulumi.Google Native. Dataproc. V1Beta2. Outputs. Instance Group Autoscaling Policy Config Response - Describes how the autoscaler will operate for primary workers.
- Basic
Algorithm BasicAutoscaling Algorithm Response - Name string
- The "resource name" of the autoscaling policy, as described in https://cloud.google.com/apis/design/resource_names. For projects.regions.autoscalingPolicies, the resource name of the policy has the following format: projects/{project_id}/regions/{region}/autoscalingPolicies/{policy_id} For projects.locations.autoscalingPolicies, the resource name of the policy has the following format: projects/{project_id}/locations/{location}/autoscalingPolicies/{policy_id}
- Secondary
Worker InstanceConfig Group Autoscaling Policy Config Response - Optional. Describes how the autoscaler will operate for secondary workers.
- Worker
Config InstanceGroup Autoscaling Policy Config Response - Describes how the autoscaler will operate for primary workers.
- basic
Algorithm BasicAutoscaling Algorithm Response - name String
- The "resource name" of the autoscaling policy, as described in https://cloud.google.com/apis/design/resource_names. For projects.regions.autoscalingPolicies, the resource name of the policy has the following format: projects/{project_id}/regions/{region}/autoscalingPolicies/{policy_id} For projects.locations.autoscalingPolicies, the resource name of the policy has the following format: projects/{project_id}/locations/{location}/autoscalingPolicies/{policy_id}
- secondary
Worker InstanceConfig Group Autoscaling Policy Config Response - Optional. Describes how the autoscaler will operate for secondary workers.
- worker
Config InstanceGroup Autoscaling Policy Config Response - Describes how the autoscaler will operate for primary workers.
- basic
Algorithm BasicAutoscaling Algorithm Response - name string
- The "resource name" of the autoscaling policy, as described in https://cloud.google.com/apis/design/resource_names. For projects.regions.autoscalingPolicies, the resource name of the policy has the following format: projects/{project_id}/regions/{region}/autoscalingPolicies/{policy_id} For projects.locations.autoscalingPolicies, the resource name of the policy has the following format: projects/{project_id}/locations/{location}/autoscalingPolicies/{policy_id}
- secondary
Worker InstanceConfig Group Autoscaling Policy Config Response - Optional. Describes how the autoscaler will operate for secondary workers.
- worker
Config InstanceGroup Autoscaling Policy Config Response - Describes how the autoscaler will operate for primary workers.
- basic_
algorithm BasicAutoscaling Algorithm Response - name str
- The "resource name" of the autoscaling policy, as described in https://cloud.google.com/apis/design/resource_names. For projects.regions.autoscalingPolicies, the resource name of the policy has the following format: projects/{project_id}/regions/{region}/autoscalingPolicies/{policy_id} For projects.locations.autoscalingPolicies, the resource name of the policy has the following format: projects/{project_id}/locations/{location}/autoscalingPolicies/{policy_id}
- secondary_
worker_ Instanceconfig Group Autoscaling Policy Config Response - Optional. Describes how the autoscaler will operate for secondary workers.
- worker_
config InstanceGroup Autoscaling Policy Config Response - Describes how the autoscaler will operate for primary workers.
- basic
Algorithm Property Map - name String
- The "resource name" of the autoscaling policy, as described in https://cloud.google.com/apis/design/resource_names. For projects.regions.autoscalingPolicies, the resource name of the policy has the following format: projects/{project_id}/regions/{region}/autoscalingPolicies/{policy_id} For projects.locations.autoscalingPolicies, the resource name of the policy has the following format: projects/{project_id}/locations/{location}/autoscalingPolicies/{policy_id}
- secondary
Worker Property MapConfig - Optional. Describes how the autoscaler will operate for secondary workers.
- worker
Config Property Map - Describes how the autoscaler will operate for primary workers.
Supporting Types
BasicAutoscalingAlgorithmResponse
- Cooldown
Period string - Optional. Duration between scaling events. A scaling period starts after the update operation from the previous event has completed.Bounds: 2m, 1d. Default: 2m.
- Yarn
Config Pulumi.Google Native. Dataproc. V1Beta2. Inputs. Basic Yarn Autoscaling Config Response - Optional. YARN autoscaling configuration.
- Cooldown
Period string - Optional. Duration between scaling events. A scaling period starts after the update operation from the previous event has completed.Bounds: 2m, 1d. Default: 2m.
- Yarn
Config BasicYarn Autoscaling Config Response - Optional. YARN autoscaling configuration.
- cooldown
Period String - Optional. Duration between scaling events. A scaling period starts after the update operation from the previous event has completed.Bounds: 2m, 1d. Default: 2m.
- yarn
Config BasicYarn Autoscaling Config Response - Optional. YARN autoscaling configuration.
- cooldown
Period string - Optional. Duration between scaling events. A scaling period starts after the update operation from the previous event has completed.Bounds: 2m, 1d. Default: 2m.
- yarn
Config BasicYarn Autoscaling Config Response - Optional. YARN autoscaling configuration.
- cooldown_
period str - Optional. Duration between scaling events. A scaling period starts after the update operation from the previous event has completed.Bounds: 2m, 1d. Default: 2m.
- yarn_
config BasicYarn Autoscaling Config Response - Optional. YARN autoscaling configuration.
- cooldown
Period String - Optional. Duration between scaling events. A scaling period starts after the update operation from the previous event has completed.Bounds: 2m, 1d. Default: 2m.
- yarn
Config Property Map - Optional. YARN autoscaling configuration.
BasicYarnAutoscalingConfigResponse
- Graceful
Decommission stringTimeout - Timeout for YARN graceful decommissioning of Node Managers. Specifies the duration to wait for jobs to complete before forcefully removing workers (and potentially interrupting jobs). Only applicable to downscaling operations.Bounds: 0s, 1d.
- Scale
Down doubleFactor - Fraction of average YARN pending memory in the last cooldown period for which to remove workers. A scale-down factor of 1 will result in scaling down so that there is no available memory remaining after the update (more aggressive scaling). A scale-down factor of 0 disables removing workers, which can be beneficial for autoscaling a single job. See How autoscaling works for more information.Bounds: 0.0, 1.0.
- Scale
Down doubleMin Worker Fraction - Optional. Minimum scale-down threshold as a fraction of total cluster size before scaling occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must recommend at least a 2 worker scale-down for the cluster to scale. A threshold of 0 means the autoscaler will scale down on any recommended change.Bounds: 0.0, 1.0. Default: 0.0.
- Scale
Up doubleFactor - Fraction of average YARN pending memory in the last cooldown period for which to add workers. A scale-up factor of 1.0 will result in scaling up so that there is no pending memory remaining after the update (more aggressive scaling). A scale-up factor closer to 0 will result in a smaller magnitude of scaling up (less aggressive scaling). See How autoscaling works for more information.Bounds: 0.0, 1.0.
- Scale
Up doubleMin Worker Fraction - Optional. Minimum scale-up threshold as a fraction of total cluster size before scaling occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must recommend at least a 2-worker scale-up for the cluster to scale. A threshold of 0 means the autoscaler will scale up on any recommended change.Bounds: 0.0, 1.0. Default: 0.0.
- Graceful
Decommission stringTimeout - Timeout for YARN graceful decommissioning of Node Managers. Specifies the duration to wait for jobs to complete before forcefully removing workers (and potentially interrupting jobs). Only applicable to downscaling operations.Bounds: 0s, 1d.
- Scale
Down float64Factor - Fraction of average YARN pending memory in the last cooldown period for which to remove workers. A scale-down factor of 1 will result in scaling down so that there is no available memory remaining after the update (more aggressive scaling). A scale-down factor of 0 disables removing workers, which can be beneficial for autoscaling a single job. See How autoscaling works for more information.Bounds: 0.0, 1.0.
- Scale
Down float64Min Worker Fraction - Optional. Minimum scale-down threshold as a fraction of total cluster size before scaling occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must recommend at least a 2 worker scale-down for the cluster to scale. A threshold of 0 means the autoscaler will scale down on any recommended change.Bounds: 0.0, 1.0. Default: 0.0.
- Scale
Up float64Factor - Fraction of average YARN pending memory in the last cooldown period for which to add workers. A scale-up factor of 1.0 will result in scaling up so that there is no pending memory remaining after the update (more aggressive scaling). A scale-up factor closer to 0 will result in a smaller magnitude of scaling up (less aggressive scaling). See How autoscaling works for more information.Bounds: 0.0, 1.0.
- Scale
Up float64Min Worker Fraction - Optional. Minimum scale-up threshold as a fraction of total cluster size before scaling occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must recommend at least a 2-worker scale-up for the cluster to scale. A threshold of 0 means the autoscaler will scale up on any recommended change.Bounds: 0.0, 1.0. Default: 0.0.
- graceful
Decommission StringTimeout - Timeout for YARN graceful decommissioning of Node Managers. Specifies the duration to wait for jobs to complete before forcefully removing workers (and potentially interrupting jobs). Only applicable to downscaling operations.Bounds: 0s, 1d.
- scale
Down DoubleFactor - Fraction of average YARN pending memory in the last cooldown period for which to remove workers. A scale-down factor of 1 will result in scaling down so that there is no available memory remaining after the update (more aggressive scaling). A scale-down factor of 0 disables removing workers, which can be beneficial for autoscaling a single job. See How autoscaling works for more information.Bounds: 0.0, 1.0.
- scale
Down DoubleMin Worker Fraction - Optional. Minimum scale-down threshold as a fraction of total cluster size before scaling occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must recommend at least a 2 worker scale-down for the cluster to scale. A threshold of 0 means the autoscaler will scale down on any recommended change.Bounds: 0.0, 1.0. Default: 0.0.
- scale
Up DoubleFactor - Fraction of average YARN pending memory in the last cooldown period for which to add workers. A scale-up factor of 1.0 will result in scaling up so that there is no pending memory remaining after the update (more aggressive scaling). A scale-up factor closer to 0 will result in a smaller magnitude of scaling up (less aggressive scaling). See How autoscaling works for more information.Bounds: 0.0, 1.0.
- scale
Up DoubleMin Worker Fraction - Optional. Minimum scale-up threshold as a fraction of total cluster size before scaling occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must recommend at least a 2-worker scale-up for the cluster to scale. A threshold of 0 means the autoscaler will scale up on any recommended change.Bounds: 0.0, 1.0. Default: 0.0.
- graceful
Decommission stringTimeout - Timeout for YARN graceful decommissioning of Node Managers. Specifies the duration to wait for jobs to complete before forcefully removing workers (and potentially interrupting jobs). Only applicable to downscaling operations.Bounds: 0s, 1d.
- scale
Down numberFactor - Fraction of average YARN pending memory in the last cooldown period for which to remove workers. A scale-down factor of 1 will result in scaling down so that there is no available memory remaining after the update (more aggressive scaling). A scale-down factor of 0 disables removing workers, which can be beneficial for autoscaling a single job. See How autoscaling works for more information.Bounds: 0.0, 1.0.
- scale
Down numberMin Worker Fraction - Optional. Minimum scale-down threshold as a fraction of total cluster size before scaling occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must recommend at least a 2 worker scale-down for the cluster to scale. A threshold of 0 means the autoscaler will scale down on any recommended change.Bounds: 0.0, 1.0. Default: 0.0.
- scale
Up numberFactor - Fraction of average YARN pending memory in the last cooldown period for which to add workers. A scale-up factor of 1.0 will result in scaling up so that there is no pending memory remaining after the update (more aggressive scaling). A scale-up factor closer to 0 will result in a smaller magnitude of scaling up (less aggressive scaling). See How autoscaling works for more information.Bounds: 0.0, 1.0.
- scale
Up numberMin Worker Fraction - Optional. Minimum scale-up threshold as a fraction of total cluster size before scaling occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must recommend at least a 2-worker scale-up for the cluster to scale. A threshold of 0 means the autoscaler will scale up on any recommended change.Bounds: 0.0, 1.0. Default: 0.0.
- graceful_
decommission_ strtimeout - Timeout for YARN graceful decommissioning of Node Managers. Specifies the duration to wait for jobs to complete before forcefully removing workers (and potentially interrupting jobs). Only applicable to downscaling operations.Bounds: 0s, 1d.
- scale_
down_ floatfactor - Fraction of average YARN pending memory in the last cooldown period for which to remove workers. A scale-down factor of 1 will result in scaling down so that there is no available memory remaining after the update (more aggressive scaling). A scale-down factor of 0 disables removing workers, which can be beneficial for autoscaling a single job. See How autoscaling works for more information.Bounds: 0.0, 1.0.
- scale_
down_ floatmin_ worker_ fraction - Optional. Minimum scale-down threshold as a fraction of total cluster size before scaling occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must recommend at least a 2 worker scale-down for the cluster to scale. A threshold of 0 means the autoscaler will scale down on any recommended change.Bounds: 0.0, 1.0. Default: 0.0.
- scale_
up_ floatfactor - Fraction of average YARN pending memory in the last cooldown period for which to add workers. A scale-up factor of 1.0 will result in scaling up so that there is no pending memory remaining after the update (more aggressive scaling). A scale-up factor closer to 0 will result in a smaller magnitude of scaling up (less aggressive scaling). See How autoscaling works for more information.Bounds: 0.0, 1.0.
- scale_
up_ floatmin_ worker_ fraction - Optional. Minimum scale-up threshold as a fraction of total cluster size before scaling occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must recommend at least a 2-worker scale-up for the cluster to scale. A threshold of 0 means the autoscaler will scale up on any recommended change.Bounds: 0.0, 1.0. Default: 0.0.
- graceful
Decommission StringTimeout - Timeout for YARN graceful decommissioning of Node Managers. Specifies the duration to wait for jobs to complete before forcefully removing workers (and potentially interrupting jobs). Only applicable to downscaling operations.Bounds: 0s, 1d.
- scale
Down NumberFactor - Fraction of average YARN pending memory in the last cooldown period for which to remove workers. A scale-down factor of 1 will result in scaling down so that there is no available memory remaining after the update (more aggressive scaling). A scale-down factor of 0 disables removing workers, which can be beneficial for autoscaling a single job. See How autoscaling works for more information.Bounds: 0.0, 1.0.
- scale
Down NumberMin Worker Fraction - Optional. Minimum scale-down threshold as a fraction of total cluster size before scaling occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must recommend at least a 2 worker scale-down for the cluster to scale. A threshold of 0 means the autoscaler will scale down on any recommended change.Bounds: 0.0, 1.0. Default: 0.0.
- scale
Up NumberFactor - Fraction of average YARN pending memory in the last cooldown period for which to add workers. A scale-up factor of 1.0 will result in scaling up so that there is no pending memory remaining after the update (more aggressive scaling). A scale-up factor closer to 0 will result in a smaller magnitude of scaling up (less aggressive scaling). See How autoscaling works for more information.Bounds: 0.0, 1.0.
- scale
Up NumberMin Worker Fraction - Optional. Minimum scale-up threshold as a fraction of total cluster size before scaling occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must recommend at least a 2-worker scale-up for the cluster to scale. A threshold of 0 means the autoscaler will scale up on any recommended change.Bounds: 0.0, 1.0. Default: 0.0.
InstanceGroupAutoscalingPolicyConfigResponse
- Max
Instances int - Optional. Maximum number of instances for this group. Required for primary workers. Note that by default, clusters will not use secondary workers. Required for secondary workers if the minimum secondary instances is set.Primary workers - Bounds: [min_instances, ). Required. Secondary workers - Bounds: [min_instances, ). Default: 0.
- Min
Instances int - Optional. Minimum number of instances for this group.Primary workers - Bounds: 2, max_instances. Default: 2. Secondary workers - Bounds: 0, max_instances. Default: 0.
- Weight int
- Optional. Weight for the instance group, which is used to determine the fraction of total workers in the cluster from this instance group. For example, if primary workers have weight 2, and secondary workers have weight 1, the cluster will have approximately 2 primary workers for each secondary worker.The cluster may not reach the specified balance if constrained by min/max bounds or other autoscaling settings. For example, if max_instances for secondary workers is 0, then only primary workers will be added. The cluster can also be out of balance when created.If weight is not set on any instance group, the cluster will default to equal weight for all groups: the cluster will attempt to maintain an equal number of workers in each group within the configured size bounds for each group. If weight is set for one group only, the cluster will default to zero weight on the unset group. For example if weight is set only on primary workers, the cluster will use primary workers only and no secondary workers.
- Max
Instances int - Optional. Maximum number of instances for this group. Required for primary workers. Note that by default, clusters will not use secondary workers. Required for secondary workers if the minimum secondary instances is set.Primary workers - Bounds: [min_instances, ). Required. Secondary workers - Bounds: [min_instances, ). Default: 0.
- Min
Instances int - Optional. Minimum number of instances for this group.Primary workers - Bounds: 2, max_instances. Default: 2. Secondary workers - Bounds: 0, max_instances. Default: 0.
- Weight int
- Optional. Weight for the instance group, which is used to determine the fraction of total workers in the cluster from this instance group. For example, if primary workers have weight 2, and secondary workers have weight 1, the cluster will have approximately 2 primary workers for each secondary worker.The cluster may not reach the specified balance if constrained by min/max bounds or other autoscaling settings. For example, if max_instances for secondary workers is 0, then only primary workers will be added. The cluster can also be out of balance when created.If weight is not set on any instance group, the cluster will default to equal weight for all groups: the cluster will attempt to maintain an equal number of workers in each group within the configured size bounds for each group. If weight is set for one group only, the cluster will default to zero weight on the unset group. For example if weight is set only on primary workers, the cluster will use primary workers only and no secondary workers.
- max
Instances Integer - Optional. Maximum number of instances for this group. Required for primary workers. Note that by default, clusters will not use secondary workers. Required for secondary workers if the minimum secondary instances is set.Primary workers - Bounds: [min_instances, ). Required. Secondary workers - Bounds: [min_instances, ). Default: 0.
- min
Instances Integer - Optional. Minimum number of instances for this group.Primary workers - Bounds: 2, max_instances. Default: 2. Secondary workers - Bounds: 0, max_instances. Default: 0.
- weight Integer
- Optional. Weight for the instance group, which is used to determine the fraction of total workers in the cluster from this instance group. For example, if primary workers have weight 2, and secondary workers have weight 1, the cluster will have approximately 2 primary workers for each secondary worker.The cluster may not reach the specified balance if constrained by min/max bounds or other autoscaling settings. For example, if max_instances for secondary workers is 0, then only primary workers will be added. The cluster can also be out of balance when created.If weight is not set on any instance group, the cluster will default to equal weight for all groups: the cluster will attempt to maintain an equal number of workers in each group within the configured size bounds for each group. If weight is set for one group only, the cluster will default to zero weight on the unset group. For example if weight is set only on primary workers, the cluster will use primary workers only and no secondary workers.
- max
Instances number - Optional. Maximum number of instances for this group. Required for primary workers. Note that by default, clusters will not use secondary workers. Required for secondary workers if the minimum secondary instances is set.Primary workers - Bounds: [min_instances, ). Required. Secondary workers - Bounds: [min_instances, ). Default: 0.
- min
Instances number - Optional. Minimum number of instances for this group.Primary workers - Bounds: 2, max_instances. Default: 2. Secondary workers - Bounds: 0, max_instances. Default: 0.
- weight number
- Optional. Weight for the instance group, which is used to determine the fraction of total workers in the cluster from this instance group. For example, if primary workers have weight 2, and secondary workers have weight 1, the cluster will have approximately 2 primary workers for each secondary worker.The cluster may not reach the specified balance if constrained by min/max bounds or other autoscaling settings. For example, if max_instances for secondary workers is 0, then only primary workers will be added. The cluster can also be out of balance when created.If weight is not set on any instance group, the cluster will default to equal weight for all groups: the cluster will attempt to maintain an equal number of workers in each group within the configured size bounds for each group. If weight is set for one group only, the cluster will default to zero weight on the unset group. For example if weight is set only on primary workers, the cluster will use primary workers only and no secondary workers.
- max_
instances int - Optional. Maximum number of instances for this group. Required for primary workers. Note that by default, clusters will not use secondary workers. Required for secondary workers if the minimum secondary instances is set.Primary workers - Bounds: [min_instances, ). Required. Secondary workers - Bounds: [min_instances, ). Default: 0.
- min_
instances int - Optional. Minimum number of instances for this group.Primary workers - Bounds: 2, max_instances. Default: 2. Secondary workers - Bounds: 0, max_instances. Default: 0.
- weight int
- Optional. Weight for the instance group, which is used to determine the fraction of total workers in the cluster from this instance group. For example, if primary workers have weight 2, and secondary workers have weight 1, the cluster will have approximately 2 primary workers for each secondary worker.The cluster may not reach the specified balance if constrained by min/max bounds or other autoscaling settings. For example, if max_instances for secondary workers is 0, then only primary workers will be added. The cluster can also be out of balance when created.If weight is not set on any instance group, the cluster will default to equal weight for all groups: the cluster will attempt to maintain an equal number of workers in each group within the configured size bounds for each group. If weight is set for one group only, the cluster will default to zero weight on the unset group. For example if weight is set only on primary workers, the cluster will use primary workers only and no secondary workers.
- max
Instances Number - Optional. Maximum number of instances for this group. Required for primary workers. Note that by default, clusters will not use secondary workers. Required for secondary workers if the minimum secondary instances is set.Primary workers - Bounds: [min_instances, ). Required. Secondary workers - Bounds: [min_instances, ). Default: 0.
- min
Instances Number - Optional. Minimum number of instances for this group.Primary workers - Bounds: 2, max_instances. Default: 2. Secondary workers - Bounds: 0, max_instances. Default: 0.
- weight Number
- Optional. Weight for the instance group, which is used to determine the fraction of total workers in the cluster from this instance group. For example, if primary workers have weight 2, and secondary workers have weight 1, the cluster will have approximately 2 primary workers for each secondary worker.The cluster may not reach the specified balance if constrained by min/max bounds or other autoscaling settings. For example, if max_instances for secondary workers is 0, then only primary workers will be added. The cluster can also be out of balance when created.If weight is not set on any instance group, the cluster will default to equal weight for all groups: the cluster will attempt to maintain an equal number of workers in each group within the configured size bounds for each group. If weight is set for one group only, the cluster will default to zero weight on the unset group. For example if weight is set only on primary workers, the cluster will use primary workers only and no secondary workers.
Package Details
- Repository
- Google Cloud Native pulumi/pulumi-google-native
- License
- Apache-2.0
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