RegisterScalableTargetFluentBuilder

aws_sdk_applicationautoscaling::operation::register_scalable_target::builders

Struct RegisterScalableTargetFluentBuilder 

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pub struct RegisterScalableTargetFluentBuilder { /* private fields */ }
Expand description

Fluent builder constructing a request to RegisterScalableTarget.

Registers or updates a scalable target, which is the resource that you want to scale.

Scalable targets are uniquely identified by the combination of resource ID, scalable dimension, and namespace, which represents some capacity dimension of the underlying service.

When you register a new scalable target, you must specify values for the minimum and maximum capacity. If the specified resource is not active in the target service, this operation does not change the resource's current capacity. Otherwise, it changes the resource's current capacity to a value that is inside of this range.

If you add a scaling policy, current capacity is adjustable within the specified range when scaling starts. Application Auto Scaling scaling policies will not scale capacity to values that are outside of the minimum and maximum range.

After you register a scalable target, you do not need to register it again to use other Application Auto Scaling operations. To see which resources have been registered, use DescribeScalableTargets. You can also view the scaling policies for a service namespace by using DescribeScalableTargets. If you no longer need a scalable target, you can deregister it by using DeregisterScalableTarget.

To update a scalable target, specify the parameters that you want to change. Include the parameters that identify the scalable target: resource ID, scalable dimension, and namespace. Any parameters that you don't specify are not changed by this update request.

If you call the RegisterScalableTarget API operation to create a scalable target, there might be a brief delay until the operation achieves eventual consistency. You might become aware of this brief delay if you get unexpected errors when performing sequential operations. The typical strategy is to retry the request, and some Amazon Web Services SDKs include automatic backoff and retry logic.

If you call the RegisterScalableTarget API operation to update an existing scalable target, Application Auto Scaling retrieves the current capacity of the resource. If it's below the minimum capacity or above the maximum capacity, Application Auto Scaling adjusts the capacity of the scalable target to place it within these bounds, even if you don't include the MinCapacity or MaxCapacity request parameters.

Implementations§

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impl RegisterScalableTargetFluentBuilder

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pub fn as_input(&self) -> &RegisterScalableTargetInputBuilder

Access the RegisterScalableTarget as a reference.

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pub async fn send( self, ) -> Result<RegisterScalableTargetOutput, SdkError<RegisterScalableTargetError, HttpResponse>>

Sends the request and returns the response.

If an error occurs, an SdkError will be returned with additional details that can be matched against.

By default, any retryable failures will be retried twice. Retry behavior is configurable with the RetryConfig, which can be set when configuring the client.

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pub fn customize( self, ) -> CustomizableOperation<RegisterScalableTargetOutput, RegisterScalableTargetError, Self>

Consumes this builder, creating a customizable operation that can be modified before being sent.

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pub fn service_namespace(self, input: ServiceNamespace) -> Self

The namespace of the Amazon Web Services service that provides the resource. For a resource provided by your own application or service, use custom-resource instead.

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pub fn set_service_namespace(self, input: Option<ServiceNamespace>) -> Self

The namespace of the Amazon Web Services service that provides the resource. For a resource provided by your own application or service, use custom-resource instead.

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pub fn get_service_namespace(&self) -> &Option<ServiceNamespace>

The namespace of the Amazon Web Services service that provides the resource. For a resource provided by your own application or service, use custom-resource instead.

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pub fn resource_id(self, input: impl Into<String>) -> Self

The identifier of the resource that is associated with the scalable target. This string consists of the resource type and unique identifier.

  • ECS service - The resource type is service and the unique identifier is the cluster name and service name. Example: service/my-cluster/my-service.

  • Spot Fleet - The resource type is spot-fleet-request and the unique identifier is the Spot Fleet request ID. Example: spot-fleet-request/sfr-73fbd2ce-aa30-494c-8788-1cee4EXAMPLE.

  • EMR cluster - The resource type is instancegroup and the unique identifier is the cluster ID and instance group ID. Example: instancegroup/j-2EEZNYKUA1NTV/ig-1791Y4E1L8YI0.

  • AppStream 2.0 fleet - The resource type is fleet and the unique identifier is the fleet name. Example: fleet/sample-fleet.

  • DynamoDB table - The resource type is table and the unique identifier is the table name. Example: table/my-table.

  • DynamoDB global secondary index - The resource type is index and the unique identifier is the index name. Example: table/my-table/index/my-table-index.

  • Aurora DB cluster - The resource type is cluster and the unique identifier is the cluster name. Example: cluster:my-db-cluster.

  • SageMaker endpoint variant - The resource type is variant and the unique identifier is the resource ID. Example: endpoint/my-end-point/variant/KMeansClustering.

  • Custom resources are not supported with a resource type. This parameter must specify the OutputValue from the CloudFormation template stack used to access the resources. The unique identifier is defined by the service provider. More information is available in our GitHub repository.

  • Amazon Comprehend document classification endpoint - The resource type and unique identifier are specified using the endpoint ARN. Example: arn:aws:comprehend:us-west-2:123456789012:document-classifier-endpoint/EXAMPLE.

  • Amazon Comprehend entity recognizer endpoint - The resource type and unique identifier are specified using the endpoint ARN. Example: arn:aws:comprehend:us-west-2:123456789012:entity-recognizer-endpoint/EXAMPLE.

  • Lambda provisioned concurrency - The resource type is function and the unique identifier is the function name with a function version or alias name suffix that is not $LATEST. Example: function:my-function:prod or function:my-function:1.

  • Amazon Keyspaces table - The resource type is table and the unique identifier is the table name. Example: keyspace/mykeyspace/table/mytable.

  • Amazon MSK cluster - The resource type and unique identifier are specified using the cluster ARN. Example: arn:aws:kafka:us-east-1:123456789012:cluster/demo-cluster-1/6357e0b2-0e6a-4b86-a0b4-70df934c2e31-5.

  • Amazon ElastiCache replication group - The resource type is replication-group and the unique identifier is the replication group name. Example: replication-group/mycluster.

  • Amazon ElastiCache cache cluster - The resource type is cache-cluster and the unique identifier is the cache cluster name. Example: cache-cluster/mycluster.

  • Neptune cluster - The resource type is cluster and the unique identifier is the cluster name. Example: cluster:mycluster.

  • SageMaker serverless endpoint - The resource type is variant and the unique identifier is the resource ID. Example: endpoint/my-end-point/variant/KMeansClustering.

  • SageMaker inference component - The resource type is inference-component and the unique identifier is the resource ID. Example: inference-component/my-inference-component.

  • Pool of WorkSpaces - The resource type is workspacespool and the unique identifier is the pool ID. Example: workspacespool/wspool-123456.

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pub fn set_resource_id(self, input: Option<String>) -> Self

The identifier of the resource that is associated with the scalable target. This string consists of the resource type and unique identifier.

  • ECS service - The resource type is service and the unique identifier is the cluster name and service name. Example: service/my-cluster/my-service.

  • Spot Fleet - The resource type is spot-fleet-request and the unique identifier is the Spot Fleet request ID. Example: spot-fleet-request/sfr-73fbd2ce-aa30-494c-8788-1cee4EXAMPLE.

  • EMR cluster - The resource type is instancegroup and the unique identifier is the cluster ID and instance group ID. Example: instancegroup/j-2EEZNYKUA1NTV/ig-1791Y4E1L8YI0.

  • AppStream 2.0 fleet - The resource type is fleet and the unique identifier is the fleet name. Example: fleet/sample-fleet.

  • DynamoDB table - The resource type is table and the unique identifier is the table name. Example: table/my-table.

  • DynamoDB global secondary index - The resource type is index and the unique identifier is the index name. Example: table/my-table/index/my-table-index.

  • Aurora DB cluster - The resource type is cluster and the unique identifier is the cluster name. Example: cluster:my-db-cluster.

  • SageMaker endpoint variant - The resource type is variant and the unique identifier is the resource ID. Example: endpoint/my-end-point/variant/KMeansClustering.

  • Custom resources are not supported with a resource type. This parameter must specify the OutputValue from the CloudFormation template stack used to access the resources. The unique identifier is defined by the service provider. More information is available in our GitHub repository.

  • Amazon Comprehend document classification endpoint - The resource type and unique identifier are specified using the endpoint ARN. Example: arn:aws:comprehend:us-west-2:123456789012:document-classifier-endpoint/EXAMPLE.

  • Amazon Comprehend entity recognizer endpoint - The resource type and unique identifier are specified using the endpoint ARN. Example: arn:aws:comprehend:us-west-2:123456789012:entity-recognizer-endpoint/EXAMPLE.

  • Lambda provisioned concurrency - The resource type is function and the unique identifier is the function name with a function version or alias name suffix that is not $LATEST. Example: function:my-function:prod or function:my-function:1.

  • Amazon Keyspaces table - The resource type is table and the unique identifier is the table name. Example: keyspace/mykeyspace/table/mytable.

  • Amazon MSK cluster - The resource type and unique identifier are specified using the cluster ARN. Example: arn:aws:kafka:us-east-1:123456789012:cluster/demo-cluster-1/6357e0b2-0e6a-4b86-a0b4-70df934c2e31-5.

  • Amazon ElastiCache replication group - The resource type is replication-group and the unique identifier is the replication group name. Example: replication-group/mycluster.

  • Amazon ElastiCache cache cluster - The resource type is cache-cluster and the unique identifier is the cache cluster name. Example: cache-cluster/mycluster.

  • Neptune cluster - The resource type is cluster and the unique identifier is the cluster name. Example: cluster:mycluster.

  • SageMaker serverless endpoint - The resource type is variant and the unique identifier is the resource ID. Example: endpoint/my-end-point/variant/KMeansClustering.

  • SageMaker inference component - The resource type is inference-component and the unique identifier is the resource ID. Example: inference-component/my-inference-component.

  • Pool of WorkSpaces - The resource type is workspacespool and the unique identifier is the pool ID. Example: workspacespool/wspool-123456.

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pub fn get_resource_id(&self) -> &Option<String>

The identifier of the resource that is associated with the scalable target. This string consists of the resource type and unique identifier.

  • ECS service - The resource type is service and the unique identifier is the cluster name and service name. Example: service/my-cluster/my-service.

  • Spot Fleet - The resource type is spot-fleet-request and the unique identifier is the Spot Fleet request ID. Example: spot-fleet-request/sfr-73fbd2ce-aa30-494c-8788-1cee4EXAMPLE.

  • EMR cluster - The resource type is instancegroup and the unique identifier is the cluster ID and instance group ID. Example: instancegroup/j-2EEZNYKUA1NTV/ig-1791Y4E1L8YI0.

  • AppStream 2.0 fleet - The resource type is fleet and the unique identifier is the fleet name. Example: fleet/sample-fleet.

  • DynamoDB table - The resource type is table and the unique identifier is the table name. Example: table/my-table.

  • DynamoDB global secondary index - The resource type is index and the unique identifier is the index name. Example: table/my-table/index/my-table-index.

  • Aurora DB cluster - The resource type is cluster and the unique identifier is the cluster name. Example: cluster:my-db-cluster.

  • SageMaker endpoint variant - The resource type is variant and the unique identifier is the resource ID. Example: endpoint/my-end-point/variant/KMeansClustering.

  • Custom resources are not supported with a resource type. This parameter must specify the OutputValue from the CloudFormation template stack used to access the resources. The unique identifier is defined by the service provider. More information is available in our GitHub repository.

  • Amazon Comprehend document classification endpoint - The resource type and unique identifier are specified using the endpoint ARN. Example: arn:aws:comprehend:us-west-2:123456789012:document-classifier-endpoint/EXAMPLE.

  • Amazon Comprehend entity recognizer endpoint - The resource type and unique identifier are specified using the endpoint ARN. Example: arn:aws:comprehend:us-west-2:123456789012:entity-recognizer-endpoint/EXAMPLE.

  • Lambda provisioned concurrency - The resource type is function and the unique identifier is the function name with a function version or alias name suffix that is not $LATEST. Example: function:my-function:prod or function:my-function:1.

  • Amazon Keyspaces table - The resource type is table and the unique identifier is the table name. Example: keyspace/mykeyspace/table/mytable.

  • Amazon MSK cluster - The resource type and unique identifier are specified using the cluster ARN. Example: arn:aws:kafka:us-east-1:123456789012:cluster/demo-cluster-1/6357e0b2-0e6a-4b86-a0b4-70df934c2e31-5.

  • Amazon ElastiCache replication group - The resource type is replication-group and the unique identifier is the replication group name. Example: replication-group/mycluster.

  • Amazon ElastiCache cache cluster - The resource type is cache-cluster and the unique identifier is the cache cluster name. Example: cache-cluster/mycluster.

  • Neptune cluster - The resource type is cluster and the unique identifier is the cluster name. Example: cluster:mycluster.

  • SageMaker serverless endpoint - The resource type is variant and the unique identifier is the resource ID. Example: endpoint/my-end-point/variant/KMeansClustering.

  • SageMaker inference component - The resource type is inference-component and the unique identifier is the resource ID. Example: inference-component/my-inference-component.

  • Pool of WorkSpaces - The resource type is workspacespool and the unique identifier is the pool ID. Example: workspacespool/wspool-123456.

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pub fn scalable_dimension(self, input: ScalableDimension) -> Self

The scalable dimension associated with the scalable target. This string consists of the service namespace, resource type, and scaling property.

  • ecs:service:DesiredCount - The task count of an ECS service.

  • elasticmapreduce:instancegroup:InstanceCount - The instance count of an EMR Instance Group.

  • ec2:spot-fleet-request:TargetCapacity - The target capacity of a Spot Fleet.

  • appstream:fleet:DesiredCapacity - The capacity of an AppStream 2.0 fleet.

  • dynamodb:table:ReadCapacityUnits - The provisioned read capacity for a DynamoDB table.

  • dynamodb:table:WriteCapacityUnits - The provisioned write capacity for a DynamoDB table.

  • dynamodb:index:ReadCapacityUnits - The provisioned read capacity for a DynamoDB global secondary index.

  • dynamodb:index:WriteCapacityUnits - The provisioned write capacity for a DynamoDB global secondary index.

  • rds:cluster:ReadReplicaCount - The count of Aurora Replicas in an Aurora DB cluster. Available for Aurora MySQL-compatible edition and Aurora PostgreSQL-compatible edition.

  • sagemaker:variant:DesiredInstanceCount - The number of EC2 instances for a SageMaker model endpoint variant.

  • custom-resource:ResourceType:Property - The scalable dimension for a custom resource provided by your own application or service.

  • comprehend:document-classifier-endpoint:DesiredInferenceUnits - The number of inference units for an Amazon Comprehend document classification endpoint.

  • comprehend:entity-recognizer-endpoint:DesiredInferenceUnits - The number of inference units for an Amazon Comprehend entity recognizer endpoint.

  • lambda:function:ProvisionedConcurrency - The provisioned concurrency for a Lambda function.

  • cassandra:table:ReadCapacityUnits - The provisioned read capacity for an Amazon Keyspaces table.

  • cassandra:table:WriteCapacityUnits - The provisioned write capacity for an Amazon Keyspaces table.

  • kafka:broker-storage:VolumeSize - The provisioned volume size (in GiB) for brokers in an Amazon MSK cluster.

  • elasticache:cache-cluster:Nodes - The number of nodes for an Amazon ElastiCache cache cluster.

  • elasticache:replication-group:NodeGroups - The number of node groups for an Amazon ElastiCache replication group.

  • elasticache:replication-group:Replicas - The number of replicas per node group for an Amazon ElastiCache replication group.

  • neptune:cluster:ReadReplicaCount - The count of read replicas in an Amazon Neptune DB cluster.

  • sagemaker:variant:DesiredProvisionedConcurrency - The provisioned concurrency for a SageMaker serverless endpoint.

  • sagemaker:inference-component:DesiredCopyCount - The number of copies across an endpoint for a SageMaker inference component.

  • workspaces:workspacespool:DesiredUserSessions - The number of user sessions for the WorkSpaces in the pool.

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pub fn set_scalable_dimension(self, input: Option<ScalableDimension>) -> Self

The scalable dimension associated with the scalable target. This string consists of the service namespace, resource type, and scaling property.

  • ecs:service:DesiredCount - The task count of an ECS service.

  • elasticmapreduce:instancegroup:InstanceCount - The instance count of an EMR Instance Group.

  • ec2:spot-fleet-request:TargetCapacity - The target capacity of a Spot Fleet.

  • appstream:fleet:DesiredCapacity - The capacity of an AppStream 2.0 fleet.

  • dynamodb:table:ReadCapacityUnits - The provisioned read capacity for a DynamoDB table.

  • dynamodb:table:WriteCapacityUnits - The provisioned write capacity for a DynamoDB table.

  • dynamodb:index:ReadCapacityUnits - The provisioned read capacity for a DynamoDB global secondary index.

  • dynamodb:index:WriteCapacityUnits - The provisioned write capacity for a DynamoDB global secondary index.

  • rds:cluster:ReadReplicaCount - The count of Aurora Replicas in an Aurora DB cluster. Available for Aurora MySQL-compatible edition and Aurora PostgreSQL-compatible edition.

  • sagemaker:variant:DesiredInstanceCount - The number of EC2 instances for a SageMaker model endpoint variant.

  • custom-resource:ResourceType:Property - The scalable dimension for a custom resource provided by your own application or service.

  • comprehend:document-classifier-endpoint:DesiredInferenceUnits - The number of inference units for an Amazon Comprehend document classification endpoint.

  • comprehend:entity-recognizer-endpoint:DesiredInferenceUnits - The number of inference units for an Amazon Comprehend entity recognizer endpoint.

  • lambda:function:ProvisionedConcurrency - The provisioned concurrency for a Lambda function.

  • cassandra:table:ReadCapacityUnits - The provisioned read capacity for an Amazon Keyspaces table.

  • cassandra:table:WriteCapacityUnits - The provisioned write capacity for an Amazon Keyspaces table.

  • kafka:broker-storage:VolumeSize - The provisioned volume size (in GiB) for brokers in an Amazon MSK cluster.

  • elasticache:cache-cluster:Nodes - The number of nodes for an Amazon ElastiCache cache cluster.

  • elasticache:replication-group:NodeGroups - The number of node groups for an Amazon ElastiCache replication group.

  • elasticache:replication-group:Replicas - The number of replicas per node group for an Amazon ElastiCache replication group.

  • neptune:cluster:ReadReplicaCount - The count of read replicas in an Amazon Neptune DB cluster.

  • sagemaker:variant:DesiredProvisionedConcurrency - The provisioned concurrency for a SageMaker serverless endpoint.

  • sagemaker:inference-component:DesiredCopyCount - The number of copies across an endpoint for a SageMaker inference component.

  • workspaces:workspacespool:DesiredUserSessions - The number of user sessions for the WorkSpaces in the pool.

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pub fn get_scalable_dimension(&self) -> &Option<ScalableDimension>

The scalable dimension associated with the scalable target. This string consists of the service namespace, resource type, and scaling property.

  • ecs:service:DesiredCount - The task count of an ECS service.

  • elasticmapreduce:instancegroup:InstanceCount - The instance count of an EMR Instance Group.

  • ec2:spot-fleet-request:TargetCapacity - The target capacity of a Spot Fleet.

  • appstream:fleet:DesiredCapacity - The capacity of an AppStream 2.0 fleet.

  • dynamodb:table:ReadCapacityUnits - The provisioned read capacity for a DynamoDB table.

  • dynamodb:table:WriteCapacityUnits - The provisioned write capacity for a DynamoDB table.

  • dynamodb:index:ReadCapacityUnits - The provisioned read capacity for a DynamoDB global secondary index.

  • dynamodb:index:WriteCapacityUnits - The provisioned write capacity for a DynamoDB global secondary index.

  • rds:cluster:ReadReplicaCount - The count of Aurora Replicas in an Aurora DB cluster. Available for Aurora MySQL-compatible edition and Aurora PostgreSQL-compatible edition.

  • sagemaker:variant:DesiredInstanceCount - The number of EC2 instances for a SageMaker model endpoint variant.

  • custom-resource:ResourceType:Property - The scalable dimension for a custom resource provided by your own application or service.

  • comprehend:document-classifier-endpoint:DesiredInferenceUnits - The number of inference units for an Amazon Comprehend document classification endpoint.

  • comprehend:entity-recognizer-endpoint:DesiredInferenceUnits - The number of inference units for an Amazon Comprehend entity recognizer endpoint.

  • lambda:function:ProvisionedConcurrency - The provisioned concurrency for a Lambda function.

  • cassandra:table:ReadCapacityUnits - The provisioned read capacity for an Amazon Keyspaces table.

  • cassandra:table:WriteCapacityUnits - The provisioned write capacity for an Amazon Keyspaces table.

  • kafka:broker-storage:VolumeSize - The provisioned volume size (in GiB) for brokers in an Amazon MSK cluster.

  • elasticache:cache-cluster:Nodes - The number of nodes for an Amazon ElastiCache cache cluster.

  • elasticache:replication-group:NodeGroups - The number of node groups for an Amazon ElastiCache replication group.

  • elasticache:replication-group:Replicas - The number of replicas per node group for an Amazon ElastiCache replication group.

  • neptune:cluster:ReadReplicaCount - The count of read replicas in an Amazon Neptune DB cluster.

  • sagemaker:variant:DesiredProvisionedConcurrency - The provisioned concurrency for a SageMaker serverless endpoint.

  • sagemaker:inference-component:DesiredCopyCount - The number of copies across an endpoint for a SageMaker inference component.

  • workspaces:workspacespool:DesiredUserSessions - The number of user sessions for the WorkSpaces in the pool.

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pub fn min_capacity(self, input: i32) -> Self

The minimum value that you plan to scale in to. When a scaling policy is in effect, Application Auto Scaling can scale in (contract) as needed to the minimum capacity limit in response to changing demand. This property is required when registering a new scalable target.

For the following resources, the minimum value allowed is 0.

  • AppStream 2.0 fleets

  • Aurora DB clusters

  • ECS services

  • EMR clusters

  • Lambda provisioned concurrency

  • SageMaker endpoint variants

  • SageMaker inference components

  • SageMaker serverless endpoint provisioned concurrency

  • Spot Fleets

  • custom resources

It's strongly recommended that you specify a value greater than 0. A value greater than 0 means that data points are continuously reported to CloudWatch that scaling policies can use to scale on a metric like average CPU utilization.

For all other resources, the minimum allowed value depends on the type of resource that you are using. If you provide a value that is lower than what a resource can accept, an error occurs. In which case, the error message will provide the minimum value that the resource can accept.

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pub fn set_min_capacity(self, input: Option<i32>) -> Self

The minimum value that you plan to scale in to. When a scaling policy is in effect, Application Auto Scaling can scale in (contract) as needed to the minimum capacity limit in response to changing demand. This property is required when registering a new scalable target.

For the following resources, the minimum value allowed is 0.

  • AppStream 2.0 fleets

  • Aurora DB clusters

  • ECS services

  • EMR clusters

  • Lambda provisioned concurrency

  • SageMaker endpoint variants

  • SageMaker inference components

  • SageMaker serverless endpoint provisioned concurrency

  • Spot Fleets

  • custom resources

It's strongly recommended that you specify a value greater than 0. A value greater than 0 means that data points are continuously reported to CloudWatch that scaling policies can use to scale on a metric like average CPU utilization.

For all other resources, the minimum allowed value depends on the type of resource that you are using. If you provide a value that is lower than what a resource can accept, an error occurs. In which case, the error message will provide the minimum value that the resource can accept.

Source

pub fn get_min_capacity(&self) -> &Option<i32>

The minimum value that you plan to scale in to. When a scaling policy is in effect, Application Auto Scaling can scale in (contract) as needed to the minimum capacity limit in response to changing demand. This property is required when registering a new scalable target.

For the following resources, the minimum value allowed is 0.

  • AppStream 2.0 fleets

  • Aurora DB clusters

  • ECS services

  • EMR clusters

  • Lambda provisioned concurrency

  • SageMaker endpoint variants

  • SageMaker inference components

  • SageMaker serverless endpoint provisioned concurrency

  • Spot Fleets

  • custom resources

It's strongly recommended that you specify a value greater than 0. A value greater than 0 means that data points are continuously reported to CloudWatch that scaling policies can use to scale on a metric like average CPU utilization.

For all other resources, the minimum allowed value depends on the type of resource that you are using. If you provide a value that is lower than what a resource can accept, an error occurs. In which case, the error message will provide the minimum value that the resource can accept.

Source

pub fn max_capacity(self, input: i32) -> Self

The maximum value that you plan to scale out to. When a scaling policy is in effect, Application Auto Scaling can scale out (expand) as needed to the maximum capacity limit in response to changing demand. This property is required when registering a new scalable target.

Although you can specify a large maximum capacity, note that service quotas might impose lower limits. Each service has its own default quotas for the maximum capacity of the resource. If you want to specify a higher limit, you can request an increase. For more information, consult the documentation for that service. For information about the default quotas for each service, see Service endpoints and quotas in the Amazon Web Services General Reference.

Source

pub fn set_max_capacity(self, input: Option<i32>) -> Self

The maximum value that you plan to scale out to. When a scaling policy is in effect, Application Auto Scaling can scale out (expand) as needed to the maximum capacity limit in response to changing demand. This property is required when registering a new scalable target.

Although you can specify a large maximum capacity, note that service quotas might impose lower limits. Each service has its own default quotas for the maximum capacity of the resource. If you want to specify a higher limit, you can request an increase. For more information, consult the documentation for that service. For information about the default quotas for each service, see Service endpoints and quotas in the Amazon Web Services General Reference.

Source

pub fn get_max_capacity(&self) -> &Option<i32>

The maximum value that you plan to scale out to. When a scaling policy is in effect, Application Auto Scaling can scale out (expand) as needed to the maximum capacity limit in response to changing demand. This property is required when registering a new scalable target.

Although you can specify a large maximum capacity, note that service quotas might impose lower limits. Each service has its own default quotas for the maximum capacity of the resource. If you want to specify a higher limit, you can request an increase. For more information, consult the documentation for that service. For information about the default quotas for each service, see Service endpoints and quotas in the Amazon Web Services General Reference.

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pub fn role_arn(self, input: impl Into<String>) -> Self

This parameter is required for services that do not support service-linked roles (such as Amazon EMR), and it must specify the ARN of an IAM role that allows Application Auto Scaling to modify the scalable target on your behalf.

If the service supports service-linked roles, Application Auto Scaling uses a service-linked role, which it creates if it does not yet exist. For more information, see How Application Auto Scaling works with IAM.

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pub fn set_role_arn(self, input: Option<String>) -> Self

This parameter is required for services that do not support service-linked roles (such as Amazon EMR), and it must specify the ARN of an IAM role that allows Application Auto Scaling to modify the scalable target on your behalf.

If the service supports service-linked roles, Application Auto Scaling uses a service-linked role, which it creates if it does not yet exist. For more information, see How Application Auto Scaling works with IAM.

Source

pub fn get_role_arn(&self) -> &Option<String>

This parameter is required for services that do not support service-linked roles (such as Amazon EMR), and it must specify the ARN of an IAM role that allows Application Auto Scaling to modify the scalable target on your behalf.

If the service supports service-linked roles, Application Auto Scaling uses a service-linked role, which it creates if it does not yet exist. For more information, see How Application Auto Scaling works with IAM.

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pub fn suspended_state(self, input: SuspendedState) -> Self

An embedded object that contains attributes and attribute values that are used to suspend and resume automatic scaling. Setting the value of an attribute to true suspends the specified scaling activities. Setting it to false (default) resumes the specified scaling activities.

Suspension Outcomes

  • For DynamicScalingInSuspended, while a suspension is in effect, all scale-in activities that are triggered by a scaling policy are suspended.

  • For DynamicScalingOutSuspended, while a suspension is in effect, all scale-out activities that are triggered by a scaling policy are suspended.

  • For ScheduledScalingSuspended, while a suspension is in effect, all scaling activities that involve scheduled actions are suspended.

For more information, see Suspend and resume scaling in the Application Auto Scaling User Guide.

Source

pub fn set_suspended_state(self, input: Option<SuspendedState>) -> Self

An embedded object that contains attributes and attribute values that are used to suspend and resume automatic scaling. Setting the value of an attribute to true suspends the specified scaling activities. Setting it to false (default) resumes the specified scaling activities.

Suspension Outcomes

  • For DynamicScalingInSuspended, while a suspension is in effect, all scale-in activities that are triggered by a scaling policy are suspended.

  • For DynamicScalingOutSuspended, while a suspension is in effect, all scale-out activities that are triggered by a scaling policy are suspended.

  • For ScheduledScalingSuspended, while a suspension is in effect, all scaling activities that involve scheduled actions are suspended.

For more information, see Suspend and resume scaling in the Application Auto Scaling User Guide.

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pub fn get_suspended_state(&self) -> &Option<SuspendedState>

An embedded object that contains attributes and attribute values that are used to suspend and resume automatic scaling. Setting the value of an attribute to true suspends the specified scaling activities. Setting it to false (default) resumes the specified scaling activities.

Suspension Outcomes

  • For DynamicScalingInSuspended, while a suspension is in effect, all scale-in activities that are triggered by a scaling policy are suspended.

  • For DynamicScalingOutSuspended, while a suspension is in effect, all scale-out activities that are triggered by a scaling policy are suspended.

  • For ScheduledScalingSuspended, while a suspension is in effect, all scaling activities that involve scheduled actions are suspended.

For more information, see Suspend and resume scaling in the Application Auto Scaling User Guide.

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pub fn tags(self, k: impl Into<String>, v: impl Into<String>) -> Self

Adds a key-value pair to Tags.

To override the contents of this collection use set_tags.

Assigns one or more tags to the scalable target. Use this parameter to tag the scalable target when it is created. To tag an existing scalable target, use the TagResource operation.

Each tag consists of a tag key and a tag value. Both the tag key and the tag value are required. You cannot have more than one tag on a scalable target with the same tag key.

Use tags to control access to a scalable target. For more information, see Tagging support for Application Auto Scaling in the Application Auto Scaling User Guide.

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pub fn set_tags(self, input: Option<HashMap<String, String>>) -> Self

Assigns one or more tags to the scalable target. Use this parameter to tag the scalable target when it is created. To tag an existing scalable target, use the TagResource operation.

Each tag consists of a tag key and a tag value. Both the tag key and the tag value are required. You cannot have more than one tag on a scalable target with the same tag key.

Use tags to control access to a scalable target. For more information, see Tagging support for Application Auto Scaling in the Application Auto Scaling User Guide.

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pub fn get_tags(&self) -> &Option<HashMap<String, String>>

Assigns one or more tags to the scalable target. Use this parameter to tag the scalable target when it is created. To tag an existing scalable target, use the TagResource operation.

Each tag consists of a tag key and a tag value. Both the tag key and the tag value are required. You cannot have more than one tag on a scalable target with the same tag key.

Use tags to control access to a scalable target. For more information, see Tagging support for Application Auto Scaling in the Application Auto Scaling User Guide.

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impl Clone for RegisterScalableTargetFluentBuilder

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impl Debug for RegisterScalableTargetFluentBuilder

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