Class: Aws::ApplicationAutoScaling::Client

Inherits:
Seahorse::Client::Base
  • Object
show all
Includes:
ClientStubs
Defined in:
lib/aws-sdk-applicationautoscaling/client.rb

Overview

An API client for ApplicationAutoScaling. To construct a client, you need to configure a ‘:region` and `:credentials`.

client = Aws::ApplicationAutoScaling::Client.new(
  region: region_name,
  credentials: credentials,
  # ...
)

For details on configuring region and credentials see the [developer guide](/sdk-for-ruby/v3/developer-guide/setup-config.html).

See #initialize for a full list of supported configuration options.

Class Attribute Summary collapse

API Operations collapse

Class Method Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(options) ⇒ Client

Returns a new instance of Client.

Parameters:

  • options (Hash)

Options Hash (options):

  • :plugins (Array<Seahorse::Client::Plugin>) — default: []] —

    A list of plugins to apply to the client. Each plugin is either a class name or an instance of a plugin class.

  • :credentials (required, Aws::CredentialProvider) —

    Your AWS credentials. This can be an instance of any one of the following classes:

    • ‘Aws::Credentials` - Used for configuring static, non-refreshing credentials.

    • ‘Aws::SharedCredentials` - Used for loading static credentials from a shared file, such as `~/.aws/config`.

    • ‘Aws::AssumeRoleCredentials` - Used when you need to assume a role.

    • ‘Aws::AssumeRoleWebIdentityCredentials` - Used when you need to assume a role after providing credentials via the web.

    • ‘Aws::SSOCredentials` - Used for loading credentials from AWS SSO using an access token generated from `aws login`.

    • ‘Aws::ProcessCredentials` - Used for loading credentials from a process that outputs to stdout.

    • ‘Aws::InstanceProfileCredentials` - Used for loading credentials from an EC2 IMDS on an EC2 instance.

    • ‘Aws::ECSCredentials` - Used for loading credentials from instances running in ECS.

    • ‘Aws::CognitoIdentityCredentials` - Used for loading credentials from the Cognito Identity service.

    When ‘:credentials` are not configured directly, the following locations will be searched for credentials:

    • ‘Aws.config`

    • The ‘:access_key_id`, `:secret_access_key`, `:session_token`, and `:account_id` options.

    • ENV, ENV, ENV, and ENV

    • ‘~/.aws/credentials`

    • ‘~/.aws/config`

    • EC2/ECS IMDS instance profile - When used by default, the timeouts are very aggressive. Construct and pass an instance of ‘Aws::InstanceProfileCredentials` or `Aws::ECSCredentials` to enable retries and extended timeouts. Instance profile credential fetching can be disabled by setting ENV to true.

  • :region (required, String) —

    The AWS region to connect to. The configured ‘:region` is used to determine the service `:endpoint`. When not passed, a default `:region` is searched for in the following locations:

  • :access_key_id (String)
  • :account_id (String)
  • :active_endpoint_cache (Boolean) — default: false —

    When set to ‘true`, a thread polling for endpoints will be running in the background every 60 secs (default). Defaults to `false`.

  • :adaptive_retry_wait_to_fill (Boolean) — default: true —

    Used only in ‘adaptive` retry mode. When true, the request will sleep until there is sufficent client side capacity to retry the request. When false, the request will raise a `RetryCapacityNotAvailableError` and will not retry instead of sleeping.

  • :client_side_monitoring (Boolean) — default: false —

    When ‘true`, client-side metrics will be collected for all API requests from this client.

  • :client_side_monitoring_client_id (String) — default: "" —

    Allows you to provide an identifier for this client which will be attached to all generated client side metrics. Defaults to an empty string.

  • :client_side_monitoring_host (String) — default: "127.0.0.1" —

    Allows you to specify the DNS hostname or IPv4 or IPv6 address that the client side monitoring agent is running on, where client metrics will be published via UDP.

  • :client_side_monitoring_port (Integer) — default: 31000 —

    Required for publishing client metrics. The port that the client side monitoring agent is running on, where client metrics will be published via UDP.

  • :client_side_monitoring_publisher (Aws::ClientSideMonitoring::Publisher) — default: Aws::ClientSideMonitoring::Publisher —

    Allows you to provide a custom client-side monitoring publisher class. By default, will use the Client Side Monitoring Agent Publisher.

  • :convert_params (Boolean) — default: true —

    When ‘true`, an attempt is made to coerce request parameters into the required types.

  • :correct_clock_skew (Boolean) — default: true —

    Used only in ‘standard` and adaptive retry modes. Specifies whether to apply a clock skew correction and retry requests with skewed client clocks.

  • :defaults_mode (String) — default: "legacy" —

    See DefaultsModeConfiguration for a list of the accepted modes and the configuration defaults that are included.

  • :disable_host_prefix_injection (Boolean) — default: false —

    Set to true to disable SDK automatically adding host prefix to default service endpoint when available.

  • :disable_request_compression (Boolean) — default: false —

    When set to ‘true’ the request body will not be compressed for supported operations.

  • :endpoint (String, URI::HTTPS, URI::HTTP) —

    Normally you should not configure the ‘:endpoint` option directly. This is normally constructed from the `:region` option. Configuring `:endpoint` is normally reserved for connecting to test or custom endpoints. The endpoint should be a URI formatted like:

    'http://example.com'
'https://example.com'
'http://example.com:123'
  • :endpoint_cache_max_entries (Integer) — default: 1000 —

    Used for the maximum size limit of the LRU cache storing endpoints data for endpoint discovery enabled operations. Defaults to 1000.

  • :endpoint_cache_max_threads (Integer) — default: 10 —

    Used for the maximum threads in use for polling endpoints to be cached, defaults to 10.

  • :endpoint_cache_poll_interval (Integer) — default: 60 —

    When :endpoint_discovery and :active_endpoint_cache is enabled, Use this option to config the time interval in seconds for making requests fetching endpoints information. Defaults to 60 sec.

  • :endpoint_discovery (Boolean) — default: false —

    When set to ‘true`, endpoint discovery will be enabled for operations when available.

  • :ignore_configured_endpoint_urls (Boolean) —

    Setting to true disables use of endpoint URLs provided via environment variables and the shared configuration file.

  • :log_formatter (Aws::Log::Formatter) — default: Aws::Log::Formatter.default —

    The log formatter.

  • :log_level (Symbol) — default: :info —

    The log level to send messages to the ‘:logger` at.

  • :logger (Logger) —

    The Logger instance to send log messages to. If this option is not set, logging will be disabled.

  • :max_attempts (Integer) — default: 3 —

    An integer representing the maximum number attempts that will be made for a single request, including the initial attempt. For example, setting this value to 5 will result in a request being retried up to 4 times. Used in ‘standard` and `adaptive` retry modes.

  • :profile (String) — default: "default" —

    Used when loading credentials from the shared credentials file at HOME/.aws/credentials. When not specified, ‘default’ is used.

  • :request_min_compression_size_bytes (Integer) — default: 10240 —

    The minimum size in bytes that triggers compression for request bodies. The value must be non-negative integer value between 0 and 10485780 bytes inclusive.

  • :retry_backoff (Proc) —

    A proc or lambda used for backoff. Defaults to 2**retries * retry_base_delay. This option is only used in the ‘legacy` retry mode.

  • :retry_base_delay (Float) — default: 0.3 —

    The base delay in seconds used by the default backoff function. This option is only used in the ‘legacy` retry mode.

  • :retry_jitter (Symbol) — default: :none —

    A delay randomiser function used by the default backoff function. Some predefined functions can be referenced by name - :none, :equal, :full, otherwise a Proc that takes and returns a number. This option is only used in the ‘legacy` retry mode.

    @see www.awsarchitectureblog.com/2015/03/backoff.html

  • :retry_limit (Integer) — default: 3 —

    The maximum number of times to retry failed requests. Only ~ 500 level server errors and certain ~ 400 level client errors are retried. Generally, these are throttling errors, data checksum errors, networking errors, timeout errors, auth errors, endpoint discovery, and errors from expired credentials. This option is only used in the ‘legacy` retry mode.

  • :retry_max_delay (Integer) — default: 0 —

    The maximum number of seconds to delay between retries (0 for no limit) used by the default backoff function. This option is only used in the ‘legacy` retry mode.

  • :retry_mode (String) — default: "legacy" —

    Specifies which retry algorithm to use. Values are:

    • ‘legacy` - The pre-existing retry behavior. This is default value if no retry mode is provided.

    • ‘standard` - A standardized set of retry rules across the AWS SDKs. This includes support for retry quotas, which limit the number of unsuccessful retries a client can make.

    • ‘adaptive` - An experimental retry mode that includes all the functionality of `standard` mode along with automatic client side throttling. This is a provisional mode that may change behavior in the future.

  • :sdk_ua_app_id (String) —

    A unique and opaque application ID that is appended to the User-Agent header as app/sdk_ua_app_id. It should have a maximum length of 50. This variable is sourced from environment variable AWS_SDK_UA_APP_ID or the shared config profile attribute sdk_ua_app_id.

  • :secret_access_key (String)
  • :session_token (String)
  • :sigv4a_signing_region_set (Array) —

    A list of regions that should be signed with SigV4a signing. When not passed, a default ‘:sigv4a_signing_region_set` is searched for in the following locations:

  • :simple_json (Boolean) — default: false —

    Disables request parameter conversion, validation, and formatting. Also disables response data type conversions. The request parameters hash must be formatted exactly as the API expects.This option is useful when you want to ensure the highest level of performance by avoiding overhead of walking request parameters and response data structures.

  • :stub_responses (Boolean) — default: false —

    Causes the client to return stubbed responses. By default fake responses are generated and returned. You can specify the response data to return or errors to raise by calling ClientStubs#stub_responses. See ClientStubs for more information.

    ** Please note ** When response stubbing is enabled, no HTTP requests are made, and retries are disabled.

  • :telemetry_provider (Aws::Telemetry::TelemetryProviderBase) — default: Aws::Telemetry::NoOpTelemetryProvider —

    Allows you to provide a telemetry provider, which is used to emit telemetry data. By default, uses ‘NoOpTelemetryProvider` which will not record or emit any telemetry data. The SDK supports the following telemetry providers:

    • OpenTelemetry (OTel) - To use the OTel provider, install and require the

    ‘opentelemetry-sdk` gem and then, pass in an instance of a `Aws::Telemetry::OTelProvider` for telemetry provider.

  • :token_provider (Aws::TokenProvider) —

    A Bearer Token Provider. This can be an instance of any one of the following classes:

    • ‘Aws::StaticTokenProvider` - Used for configuring static, non-refreshing tokens.

    • ‘Aws::SSOTokenProvider` - Used for loading tokens from AWS SSO using an access token generated from `aws login`.

    When ‘:token_provider` is not configured directly, the `Aws::TokenProviderChain` will be used to search for tokens configured for your profile in shared configuration files.

  • :use_dualstack_endpoint (Boolean) —

    When set to ‘true`, dualstack enabled endpoints (with `.aws` TLD) will be used if available.

  • :use_fips_endpoint (Boolean) —

    When set to ‘true`, fips compatible endpoints will be used if available. When a `fips` region is used, the region is normalized and this config is set to `true`.

  • :validate_params (Boolean) — default: true —

    When ‘true`, request parameters are validated before sending the request.

  • :endpoint_provider (Aws::ApplicationAutoScaling::EndpointProvider) —

    The endpoint provider used to resolve endpoints. Any object that responds to ‘#resolve_endpoint(parameters)` where `parameters` is a Struct similar to `Aws::ApplicationAutoScaling::EndpointParameters`.

  • :http_continue_timeout (Float) — default: 1 —

    The number of seconds to wait for a 100-continue response before sending the request body. This option has no effect unless the request has “Expect” header set to “100-continue”. Defaults to ‘nil` which disables this behaviour. This value can safely be set per request on the session.

  • :http_idle_timeout (Float) — default: 5 —

    The number of seconds a connection is allowed to sit idle before it is considered stale. Stale connections are closed and removed from the pool before making a request.

  • :http_open_timeout (Float) — default: 15 —

    The default number of seconds to wait for response data. This value can safely be set per-request on the session.

  • :http_proxy (URI::HTTP, String) —

    A proxy to send requests through. Formatted like ‘proxy.com:123’.

  • :http_read_timeout (Float) — default: 60 —

    The default number of seconds to wait for response data. This value can safely be set per-request on the session.

  • :http_wire_trace (Boolean) — default: false —

    When ‘true`, HTTP debug output will be sent to the `:logger`.

  • :on_chunk_received (Proc) —

    When a Proc object is provided, it will be used as callback when each chunk of the response body is received. It provides three arguments: the chunk, the number of bytes received, and the total number of bytes in the response (or nil if the server did not send a ‘content-length`).

  • :on_chunk_sent (Proc) —

    When a Proc object is provided, it will be used as callback when each chunk of the request body is sent. It provides three arguments: the chunk, the number of bytes read from the body, and the total number of bytes in the body.

  • :raise_response_errors (Boolean) — default: true —

    When ‘true`, response errors are raised.

  • :ssl_ca_bundle (String) —

    Full path to the SSL certificate authority bundle file that should be used when verifying peer certificates. If you do not pass ‘:ssl_ca_bundle` or `:ssl_ca_directory` the the system default will be used if available.

  • :ssl_ca_directory (String) —

    Full path of the directory that contains the unbundled SSL certificate authority files for verifying peer certificates. If you do not pass ‘:ssl_ca_bundle` or `:ssl_ca_directory` the the system default will be used if available.

  • :ssl_ca_store (String) —

    Sets the X509::Store to verify peer certificate.

  • :ssl_cert (OpenSSL::X509::Certificate) —

    Sets a client certificate when creating http connections.

  • :ssl_key (OpenSSL::PKey) —

    Sets a client key when creating http connections.

  • :ssl_timeout (Float) —

    Sets the SSL timeout in seconds

  • :ssl_verify_peer (Boolean) — default: true —

    When ‘true`, SSL peer certificates are verified when establishing a connection.



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# File 'lib/aws-sdk-applicationautoscaling/client.rb', line 451

def initialize(*args)
  super
end

Class Attribute Details

.identifier ⇒ Object (readonly)

This method is part of a private API. You should avoid using this method if possible, as it may be removed or be changed in the future. 



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# File 'lib/aws-sdk-applicationautoscaling/client.rb', line 3795

def identifier
  @identifier
end

Class Method Details

.errors_module ⇒ Object

This method is part of a private API. You should avoid using this method if possible, as it may be removed or be changed in the future. 



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# File 'lib/aws-sdk-applicationautoscaling/client.rb', line 3798

def errors_module
  Errors
end

Instance Method Details

#build_request(operation_name, params = {}) ⇒ Object

This method is part of a private API. You should avoid using this method if possible, as it may be removed or be changed in the future.

Parameters:

  • params ({}) (defaults to: {}) 


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# File 'lib/aws-sdk-applicationautoscaling/client.rb', line 3768

def build_request(operation_name, params = {})
  handlers = @handlers.for(operation_name)
  tracer = config.telemetry_provider.tracer_provider.tracer(
    Aws::Telemetry.module_to_tracer_name('Aws::ApplicationAutoScaling')
  )
  context = Seahorse::Client::RequestContext.new(
    operation_name: operation_name,
    operation: config.api.operation(operation_name),
    client: self,
    params: params,
    config: config,
    tracer: tracer
  )
  context[:gem_name] = 'aws-sdk-applicationautoscaling'
  context[:gem_version] = '1.99.0'
  Seahorse::Client::Request.new(handlers, context)
end

#delete_scaling_policy(params = {}) ⇒ Struct

Deletes the specified scaling policy for an Application Auto Scaling scalable target.

Deleting a step scaling policy deletes the underlying alarm action, but does not delete the CloudWatch alarm associated with the scaling policy, even if it no longer has an associated action.

For more information, see [Delete a step scaling policy] and

Delete a target tracking scaling policy][2

in the *Application Auto

Scaling User Guide*.

[1]: docs.aws.amazon.com/autoscaling/application/userguide/create-step-scaling-policy-cli.html#delete-step-scaling-policy [2]: docs.aws.amazon.com/autoscaling/application/userguide/create-target-tracking-policy-cli.html#delete-target-tracking-policy

Examples:

Example: To delete a scaling policy


# This example deletes a scaling policy for the Amazon ECS service called web-app, which is running in the default
# cluster.

resp = client.delete_scaling_policy({
  policy_name: "web-app-cpu-lt-25", 
  resource_id: "service/default/web-app", 
  scalable_dimension: "ecs:service:DesiredCount", 
  service_namespace: "ecs", 
})

resp.to_h outputs the following:
{
}

Request syntax with placeholder values


resp = client.delete_scaling_policy({
  policy_name: "ResourceIdMaxLen1600", # required
  service_namespace: "ecs", # required, accepts ecs, elasticmapreduce, ec2, appstream, dynamodb, rds, sagemaker, custom-resource, comprehend, lambda, cassandra, kafka, elasticache, neptune, workspaces
  resource_id: "ResourceIdMaxLen1600", # required
  scalable_dimension: "ecs:service:DesiredCount", # required, accepts ecs:service:DesiredCount, ec2:spot-fleet-request:TargetCapacity, elasticmapreduce:instancegroup:InstanceCount, appstream:fleet:DesiredCapacity, dynamodb:table:ReadCapacityUnits, dynamodb:table:WriteCapacityUnits, dynamodb:index:ReadCapacityUnits, dynamodb:index:WriteCapacityUnits, rds:cluster:ReadReplicaCount, sagemaker:variant:DesiredInstanceCount, custom-resource:ResourceType:Property, comprehend:document-classifier-endpoint:DesiredInferenceUnits, comprehend:entity-recognizer-endpoint:DesiredInferenceUnits, lambda:function:ProvisionedConcurrency, cassandra:table:ReadCapacityUnits, cassandra:table:WriteCapacityUnits, kafka:broker-storage:VolumeSize, elasticache:replication-group:NodeGroups, elasticache:replication-group:Replicas, neptune:cluster:ReadReplicaCount, sagemaker:variant:DesiredProvisionedConcurrency, sagemaker:inference-component:DesiredCopyCount, workspaces:workspacespool:DesiredUserSessions
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :policy_name (required, String) —

    The name of the scaling policy.

  • :service_namespace (required, String) —

    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.

  • :resource_id (required, String) —

    The identifier of the resource 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`.

    • 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`.

    [1]: github.com/aws/aws-auto-scaling-custom-resource

  • :scalable_dimension (required, String) —

    The scalable dimension. 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: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.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'lib/aws-sdk-applicationautoscaling/client.rb', line 672

def delete_scaling_policy(params = {}, options = {})
  req = build_request(:delete_scaling_policy, params)
  req.send_request(options)
end

#delete_scheduled_action(params = {}) ⇒ Struct

Deletes the specified scheduled action for an Application Auto Scaling scalable target.

For more information, see [Delete a scheduled action] in the *Application Auto Scaling User Guide*.

[1]: docs.aws.amazon.com/autoscaling/application/userguide/scheduled-scaling-additional-cli-commands.html#delete-scheduled-action

Examples:

Example: To delete a scheduled action


# This example deletes a scheduled action for the AppStream 2.0 fleet called sample-fleet.

resp = client.delete_scheduled_action({
  resource_id: "fleet/sample-fleet", 
  scalable_dimension: "appstream:fleet:DesiredCapacity", 
  scheduled_action_name: "my-recurring-action", 
  service_namespace: "appstream", 
})

resp.to_h outputs the following:
{
}

Request syntax with placeholder values


resp = client.delete_scheduled_action({
  service_namespace: "ecs", # required, accepts ecs, elasticmapreduce, ec2, appstream, dynamodb, rds, sagemaker, custom-resource, comprehend, lambda, cassandra, kafka, elasticache, neptune, workspaces
  scheduled_action_name: "ResourceIdMaxLen1600", # required
  resource_id: "ResourceIdMaxLen1600", # required
  scalable_dimension: "ecs:service:DesiredCount", # required, accepts ecs:service:DesiredCount, ec2:spot-fleet-request:TargetCapacity, elasticmapreduce:instancegroup:InstanceCount, appstream:fleet:DesiredCapacity, dynamodb:table:ReadCapacityUnits, dynamodb:table:WriteCapacityUnits, dynamodb:index:ReadCapacityUnits, dynamodb:index:WriteCapacityUnits, rds:cluster:ReadReplicaCount, sagemaker:variant:DesiredInstanceCount, custom-resource:ResourceType:Property, comprehend:document-classifier-endpoint:DesiredInferenceUnits, comprehend:entity-recognizer-endpoint:DesiredInferenceUnits, lambda:function:ProvisionedConcurrency, cassandra:table:ReadCapacityUnits, cassandra:table:WriteCapacityUnits, kafka:broker-storage:VolumeSize, elasticache:replication-group:NodeGroups, elasticache:replication-group:Replicas, neptune:cluster:ReadReplicaCount, sagemaker:variant:DesiredProvisionedConcurrency, sagemaker:inference-component:DesiredCopyCount, workspaces:workspacespool:DesiredUserSessions
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :service_namespace (required, String) —

    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.

  • :scheduled_action_name (required, String) —

    The name of the scheduled action.

  • :resource_id (required, String) —

    The identifier of the resource associated with the scheduled action. 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`.

    • 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`.

    [1]: github.com/aws/aws-auto-scaling-custom-resource

  • :scalable_dimension (required, String) —

    The scalable dimension. 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: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.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'lib/aws-sdk-applicationautoscaling/client.rb', line 885

def delete_scheduled_action(params = {}, options = {})
  req = build_request(:delete_scheduled_action, params)
  req.send_request(options)
end

#deregister_scalable_target(params = {}) ⇒ Struct

Deregisters an Application Auto Scaling scalable target when you have finished using it. To see which resources have been registered, use [DescribeScalableTargets].

<note markdown=“1”> Deregistering a scalable target deletes the scaling policies and the scheduled actions that are associated with it.

</note>

[1]: docs.aws.amazon.com/autoscaling/application/APIReference/API_DescribeScalableTargets.html

Examples:

Example: To deregister a scalable target


# This example deregisters a scalable target for an Amazon ECS service called web-app that is running in the default
# cluster.

resp = client.deregister_scalable_target({
  resource_id: "service/default/web-app", 
  scalable_dimension: "ecs:service:DesiredCount", 
  service_namespace: "ecs", 
})

resp.to_h outputs the following:
{
}

Request syntax with placeholder values


resp = client.deregister_scalable_target({
  service_namespace: "ecs", # required, accepts ecs, elasticmapreduce, ec2, appstream, dynamodb, rds, sagemaker, custom-resource, comprehend, lambda, cassandra, kafka, elasticache, neptune, workspaces
  resource_id: "ResourceIdMaxLen1600", # required
  scalable_dimension: "ecs:service:DesiredCount", # required, accepts ecs:service:DesiredCount, ec2:spot-fleet-request:TargetCapacity, elasticmapreduce:instancegroup:InstanceCount, appstream:fleet:DesiredCapacity, dynamodb:table:ReadCapacityUnits, dynamodb:table:WriteCapacityUnits, dynamodb:index:ReadCapacityUnits, dynamodb:index:WriteCapacityUnits, rds:cluster:ReadReplicaCount, sagemaker:variant:DesiredInstanceCount, custom-resource:ResourceType:Property, comprehend:document-classifier-endpoint:DesiredInferenceUnits, comprehend:entity-recognizer-endpoint:DesiredInferenceUnits, lambda:function:ProvisionedConcurrency, cassandra:table:ReadCapacityUnits, cassandra:table:WriteCapacityUnits, kafka:broker-storage:VolumeSize, elasticache:replication-group:NodeGroups, elasticache:replication-group:Replicas, neptune:cluster:ReadReplicaCount, sagemaker:variant:DesiredProvisionedConcurrency, sagemaker:inference-component:DesiredCopyCount, workspaces:workspacespool:DesiredUserSessions
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :service_namespace (required, String) —

    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.

  • :resource_id (required, String) —

    The identifier of the resource 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`.

    • 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`.

    [1]: github.com/aws/aws-auto-scaling-custom-resource

  • :scalable_dimension (required, String) —

    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: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.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'lib/aws-sdk-applicationautoscaling/client.rb', line 1098

def deregister_scalable_target(params = {}, options = {})
  req = build_request(:deregister_scalable_target, params)
  req.send_request(options)
end

#describe_scalable_targets(params = {}) ⇒ Types::DescribeScalableTargetsResponse

Gets information about the scalable targets in the specified namespace.

You can filter the results using ‘ResourceIds` and `ScalableDimension`.

The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.

Examples:

Example: To describe scalable targets


# This example describes the scalable targets for the ECS service namespace.

resp = client.describe_scalable_targets({
  service_namespace: "ecs", 
})

resp.to_h outputs the following:
{
  scalable_targets: [
    {
      creation_time: Time.parse("2019-05-06T11:21:46.199Z"), 
      max_capacity: 10, 
      min_capacity: 1, 
      resource_id: "service/default/web-app", 
      role_arn: "arn:aws:iam::012345678910:role/aws-service-role/ecs.application-autoscaling.amazonaws.com/AWSServiceRoleForApplicationAutoScaling_ECSService", 
      scalable_dimension: "ecs:service:DesiredCount", 
      service_namespace: "ecs", 
      suspended_state: {
        dynamic_scaling_in_suspended: false, 
        dynamic_scaling_out_suspended: false, 
        scheduled_scaling_suspended: false, 
      }, 
    }, 
  ], 
}

Request syntax with placeholder values


resp = client.describe_scalable_targets({
  service_namespace: "ecs", # required, accepts ecs, elasticmapreduce, ec2, appstream, dynamodb, rds, sagemaker, custom-resource, comprehend, lambda, cassandra, kafka, elasticache, neptune, workspaces
  resource_ids: ["ResourceIdMaxLen1600"],
  scalable_dimension: "ecs:service:DesiredCount", # accepts ecs:service:DesiredCount, ec2:spot-fleet-request:TargetCapacity, elasticmapreduce:instancegroup:InstanceCount, appstream:fleet:DesiredCapacity, dynamodb:table:ReadCapacityUnits, dynamodb:table:WriteCapacityUnits, dynamodb:index:ReadCapacityUnits, dynamodb:index:WriteCapacityUnits, rds:cluster:ReadReplicaCount, sagemaker:variant:DesiredInstanceCount, custom-resource:ResourceType:Property, comprehend:document-classifier-endpoint:DesiredInferenceUnits, comprehend:entity-recognizer-endpoint:DesiredInferenceUnits, lambda:function:ProvisionedConcurrency, cassandra:table:ReadCapacityUnits, cassandra:table:WriteCapacityUnits, kafka:broker-storage:VolumeSize, elasticache:replication-group:NodeGroups, elasticache:replication-group:Replicas, neptune:cluster:ReadReplicaCount, sagemaker:variant:DesiredProvisionedConcurrency, sagemaker:inference-component:DesiredCopyCount, workspaces:workspacespool:DesiredUserSessions
  max_results: 1,
  next_token: "XmlString",
})

Response structure


resp.scalable_targets #=> Array
resp.scalable_targets[0].service_namespace #=> String, one of "ecs", "elasticmapreduce", "ec2", "appstream", "dynamodb", "rds", "sagemaker", "custom-resource", "comprehend", "lambda", "cassandra", "kafka", "elasticache", "neptune", "workspaces"
resp.scalable_targets[0].resource_id #=> String
resp.scalable_targets[0].scalable_dimension #=> String, one of "ecs:service:DesiredCount", "ec2:spot-fleet-request:TargetCapacity", "elasticmapreduce:instancegroup:InstanceCount", "appstream:fleet:DesiredCapacity", "dynamodb:table:ReadCapacityUnits", "dynamodb:table:WriteCapacityUnits", "dynamodb:index:ReadCapacityUnits", "dynamodb:index:WriteCapacityUnits", "rds:cluster:ReadReplicaCount", "sagemaker:variant:DesiredInstanceCount", "custom-resource:ResourceType:Property", "comprehend:document-classifier-endpoint:DesiredInferenceUnits", "comprehend:entity-recognizer-endpoint:DesiredInferenceUnits", "lambda:function:ProvisionedConcurrency", "cassandra:table:ReadCapacityUnits", "cassandra:table:WriteCapacityUnits", "kafka:broker-storage:VolumeSize", "elasticache:replication-group:NodeGroups", "elasticache:replication-group:Replicas", "neptune:cluster:ReadReplicaCount", "sagemaker:variant:DesiredProvisionedConcurrency", "sagemaker:inference-component:DesiredCopyCount", "workspaces:workspacespool:DesiredUserSessions"
resp.scalable_targets[0].min_capacity #=> Integer
resp.scalable_targets[0].max_capacity #=> Integer
resp.scalable_targets[0].predicted_capacity #=> Integer
resp.scalable_targets[0].role_arn #=> String
resp.scalable_targets[0].creation_time #=> Time
resp.scalable_targets[0].suspended_state.dynamic_scaling_in_suspended #=> Boolean
resp.scalable_targets[0].suspended_state.dynamic_scaling_out_suspended #=> Boolean
resp.scalable_targets[0].suspended_state.scheduled_scaling_suspended #=> Boolean
resp.scalable_targets[0].scalable_target_arn #=> String
resp.next_token #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :service_namespace (required, String) —

    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.

  • :resource_ids (Array<String>) —

    The identifier of the resource 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`.

    • 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`.

    [1]: github.com/aws/aws-auto-scaling-custom-resource

  • :scalable_dimension (String) —

    The scalable dimension associated with the scalable target. This string consists of the service namespace, resource type, and scaling property. If you specify a scalable dimension, you must also specify a resource ID.

    • ‘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: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.

  • :max_results (Integer) —

    The maximum number of scalable targets. This value can be between 1 and 50. The default value is 50.

    If this parameter is used, the operation returns up to ‘MaxResults` results at a time, along with a `NextToken` value. To get the next set of results, include the `NextToken` value in a subsequent call. If this parameter is not used, the operation returns up to 50 results and a `NextToken` value, if applicable.

  • :next_token (String) —

    The token for the next set of results.

Returns:

See Also:



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# File 'lib/aws-sdk-applicationautoscaling/client.rb', line 1355

def describe_scalable_targets(params = {}, options = {})
  req = build_request(:describe_scalable_targets, params)
  req.send_request(options)
end

#describe_scaling_activities(params = {}) ⇒ Types::DescribeScalingActivitiesResponse

Provides descriptive information about the scaling activities in the specified namespace from the previous six weeks.

You can filter the results using ‘ResourceId` and `ScalableDimension`.

For information about viewing scaling activities using the Amazon Web Services CLI, see [Scaling activities for Application Auto Scaling].

[1]: docs.aws.amazon.com/autoscaling/application/userguide/application-auto-scaling-scaling-activities.html

The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.

Examples:

Example: To describe scaling activities for a scalable target


# This example describes the scaling activities for an Amazon ECS service called web-app that is running in the default
# cluster.

resp = client.describe_scaling_activities({
  resource_id: "service/default/web-app", 
  scalable_dimension: "ecs:service:DesiredCount", 
  service_namespace: "ecs", 
})

resp.to_h outputs the following:
{
  scaling_activities: [
    {
      activity_id: "e6c5f7d1-dbbb-4a3f-89b2-51f33e766399", 
      cause: "monitor alarm web-app-cpu-lt-25 in state ALARM triggered policy web-app-cpu-lt-25", 
      description: "Setting desired count to 1.", 
      end_time: Time.parse("2019-05-06T16:04:32.111Z"), 
      resource_id: "service/default/web-app", 
      scalable_dimension: "ecs:service:DesiredCount", 
      service_namespace: "ecs", 
      start_time: Time.parse("2019-05-06T16:03:58.171Z"), 
      status_code: "Successful", 
      status_message: "Successfully set desired count to 1. Change successfully fulfilled by ecs.", 
    }, 
  ], 
}

Request syntax with placeholder values


resp = client.describe_scaling_activities({
  service_namespace: "ecs", # required, accepts ecs, elasticmapreduce, ec2, appstream, dynamodb, rds, sagemaker, custom-resource, comprehend, lambda, cassandra, kafka, elasticache, neptune, workspaces
  resource_id: "ResourceIdMaxLen1600",
  scalable_dimension: "ecs:service:DesiredCount", # accepts ecs:service:DesiredCount, ec2:spot-fleet-request:TargetCapacity, elasticmapreduce:instancegroup:InstanceCount, appstream:fleet:DesiredCapacity, dynamodb:table:ReadCapacityUnits, dynamodb:table:WriteCapacityUnits, dynamodb:index:ReadCapacityUnits, dynamodb:index:WriteCapacityUnits, rds:cluster:ReadReplicaCount, sagemaker:variant:DesiredInstanceCount, custom-resource:ResourceType:Property, comprehend:document-classifier-endpoint:DesiredInferenceUnits, comprehend:entity-recognizer-endpoint:DesiredInferenceUnits, lambda:function:ProvisionedConcurrency, cassandra:table:ReadCapacityUnits, cassandra:table:WriteCapacityUnits, kafka:broker-storage:VolumeSize, elasticache:replication-group:NodeGroups, elasticache:replication-group:Replicas, neptune:cluster:ReadReplicaCount, sagemaker:variant:DesiredProvisionedConcurrency, sagemaker:inference-component:DesiredCopyCount, workspaces:workspacespool:DesiredUserSessions
  max_results: 1,
  next_token: "XmlString",
  include_not_scaled_activities: false,
})

Response structure


resp.scaling_activities #=> Array
resp.scaling_activities[0].activity_id #=> String
resp.scaling_activities[0].service_namespace #=> String, one of "ecs", "elasticmapreduce", "ec2", "appstream", "dynamodb", "rds", "sagemaker", "custom-resource", "comprehend", "lambda", "cassandra", "kafka", "elasticache", "neptune", "workspaces"
resp.scaling_activities[0].resource_id #=> String
resp.scaling_activities[0].scalable_dimension #=> String, one of "ecs:service:DesiredCount", "ec2:spot-fleet-request:TargetCapacity", "elasticmapreduce:instancegroup:InstanceCount", "appstream:fleet:DesiredCapacity", "dynamodb:table:ReadCapacityUnits", "dynamodb:table:WriteCapacityUnits", "dynamodb:index:ReadCapacityUnits", "dynamodb:index:WriteCapacityUnits", "rds:cluster:ReadReplicaCount", "sagemaker:variant:DesiredInstanceCount", "custom-resource:ResourceType:Property", "comprehend:document-classifier-endpoint:DesiredInferenceUnits", "comprehend:entity-recognizer-endpoint:DesiredInferenceUnits", "lambda:function:ProvisionedConcurrency", "cassandra:table:ReadCapacityUnits", "cassandra:table:WriteCapacityUnits", "kafka:broker-storage:VolumeSize", "elasticache:replication-group:NodeGroups", "elasticache:replication-group:Replicas", "neptune:cluster:ReadReplicaCount", "sagemaker:variant:DesiredProvisionedConcurrency", "sagemaker:inference-component:DesiredCopyCount", "workspaces:workspacespool:DesiredUserSessions"
resp.scaling_activities[0].description #=> String
resp.scaling_activities[0].cause #=> String
resp.scaling_activities[0].start_time #=> Time
resp.scaling_activities[0].end_time #=> Time
resp.scaling_activities[0].status_code #=> String, one of "Pending", "InProgress", "Successful", "Overridden", "Unfulfilled", "Failed"
resp.scaling_activities[0].status_message #=> String
resp.scaling_activities[0].details #=> String
resp.scaling_activities[0].not_scaled_reasons #=> Array
resp.scaling_activities[0].not_scaled_reasons[0].code #=> String
resp.scaling_activities[0].not_scaled_reasons[0].max_capacity #=> Integer
resp.scaling_activities[0].not_scaled_reasons[0].min_capacity #=> Integer
resp.scaling_activities[0].not_scaled_reasons[0].current_capacity #=> Integer
resp.next_token #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :service_namespace (required, String) —

    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.

  • :resource_id (String) —

    The identifier of the resource associated with the scaling activity. 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`.

    • 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`.

    [1]: github.com/aws/aws-auto-scaling-custom-resource

  • :scalable_dimension (String) —

    The scalable dimension. This string consists of the service namespace, resource type, and scaling property. If you specify a scalable dimension, you must also specify a resource ID.

    • ‘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: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.

  • :max_results (Integer) —

    The maximum number of scalable targets. This value can be between 1 and 50. The default value is 50.

    If this parameter is used, the operation returns up to ‘MaxResults` results at a time, along with a `NextToken` value. To get the next set of results, include the `NextToken` value in a subsequent call. If this parameter is not used, the operation returns up to 50 results and a `NextToken` value, if applicable.

  • :next_token (String) —

    The token for the next set of results.

  • :include_not_scaled_activities (Boolean) —

    Specifies whether to include activities that aren’t scaled (*not scaled activities*) in the response. Not scaled activities are activities that aren’t completed or started for various reasons, such as preventing infinite scaling loops. For help interpreting the not scaled reason details in the response, see [Scaling activities for Application Auto Scaling].

    [1]: docs.aws.amazon.com/autoscaling/application/userguide/application-auto-scaling-scaling-activities.html

Returns:

See Also:



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# File 'lib/aws-sdk-applicationautoscaling/client.rb', line 1636

def describe_scaling_activities(params = {}, options = {})
  req = build_request(:describe_scaling_activities, params)
  req.send_request(options)
end

#describe_scaling_policies(params = {}) ⇒ Types::DescribeScalingPoliciesResponse

Describes the Application Auto Scaling scaling policies for the specified service namespace.

You can filter the results using ‘ResourceId`, `ScalableDimension`, and `PolicyNames`.

For more information, see [Target tracking scaling policies] and

Step scaling policies][2

in the *Application Auto Scaling User

Guide*.

[1]: docs.aws.amazon.com/autoscaling/application/userguide/application-auto-scaling-target-tracking.html [2]: docs.aws.amazon.com/autoscaling/application/userguide/application-auto-scaling-step-scaling-policies.html

The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.

Examples:

Example: To describe scaling policies


# This example describes the scaling policies for the ECS service namespace.

resp = client.describe_scaling_policies({
  service_namespace: "ecs", 
})

resp.to_h outputs the following:
{
  next_token: "", 
  scaling_policies: [
    {
      alarms: [
        {
          alarm_arn: "arn:aws:cloudwatch:us-west-2:012345678910:alarm:web-app-cpu-gt-75", 
          alarm_name: "web-app-cpu-gt-75", 
        }, 
      ], 
      creation_time: Time.parse("2019-05-06T12:11:39.230Z"), 
      policy_arn: "arn:aws:autoscaling:us-west-2:012345678910:scalingPolicy:6d8972f3-efc8-437c-92d1-6270f29a66e7:resource/ecs/service/default/web-app:policyName/web-app-cpu-gt-75", 
      policy_name: "web-app-cpu-gt-75", 
      policy_type: "StepScaling", 
      resource_id: "service/default/web-app", 
      scalable_dimension: "ecs:service:DesiredCount", 
      service_namespace: "ecs", 
      step_scaling_policy_configuration: {
        adjustment_type: "PercentChangeInCapacity", 
        cooldown: 60, 
        step_adjustments: [
          {
            metric_interval_lower_bound: 0, 
            scaling_adjustment: 200, 
          }, 
        ], 
      }, 
    }, 
  ], 
}

Request syntax with placeholder values


resp = client.describe_scaling_policies({
  policy_names: ["ResourceIdMaxLen1600"],
  service_namespace: "ecs", # required, accepts ecs, elasticmapreduce, ec2, appstream, dynamodb, rds, sagemaker, custom-resource, comprehend, lambda, cassandra, kafka, elasticache, neptune, workspaces
  resource_id: "ResourceIdMaxLen1600",
  scalable_dimension: "ecs:service:DesiredCount", # accepts ecs:service:DesiredCount, ec2:spot-fleet-request:TargetCapacity, elasticmapreduce:instancegroup:InstanceCount, appstream:fleet:DesiredCapacity, dynamodb:table:ReadCapacityUnits, dynamodb:table:WriteCapacityUnits, dynamodb:index:ReadCapacityUnits, dynamodb:index:WriteCapacityUnits, rds:cluster:ReadReplicaCount, sagemaker:variant:DesiredInstanceCount, custom-resource:ResourceType:Property, comprehend:document-classifier-endpoint:DesiredInferenceUnits, comprehend:entity-recognizer-endpoint:DesiredInferenceUnits, lambda:function:ProvisionedConcurrency, cassandra:table:ReadCapacityUnits, cassandra:table:WriteCapacityUnits, kafka:broker-storage:VolumeSize, elasticache:replication-group:NodeGroups, elasticache:replication-group:Replicas, neptune:cluster:ReadReplicaCount, sagemaker:variant:DesiredProvisionedConcurrency, sagemaker:inference-component:DesiredCopyCount, workspaces:workspacespool:DesiredUserSessions
  max_results: 1,
  next_token: "XmlString",
})

Response structure


resp.scaling_policies #=> Array
resp.scaling_policies[0].policy_arn #=> String
resp.scaling_policies[0].policy_name #=> String
resp.scaling_policies[0].service_namespace #=> String, one of "ecs", "elasticmapreduce", "ec2", "appstream", "dynamodb", "rds", "sagemaker", "custom-resource", "comprehend", "lambda", "cassandra", "kafka", "elasticache", "neptune", "workspaces"
resp.scaling_policies[0].resource_id #=> String
resp.scaling_policies[0].scalable_dimension #=> String, one of "ecs:service:DesiredCount", "ec2:spot-fleet-request:TargetCapacity", "elasticmapreduce:instancegroup:InstanceCount", "appstream:fleet:DesiredCapacity", "dynamodb:table:ReadCapacityUnits", "dynamodb:table:WriteCapacityUnits", "dynamodb:index:ReadCapacityUnits", "dynamodb:index:WriteCapacityUnits", "rds:cluster:ReadReplicaCount", "sagemaker:variant:DesiredInstanceCount", "custom-resource:ResourceType:Property", "comprehend:document-classifier-endpoint:DesiredInferenceUnits", "comprehend:entity-recognizer-endpoint:DesiredInferenceUnits", "lambda:function:ProvisionedConcurrency", "cassandra:table:ReadCapacityUnits", "cassandra:table:WriteCapacityUnits", "kafka:broker-storage:VolumeSize", "elasticache:replication-group:NodeGroups", "elasticache:replication-group:Replicas", "neptune:cluster:ReadReplicaCount", "sagemaker:variant:DesiredProvisionedConcurrency", "sagemaker:inference-component:DesiredCopyCount", "workspaces:workspacespool:DesiredUserSessions"
resp.scaling_policies[0].policy_type #=> String, one of "StepScaling", "TargetTrackingScaling", "PredictiveScaling"
resp.scaling_policies[0].step_scaling_policy_configuration.adjustment_type #=> String, one of "ChangeInCapacity", "PercentChangeInCapacity", "ExactCapacity"
resp.scaling_policies[0].step_scaling_policy_configuration.step_adjustments #=> Array
resp.scaling_policies[0].step_scaling_policy_configuration.step_adjustments[0].metric_interval_lower_bound #=> Float
resp.scaling_policies[0].step_scaling_policy_configuration.step_adjustments[0].metric_interval_upper_bound #=> Float
resp.scaling_policies[0].step_scaling_policy_configuration.step_adjustments[0].scaling_adjustment #=> Integer
resp.scaling_policies[0].step_scaling_policy_configuration.min_adjustment_magnitude #=> Integer
resp.scaling_policies[0].step_scaling_policy_configuration.cooldown #=> Integer
resp.scaling_policies[0].step_scaling_policy_configuration.metric_aggregation_type #=> String, one of "Average", "Minimum", "Maximum"
resp.scaling_policies[0].target_tracking_scaling_policy_configuration.target_value #=> Float
resp.scaling_policies[0].target_tracking_scaling_policy_configuration.predefined_metric_specification.predefined_metric_type #=> String, one of "DynamoDBReadCapacityUtilization", "DynamoDBWriteCapacityUtilization", "ALBRequestCountPerTarget", "RDSReaderAverageCPUUtilization", "RDSReaderAverageDatabaseConnections", "EC2SpotFleetRequestAverageCPUUtilization", "EC2SpotFleetRequestAverageNetworkIn", "EC2SpotFleetRequestAverageNetworkOut", "SageMakerVariantInvocationsPerInstance", "ECSServiceAverageCPUUtilization", "ECSServiceAverageMemoryUtilization", "AppStreamAverageCapacityUtilization", "ComprehendInferenceUtilization", "LambdaProvisionedConcurrencyUtilization", "CassandraReadCapacityUtilization", "CassandraWriteCapacityUtilization", "KafkaBrokerStorageUtilization", "ElastiCachePrimaryEngineCPUUtilization", "ElastiCacheReplicaEngineCPUUtilization", "ElastiCacheDatabaseMemoryUsageCountedForEvictPercentage", "NeptuneReaderAverageCPUUtilization", "SageMakerVariantProvisionedConcurrencyUtilization", "ElastiCacheDatabaseCapacityUsageCountedForEvictPercentage", "SageMakerInferenceComponentInvocationsPerCopy", "WorkSpacesAverageUserSessionsCapacityUtilization", "SageMakerInferenceComponentConcurrentRequestsPerCopyHighResolution", "SageMakerVariantConcurrentRequestsPerModelHighResolution"
resp.scaling_policies[0].target_tracking_scaling_policy_configuration.predefined_metric_specification.resource_label #=> String
resp.scaling_policies[0].target_tracking_scaling_policy_configuration.customized_metric_specification.metric_name #=> String
resp.scaling_policies[0].target_tracking_scaling_policy_configuration.customized_metric_specification.namespace #=> String
resp.scaling_policies[0].target_tracking_scaling_policy_configuration.customized_metric_specification.dimensions #=> Array
resp.scaling_policies[0].target_tracking_scaling_policy_configuration.customized_metric_specification.dimensions[0].name #=> String
resp.scaling_policies[0].target_tracking_scaling_policy_configuration.customized_metric_specification.dimensions[0].value #=> String
resp.scaling_policies[0].target_tracking_scaling_policy_configuration.customized_metric_specification.statistic #=> String, one of "Average", "Minimum", "Maximum", "SampleCount", "Sum"
resp.scaling_policies[0].target_tracking_scaling_policy_configuration.customized_metric_specification.unit #=> String
resp.scaling_policies[0].target_tracking_scaling_policy_configuration.customized_metric_specification.metrics #=> Array
resp.scaling_policies[0].target_tracking_scaling_policy_configuration.customized_metric_specification.metrics[0].expression #=> String
resp.scaling_policies[0].target_tracking_scaling_policy_configuration.customized_metric_specification.metrics[0].id #=> String
resp.scaling_policies[0].target_tracking_scaling_policy_configuration.customized_metric_specification.metrics[0].label #=> String
resp.scaling_policies[0].target_tracking_scaling_policy_configuration.customized_metric_specification.metrics[0].metric_stat.metric.dimensions #=> Array
resp.scaling_policies[0].target_tracking_scaling_policy_configuration.customized_metric_specification.metrics[0].metric_stat.metric.dimensions[0].name #=> String
resp.scaling_policies[0].target_tracking_scaling_policy_configuration.customized_metric_specification.metrics[0].metric_stat.metric.dimensions[0].value #=> String
resp.scaling_policies[0].target_tracking_scaling_policy_configuration.customized_metric_specification.metrics[0].metric_stat.metric.metric_name #=> String
resp.scaling_policies[0].target_tracking_scaling_policy_configuration.customized_metric_specification.metrics[0].metric_stat.metric.namespace #=> String
resp.scaling_policies[0].target_tracking_scaling_policy_configuration.customized_metric_specification.metrics[0].metric_stat.stat #=> String
resp.scaling_policies[0].target_tracking_scaling_policy_configuration.customized_metric_specification.metrics[0].metric_stat.unit #=> String
resp.scaling_policies[0].target_tracking_scaling_policy_configuration.customized_metric_specification.metrics[0].return_data #=> Boolean
resp.scaling_policies[0].target_tracking_scaling_policy_configuration.scale_out_cooldown #=> Integer
resp.scaling_policies[0].target_tracking_scaling_policy_configuration.scale_in_cooldown #=> Integer
resp.scaling_policies[0].target_tracking_scaling_policy_configuration.disable_scale_in #=> Boolean
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications #=> Array
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].target_value #=> Float
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].predefined_metric_pair_specification.predefined_metric_type #=> String
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].predefined_metric_pair_specification.resource_label #=> String
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].predefined_scaling_metric_specification.predefined_metric_type #=> String
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].predefined_scaling_metric_specification.resource_label #=> String
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].predefined_load_metric_specification.predefined_metric_type #=> String
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].predefined_load_metric_specification.resource_label #=> String
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].customized_scaling_metric_specification.metric_data_queries #=> Array
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].customized_scaling_metric_specification.metric_data_queries[0].id #=> String
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].customized_scaling_metric_specification.metric_data_queries[0].expression #=> String
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].customized_scaling_metric_specification.metric_data_queries[0].metric_stat.metric.dimensions #=> Array
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].customized_scaling_metric_specification.metric_data_queries[0].metric_stat.metric.dimensions[0].name #=> String
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].customized_scaling_metric_specification.metric_data_queries[0].metric_stat.metric.dimensions[0].value #=> String
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].customized_scaling_metric_specification.metric_data_queries[0].metric_stat.metric.metric_name #=> String
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].customized_scaling_metric_specification.metric_data_queries[0].metric_stat.metric.namespace #=> String
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].customized_scaling_metric_specification.metric_data_queries[0].metric_stat.stat #=> String
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].customized_scaling_metric_specification.metric_data_queries[0].metric_stat.unit #=> String
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].customized_scaling_metric_specification.metric_data_queries[0].label #=> String
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].customized_scaling_metric_specification.metric_data_queries[0].return_data #=> Boolean
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].customized_load_metric_specification.metric_data_queries #=> Array
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].customized_load_metric_specification.metric_data_queries[0].id #=> String
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].customized_load_metric_specification.metric_data_queries[0].expression #=> String
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].customized_load_metric_specification.metric_data_queries[0].metric_stat.metric.dimensions #=> Array
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].customized_load_metric_specification.metric_data_queries[0].metric_stat.metric.dimensions[0].name #=> String
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].customized_load_metric_specification.metric_data_queries[0].metric_stat.metric.dimensions[0].value #=> String
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].customized_load_metric_specification.metric_data_queries[0].metric_stat.metric.metric_name #=> String
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].customized_load_metric_specification.metric_data_queries[0].metric_stat.metric.namespace #=> String
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].customized_load_metric_specification.metric_data_queries[0].metric_stat.stat #=> String
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].customized_load_metric_specification.metric_data_queries[0].metric_stat.unit #=> String
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].customized_load_metric_specification.metric_data_queries[0].label #=> String
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].customized_load_metric_specification.metric_data_queries[0].return_data #=> Boolean
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].customized_capacity_metric_specification.metric_data_queries #=> Array
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].customized_capacity_metric_specification.metric_data_queries[0].id #=> String
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].customized_capacity_metric_specification.metric_data_queries[0].expression #=> String
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].customized_capacity_metric_specification.metric_data_queries[0].metric_stat.metric.dimensions #=> Array
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].customized_capacity_metric_specification.metric_data_queries[0].metric_stat.metric.dimensions[0].name #=> String
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].customized_capacity_metric_specification.metric_data_queries[0].metric_stat.metric.dimensions[0].value #=> String
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].customized_capacity_metric_specification.metric_data_queries[0].metric_stat.metric.metric_name #=> String
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].customized_capacity_metric_specification.metric_data_queries[0].metric_stat.metric.namespace #=> String
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].customized_capacity_metric_specification.metric_data_queries[0].metric_stat.stat #=> String
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].customized_capacity_metric_specification.metric_data_queries[0].metric_stat.unit #=> String
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].customized_capacity_metric_specification.metric_data_queries[0].label #=> String
resp.scaling_policies[0].predictive_scaling_policy_configuration.metric_specifications[0].customized_capacity_metric_specification.metric_data_queries[0].return_data #=> Boolean
resp.scaling_policies[0].predictive_scaling_policy_configuration.mode #=> String, one of "ForecastOnly", "ForecastAndScale"
resp.scaling_policies[0].predictive_scaling_policy_configuration.scheduling_buffer_time #=> Integer
resp.scaling_policies[0].predictive_scaling_policy_configuration.max_capacity_breach_behavior #=> String, one of "HonorMaxCapacity", "IncreaseMaxCapacity"
resp.scaling_policies[0].predictive_scaling_policy_configuration.max_capacity_buffer #=> Integer
resp.scaling_policies[0].alarms #=> Array
resp.scaling_policies[0].alarms[0].alarm_name #=> String
resp.scaling_policies[0].alarms[0].alarm_arn #=> String
resp.scaling_policies[0].creation_time #=> Time
resp.next_token #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :policy_names (Array<String>) —

    The names of the scaling policies to describe.

  • :service_namespace (required, String) —

    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.

  • :resource_id (String) —

    The identifier of the resource associated with the scaling policy. 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`.

    • 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`.

    [1]: github.com/aws/aws-auto-scaling-custom-resource

  • :scalable_dimension (String) —

    The scalable dimension. This string consists of the service namespace, resource type, and scaling property. If you specify a scalable dimension, you must also specify a resource ID.

    • ‘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: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.

  • :max_results (Integer) —

    The maximum number of scalable targets. This value can be between 1 and 10. The default value is 10.

    If this parameter is used, the operation returns up to ‘MaxResults` results at a time, along with a `NextToken` value. To get the next set of results, include the `NextToken` value in a subsequent call. If this parameter is not used, the operation returns up to 10 results and a `NextToken` value, if applicable.

  • :next_token (String) —

    The token for the next set of results.

Returns:

See Also:



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# File 'lib/aws-sdk-applicationautoscaling/client.rb', line 1996

def describe_scaling_policies(params = {}, options = {})
  req = build_request(:describe_scaling_policies, params)
  req.send_request(options)
end

#describe_scheduled_actions(params = {}) ⇒ Types::DescribeScheduledActionsResponse

Describes the Application Auto Scaling scheduled actions for the specified service namespace.

You can filter the results using the ‘ResourceId`, `ScalableDimension`, and `ScheduledActionNames` parameters.

For more information, see [Scheduled scaling] in the *Application Auto Scaling User Guide*.

[1]: docs.aws.amazon.com/autoscaling/application/userguide/application-auto-scaling-scheduled-scaling.html

The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.

Examples:

Example: To describe scheduled actions


# This example describes the scheduled actions for the dynamodb service namespace.

resp = client.describe_scheduled_actions({
  service_namespace: "dynamodb", 
})

resp.to_h outputs the following:
{
  scheduled_actions: [
    {
      creation_time: Time.parse(1561571888.361), 
      resource_id: "table/my-table", 
      scalable_dimension: "dynamodb:table:WriteCapacityUnits", 
      scalable_target_action: {
        max_capacity: 20, 
        min_capacity: 15, 
      }, 
      schedule: "at(2019-05-20T18:35:00)", 
      scheduled_action_arn: "arn:aws:autoscaling:us-west-2:123456789012:scheduledAction:2d36aa3b-cdf9-4565-b290-81db519b227d:resource/dynamodb/table/my-table:scheduledActionName/my-first-scheduled-action", 
      scheduled_action_name: "my-first-scheduled-action", 
      service_namespace: "dynamodb", 
    }, 
    {
      creation_time: Time.parse(1561571946.021), 
      resource_id: "table/my-table", 
      scalable_dimension: "dynamodb:table:WriteCapacityUnits", 
      scalable_target_action: {
        max_capacity: 10, 
        min_capacity: 5, 
      }, 
      schedule: "at(2019-05-20T18:40:00)", 
      scheduled_action_arn: "arn:aws:autoscaling:us-west-2:123456789012:scheduledAction:2d36aa3b-cdf9-4565-b290-81db519b227d:resource/dynamodb/table/my-table:scheduledActionName/my-second-scheduled-action", 
      scheduled_action_name: "my-second-scheduled-action", 
      service_namespace: "dynamodb", 
    }, 
  ], 
}

Request syntax with placeholder values


resp = client.describe_scheduled_actions({
  scheduled_action_names: ["ResourceIdMaxLen1600"],
  service_namespace: "ecs", # required, accepts ecs, elasticmapreduce, ec2, appstream, dynamodb, rds, sagemaker, custom-resource, comprehend, lambda, cassandra, kafka, elasticache, neptune, workspaces
  resource_id: "ResourceIdMaxLen1600",
  scalable_dimension: "ecs:service:DesiredCount", # accepts ecs:service:DesiredCount, ec2:spot-fleet-request:TargetCapacity, elasticmapreduce:instancegroup:InstanceCount, appstream:fleet:DesiredCapacity, dynamodb:table:ReadCapacityUnits, dynamodb:table:WriteCapacityUnits, dynamodb:index:ReadCapacityUnits, dynamodb:index:WriteCapacityUnits, rds:cluster:ReadReplicaCount, sagemaker:variant:DesiredInstanceCount, custom-resource:ResourceType:Property, comprehend:document-classifier-endpoint:DesiredInferenceUnits, comprehend:entity-recognizer-endpoint:DesiredInferenceUnits, lambda:function:ProvisionedConcurrency, cassandra:table:ReadCapacityUnits, cassandra:table:WriteCapacityUnits, kafka:broker-storage:VolumeSize, elasticache:replication-group:NodeGroups, elasticache:replication-group:Replicas, neptune:cluster:ReadReplicaCount, sagemaker:variant:DesiredProvisionedConcurrency, sagemaker:inference-component:DesiredCopyCount, workspaces:workspacespool:DesiredUserSessions
  max_results: 1,
  next_token: "XmlString",
})

Response structure


resp.scheduled_actions #=> Array
resp.scheduled_actions[0].scheduled_action_name #=> String
resp.scheduled_actions[0].scheduled_action_arn #=> String
resp.scheduled_actions[0].service_namespace #=> String, one of "ecs", "elasticmapreduce", "ec2", "appstream", "dynamodb", "rds", "sagemaker", "custom-resource", "comprehend", "lambda", "cassandra", "kafka", "elasticache", "neptune", "workspaces"
resp.scheduled_actions[0].schedule #=> String
resp.scheduled_actions[0].timezone #=> String
resp.scheduled_actions[0].resource_id #=> String
resp.scheduled_actions[0].scalable_dimension #=> String, one of "ecs:service:DesiredCount", "ec2:spot-fleet-request:TargetCapacity", "elasticmapreduce:instancegroup:InstanceCount", "appstream:fleet:DesiredCapacity", "dynamodb:table:ReadCapacityUnits", "dynamodb:table:WriteCapacityUnits", "dynamodb:index:ReadCapacityUnits", "dynamodb:index:WriteCapacityUnits", "rds:cluster:ReadReplicaCount", "sagemaker:variant:DesiredInstanceCount", "custom-resource:ResourceType:Property", "comprehend:document-classifier-endpoint:DesiredInferenceUnits", "comprehend:entity-recognizer-endpoint:DesiredInferenceUnits", "lambda:function:ProvisionedConcurrency", "cassandra:table:ReadCapacityUnits", "cassandra:table:WriteCapacityUnits", "kafka:broker-storage:VolumeSize", "elasticache:replication-group:NodeGroups", "elasticache:replication-group:Replicas", "neptune:cluster:ReadReplicaCount", "sagemaker:variant:DesiredProvisionedConcurrency", "sagemaker:inference-component:DesiredCopyCount", "workspaces:workspacespool:DesiredUserSessions"
resp.scheduled_actions[0].start_time #=> Time
resp.scheduled_actions[0].end_time #=> Time
resp.scheduled_actions[0].scalable_target_action.min_capacity #=> Integer
resp.scheduled_actions[0].scalable_target_action.max_capacity #=> Integer
resp.scheduled_actions[0].creation_time #=> Time
resp.next_token #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :scheduled_action_names (Array<String>) —

    The names of the scheduled actions to describe.

  • :service_namespace (required, String) —

    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.

  • :resource_id (String) —

    The identifier of the resource associated with the scheduled action. 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`.

    • 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`.

    [1]: github.com/aws/aws-auto-scaling-custom-resource

  • :scalable_dimension (String) —

    The scalable dimension. This string consists of the service namespace, resource type, and scaling property. If you specify a scalable dimension, you must also specify a resource ID.

    • ‘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: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.

  • :max_results (Integer) —

    The maximum number of scheduled action results. This value can be between 1 and 50. The default value is 50.

    If this parameter is used, the operation returns up to ‘MaxResults` results at a time, along with a `NextToken` value. To get the next set of results, include the `NextToken` value in a subsequent call. If this parameter is not used, the operation returns up to 50 results and a `NextToken` value, if applicable.

  • :next_token (String) —

    The token for the next set of results.

Returns:

See Also:



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# File 'lib/aws-sdk-applicationautoscaling/client.rb', line 2275

def describe_scheduled_actions(params = {}, options = {})
  req = build_request(:describe_scheduled_actions, params)
  req.send_request(options)
end

#get_predictive_scaling_forecast(params = {}) ⇒ Types::GetPredictiveScalingForecastResponse

Retrieves the forecast data for a predictive scaling policy.

Load forecasts are predictions of the hourly load values using historical load data from CloudWatch and an analysis of historical trends. Capacity forecasts are represented as predicted values for the minimum capacity that is needed on an hourly basis, based on the hourly load forecast.

A minimum of 24 hours of data is required to create the initial forecasts. However, having a full 14 days of historical data results in more accurate forecasts.

Examples:

Request syntax with placeholder values


resp = client.get_predictive_scaling_forecast({
  service_namespace: "ecs", # required, accepts ecs, elasticmapreduce, ec2, appstream, dynamodb, rds, sagemaker, custom-resource, comprehend, lambda, cassandra, kafka, elasticache, neptune, workspaces
  resource_id: "ResourceIdMaxLen1600", # required
  scalable_dimension: "ecs:service:DesiredCount", # required, accepts ecs:service:DesiredCount, ec2:spot-fleet-request:TargetCapacity, elasticmapreduce:instancegroup:InstanceCount, appstream:fleet:DesiredCapacity, dynamodb:table:ReadCapacityUnits, dynamodb:table:WriteCapacityUnits, dynamodb:index:ReadCapacityUnits, dynamodb:index:WriteCapacityUnits, rds:cluster:ReadReplicaCount, sagemaker:variant:DesiredInstanceCount, custom-resource:ResourceType:Property, comprehend:document-classifier-endpoint:DesiredInferenceUnits, comprehend:entity-recognizer-endpoint:DesiredInferenceUnits, lambda:function:ProvisionedConcurrency, cassandra:table:ReadCapacityUnits, cassandra:table:WriteCapacityUnits, kafka:broker-storage:VolumeSize, elasticache:replication-group:NodeGroups, elasticache:replication-group:Replicas, neptune:cluster:ReadReplicaCount, sagemaker:variant:DesiredProvisionedConcurrency, sagemaker:inference-component:DesiredCopyCount, workspaces:workspacespool:DesiredUserSessions
  policy_name: "PolicyName", # required
  start_time: Time.now, # required
  end_time: Time.now, # required
})

Response structure


resp.load_forecast #=> Array
resp.load_forecast[0].timestamps #=> Array
resp.load_forecast[0].timestamps[0] #=> Time
resp.load_forecast[0].values #=> Array
resp.load_forecast[0].values[0] #=> Float
resp.load_forecast[0].metric_specification.target_value #=> Float
resp.load_forecast[0].metric_specification.predefined_metric_pair_specification.predefined_metric_type #=> String
resp.load_forecast[0].metric_specification.predefined_metric_pair_specification.resource_label #=> String
resp.load_forecast[0].metric_specification.predefined_scaling_metric_specification.predefined_metric_type #=> String
resp.load_forecast[0].metric_specification.predefined_scaling_metric_specification.resource_label #=> String
resp.load_forecast[0].metric_specification.predefined_load_metric_specification.predefined_metric_type #=> String
resp.load_forecast[0].metric_specification.predefined_load_metric_specification.resource_label #=> String
resp.load_forecast[0].metric_specification.customized_scaling_metric_specification.metric_data_queries #=> Array
resp.load_forecast[0].metric_specification.customized_scaling_metric_specification.metric_data_queries[0].id #=> String
resp.load_forecast[0].metric_specification.customized_scaling_metric_specification.metric_data_queries[0].expression #=> String
resp.load_forecast[0].metric_specification.customized_scaling_metric_specification.metric_data_queries[0].metric_stat.metric.dimensions #=> Array
resp.load_forecast[0].metric_specification.customized_scaling_metric_specification.metric_data_queries[0].metric_stat.metric.dimensions[0].name #=> String
resp.load_forecast[0].metric_specification.customized_scaling_metric_specification.metric_data_queries[0].metric_stat.metric.dimensions[0].value #=> String
resp.load_forecast[0].metric_specification.customized_scaling_metric_specification.metric_data_queries[0].metric_stat.metric.metric_name #=> String
resp.load_forecast[0].metric_specification.customized_scaling_metric_specification.metric_data_queries[0].metric_stat.metric.namespace #=> String
resp.load_forecast[0].metric_specification.customized_scaling_metric_specification.metric_data_queries[0].metric_stat.stat #=> String
resp.load_forecast[0].metric_specification.customized_scaling_metric_specification.metric_data_queries[0].metric_stat.unit #=> String
resp.load_forecast[0].metric_specification.customized_scaling_metric_specification.metric_data_queries[0].label #=> String
resp.load_forecast[0].metric_specification.customized_scaling_metric_specification.metric_data_queries[0].return_data #=> Boolean
resp.load_forecast[0].metric_specification.customized_load_metric_specification.metric_data_queries #=> Array
resp.load_forecast[0].metric_specification.customized_load_metric_specification.metric_data_queries[0].id #=> String
resp.load_forecast[0].metric_specification.customized_load_metric_specification.metric_data_queries[0].expression #=> String
resp.load_forecast[0].metric_specification.customized_load_metric_specification.metric_data_queries[0].metric_stat.metric.dimensions #=> Array
resp.load_forecast[0].metric_specification.customized_load_metric_specification.metric_data_queries[0].metric_stat.metric.dimensions[0].name #=> String
resp.load_forecast[0].metric_specification.customized_load_metric_specification.metric_data_queries[0].metric_stat.metric.dimensions[0].value #=> String
resp.load_forecast[0].metric_specification.customized_load_metric_specification.metric_data_queries[0].metric_stat.metric.metric_name #=> String
resp.load_forecast[0].metric_specification.customized_load_metric_specification.metric_data_queries[0].metric_stat.metric.namespace #=> String
resp.load_forecast[0].metric_specification.customized_load_metric_specification.metric_data_queries[0].metric_stat.stat #=> String
resp.load_forecast[0].metric_specification.customized_load_metric_specification.metric_data_queries[0].metric_stat.unit #=> String
resp.load_forecast[0].metric_specification.customized_load_metric_specification.metric_data_queries[0].label #=> String
resp.load_forecast[0].metric_specification.customized_load_metric_specification.metric_data_queries[0].return_data #=> Boolean
resp.load_forecast[0].metric_specification.customized_capacity_metric_specification.metric_data_queries #=> Array
resp.load_forecast[0].metric_specification.customized_capacity_metric_specification.metric_data_queries[0].id #=> String
resp.load_forecast[0].metric_specification.customized_capacity_metric_specification.metric_data_queries[0].expression #=> String
resp.load_forecast[0].metric_specification.customized_capacity_metric_specification.metric_data_queries[0].metric_stat.metric.dimensions #=> Array
resp.load_forecast[0].metric_specification.customized_capacity_metric_specification.metric_data_queries[0].metric_stat.metric.dimensions[0].name #=> String
resp.load_forecast[0].metric_specification.customized_capacity_metric_specification.metric_data_queries[0].metric_stat.metric.dimensions[0].value #=> String
resp.load_forecast[0].metric_specification.customized_capacity_metric_specification.metric_data_queries[0].metric_stat.metric.metric_name #=> String
resp.load_forecast[0].metric_specification.customized_capacity_metric_specification.metric_data_queries[0].metric_stat.metric.namespace #=> String
resp.load_forecast[0].metric_specification.customized_capacity_metric_specification.metric_data_queries[0].metric_stat.stat #=> String
resp.load_forecast[0].metric_specification.customized_capacity_metric_specification.metric_data_queries[0].metric_stat.unit #=> String
resp.load_forecast[0].metric_specification.customized_capacity_metric_specification.metric_data_queries[0].label #=> String
resp.load_forecast[0].metric_specification.customized_capacity_metric_specification.metric_data_queries[0].return_data #=> Boolean
resp.capacity_forecast.timestamps #=> Array
resp.capacity_forecast.timestamps[0] #=> Time
resp.capacity_forecast.values #=> Array
resp.capacity_forecast.values[0] #=> Float
resp.update_time #=> Time

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :service_namespace (required, String) —

    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.

  • :resource_id (required, String) —

    The identifier of the resource.

  • :scalable_dimension (required, String) —

    The scalable dimension.

  • :policy_name (required, String) —

    The name of the policy.

  • :start_time (required, Time, DateTime, Date, Integer, String) —

    The inclusive start time of the time range for the forecast data to get. At most, the date and time can be one year before the current date and time

  • :end_time (required, Time, DateTime, Date, Integer, String) —

    The exclusive end time of the time range for the forecast data to get. The maximum time duration between the start and end time is 30 days.

Returns:

See Also:



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# File 'lib/aws-sdk-applicationautoscaling/client.rb', line 2392

def get_predictive_scaling_forecast(params = {}, options = {})
  req = build_request(:get_predictive_scaling_forecast, params)
  req.send_request(options)
end

#list_tags_for_resource(params = {}) ⇒ Types::ListTagsForResourceResponse

Returns all the tags on the specified Application Auto Scaling scalable target.

For general information about tags, including the format and syntax, see [Tagging your Amazon Web Services resources] in the *Amazon Web Services General Reference*.

[1]: docs.aws.amazon.com/general/latest/gr/aws_tagging.html

Examples:

Example: To list tags for a scalable target


# This example lists the tag key names and values that are attached to the scalable target specified by its ARN.

resp = client.list_tags_for_resource({
  resource_arn: "arn:aws:application-autoscaling:us-west-2:123456789012:scalable-target/1234abcd56ab78cd901ef1234567890ab123", 
})

resp.to_h outputs the following:
{
  tags: {
    "environment" => "production", 
  }, 
}

Request syntax with placeholder values


resp = client.list_tags_for_resource({
  resource_arn: "AmazonResourceName", # required
})

Response structure


resp.tags #=> Hash
resp.tags["TagKey"] #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :resource_arn (required, String) —

    Specify the ARN of the scalable target.

    For example: ‘arn:aws:application-autoscaling:us-east-1:123456789012:scalable-target/1234abcd56ab78cd901ef1234567890ab123`

    To get the ARN for a scalable target, use DescribeScalableTargets.

Returns:

See Also:



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# File 'lib/aws-sdk-applicationautoscaling/client.rb', line 2451

def list_tags_for_resource(params = {}, options = {})
  req = build_request(:list_tags_for_resource, params)
  req.send_request(options)
end

#put_scaling_policy(params = {}) ⇒ Types::PutScalingPolicyResponse

Creates or updates a scaling policy for an Application Auto Scaling scalable target.

Each scalable target is identified by a service namespace, resource ID, and scalable dimension. A scaling policy applies to the scalable target identified by those three attributes. You cannot create a scaling policy until you have registered the resource as a scalable target.

Multiple scaling policies can be in force at the same time for the same scalable target. You can have one or more target tracking scaling policies, one or more step scaling policies, or both. However, there is a chance that multiple policies could conflict, instructing the scalable target to scale out or in at the same time. Application Auto Scaling gives precedence to the policy that provides the largest capacity for both scale out and scale in. For example, if one policy increases capacity by 3, another policy increases capacity by 200 percent, and the current capacity is 10, Application Auto Scaling uses the policy with the highest calculated capacity (200% of 10 = 20) and scales out to 30.

We recommend caution, however, when using target tracking scaling policies with step scaling policies because conflicts between these policies can cause undesirable behavior. For example, if the step scaling policy initiates a scale-in activity before the target tracking policy is ready to scale in, the scale-in activity will not be blocked. After the scale-in activity completes, the target tracking policy could instruct the scalable target to scale out again.

For more information, see [Target tracking scaling policies] and

Step scaling policies][2

in the *Application Auto Scaling User

Guide*.

<note markdown=“1”> If a scalable target is deregistered, the scalable target is no longer available to use scaling policies. Any scaling policies that were specified for the scalable target are deleted.

</note>

[1]: docs.aws.amazon.com/autoscaling/application/userguide/application-auto-scaling-target-tracking.html [2]: docs.aws.amazon.com/autoscaling/application/userguide/application-auto-scaling-step-scaling-policies.html

Examples:

Example: To apply a target tracking scaling policy with a predefined metric specification


# The following example applies a target tracking scaling policy with a predefined metric specification to an Amazon ECS
# service called web-app in the default cluster. The policy keeps the average CPU utilization of the service at 75
# percent, with scale-out and scale-in cooldown periods of 60 seconds.

resp = client.put_scaling_policy({
  policy_name: "cpu75-target-tracking-scaling-policy", 
  policy_type: "TargetTrackingScaling", 
  resource_id: "service/default/web-app", 
  scalable_dimension: "ecs:service:DesiredCount", 
  service_namespace: "ecs", 
  target_tracking_scaling_policy_configuration: {
    predefined_metric_specification: {
      predefined_metric_type: "ECSServiceAverageCPUUtilization", 
    }, 
    scale_in_cooldown: 60, 
    scale_out_cooldown: 60, 
    target_value: 75, 
  }, 
})

resp.to_h outputs the following:
{
  alarms: [
    {
      alarm_arn: "arn:aws:cloudwatch:us-west-2:012345678910:alarm:TargetTracking-service/default/web-app-AlarmHigh-d4f0770c-b46e-434a-a60f-3b36d653feca", 
      alarm_name: "TargetTracking-service/default/web-app-AlarmHigh-d4f0770c-b46e-434a-a60f-3b36d653feca", 
    }, 
    {
      alarm_arn: "arn:aws:cloudwatch:us-west-2:012345678910:alarm:TargetTracking-service/default/web-app-AlarmLow-1b437334-d19b-4a63-a812-6c67aaf2910d", 
      alarm_name: "TargetTracking-service/default/web-app-AlarmLow-1b437334-d19b-4a63-a812-6c67aaf2910d", 
    }, 
  ], 
  policy_arn: "arn:aws:autoscaling:us-west-2:012345678910:scalingPolicy:6d8972f3-efc8-437c-92d1-6270f29a66e7:resource/ecs/service/default/web-app:policyName/cpu75-target-tracking-scaling-policy", 
}

Request syntax with placeholder values


resp = client.put_scaling_policy({
  policy_name: "PolicyName", # required
  service_namespace: "ecs", # required, accepts ecs, elasticmapreduce, ec2, appstream, dynamodb, rds, sagemaker, custom-resource, comprehend, lambda, cassandra, kafka, elasticache, neptune, workspaces
  resource_id: "ResourceIdMaxLen1600", # required
  scalable_dimension: "ecs:service:DesiredCount", # required, accepts ecs:service:DesiredCount, ec2:spot-fleet-request:TargetCapacity, elasticmapreduce:instancegroup:InstanceCount, appstream:fleet:DesiredCapacity, dynamodb:table:ReadCapacityUnits, dynamodb:table:WriteCapacityUnits, dynamodb:index:ReadCapacityUnits, dynamodb:index:WriteCapacityUnits, rds:cluster:ReadReplicaCount, sagemaker:variant:DesiredInstanceCount, custom-resource:ResourceType:Property, comprehend:document-classifier-endpoint:DesiredInferenceUnits, comprehend:entity-recognizer-endpoint:DesiredInferenceUnits, lambda:function:ProvisionedConcurrency, cassandra:table:ReadCapacityUnits, cassandra:table:WriteCapacityUnits, kafka:broker-storage:VolumeSize, elasticache:replication-group:NodeGroups, elasticache:replication-group:Replicas, neptune:cluster:ReadReplicaCount, sagemaker:variant:DesiredProvisionedConcurrency, sagemaker:inference-component:DesiredCopyCount, workspaces:workspacespool:DesiredUserSessions
  policy_type: "StepScaling", # accepts StepScaling, TargetTrackingScaling, PredictiveScaling
  step_scaling_policy_configuration: {
    adjustment_type: "ChangeInCapacity", # accepts ChangeInCapacity, PercentChangeInCapacity, ExactCapacity
    step_adjustments: [
      {
        metric_interval_lower_bound: 1.0,
        metric_interval_upper_bound: 1.0,
        scaling_adjustment: 1, # required
      },
    ],
    min_adjustment_magnitude: 1,
    cooldown: 1,
    metric_aggregation_type: "Average", # accepts Average, Minimum, Maximum
  },
  target_tracking_scaling_policy_configuration: {
    target_value: 1.0, # required
    predefined_metric_specification: {
      predefined_metric_type: "DynamoDBReadCapacityUtilization", # required, accepts DynamoDBReadCapacityUtilization, DynamoDBWriteCapacityUtilization, ALBRequestCountPerTarget, RDSReaderAverageCPUUtilization, RDSReaderAverageDatabaseConnections, EC2SpotFleetRequestAverageCPUUtilization, EC2SpotFleetRequestAverageNetworkIn, EC2SpotFleetRequestAverageNetworkOut, SageMakerVariantInvocationsPerInstance, ECSServiceAverageCPUUtilization, ECSServiceAverageMemoryUtilization, AppStreamAverageCapacityUtilization, ComprehendInferenceUtilization, LambdaProvisionedConcurrencyUtilization, CassandraReadCapacityUtilization, CassandraWriteCapacityUtilization, KafkaBrokerStorageUtilization, ElastiCachePrimaryEngineCPUUtilization, ElastiCacheReplicaEngineCPUUtilization, ElastiCacheDatabaseMemoryUsageCountedForEvictPercentage, NeptuneReaderAverageCPUUtilization, SageMakerVariantProvisionedConcurrencyUtilization, ElastiCacheDatabaseCapacityUsageCountedForEvictPercentage, SageMakerInferenceComponentInvocationsPerCopy, WorkSpacesAverageUserSessionsCapacityUtilization, SageMakerInferenceComponentConcurrentRequestsPerCopyHighResolution, SageMakerVariantConcurrentRequestsPerModelHighResolution
      resource_label: "ResourceLabel",
    },
    customized_metric_specification: {
      metric_name: "MetricName",
      namespace: "MetricNamespace",
      dimensions: [
        {
          name: "MetricDimensionName", # required
          value: "MetricDimensionValue", # required
        },
      ],
      statistic: "Average", # accepts Average, Minimum, Maximum, SampleCount, Sum
      unit: "MetricUnit",
      metrics: [
        {
          expression: "Expression",
          id: "Id", # required
          label: "XmlString",
          metric_stat: {
            metric: { # required
              dimensions: [
                {
                  name: "TargetTrackingMetricDimensionName", # required
                  value: "TargetTrackingMetricDimensionValue", # required
                },
              ],
              metric_name: "TargetTrackingMetricName",
              namespace: "TargetTrackingMetricNamespace",
            },
            stat: "XmlString", # required
            unit: "TargetTrackingMetricUnit",
          },
          return_data: false,
        },
      ],
    },
    scale_out_cooldown: 1,
    scale_in_cooldown: 1,
    disable_scale_in: false,
  },
  predictive_scaling_policy_configuration: {
    metric_specifications: [ # required
      {
        target_value: 1.0, # required
        predefined_metric_pair_specification: {
          predefined_metric_type: "PredictiveScalingMetricType", # required
          resource_label: "ResourceLabel",
        },
        predefined_scaling_metric_specification: {
          predefined_metric_type: "PredictiveScalingMetricType", # required
          resource_label: "ResourceLabel",
        },
        predefined_load_metric_specification: {
          predefined_metric_type: "PredictiveScalingMetricType", # required
          resource_label: "ResourceLabel",
        },
        customized_scaling_metric_specification: {
          metric_data_queries: [ # required
            {
              id: "Id", # required
              expression: "Expression",
              metric_stat: {
                metric: { # required
                  dimensions: [
                    {
                      name: "PredictiveScalingMetricDimensionName", # required
                      value: "PredictiveScalingMetricDimensionValue", # required
                    },
                  ],
                  metric_name: "PredictiveScalingMetricName",
                  namespace: "PredictiveScalingMetricNamespace",
                },
                stat: "XmlString", # required
                unit: "PredictiveScalingMetricUnit",
              },
              label: "XmlString",
              return_data: false,
            },
          ],
        },
        customized_load_metric_specification: {
          metric_data_queries: [ # required
            {
              id: "Id", # required
              expression: "Expression",
              metric_stat: {
                metric: { # required
                  dimensions: [
                    {
                      name: "PredictiveScalingMetricDimensionName", # required
                      value: "PredictiveScalingMetricDimensionValue", # required
                    },
                  ],
                  metric_name: "PredictiveScalingMetricName",
                  namespace: "PredictiveScalingMetricNamespace",
                },
                stat: "XmlString", # required
                unit: "PredictiveScalingMetricUnit",
              },
              label: "XmlString",
              return_data: false,
            },
          ],
        },
        customized_capacity_metric_specification: {
          metric_data_queries: [ # required
            {
              id: "Id", # required
              expression: "Expression",
              metric_stat: {
                metric: { # required
                  dimensions: [
                    {
                      name: "PredictiveScalingMetricDimensionName", # required
                      value: "PredictiveScalingMetricDimensionValue", # required
                    },
                  ],
                  metric_name: "PredictiveScalingMetricName",
                  namespace: "PredictiveScalingMetricNamespace",
                },
                stat: "XmlString", # required
                unit: "PredictiveScalingMetricUnit",
              },
              label: "XmlString",
              return_data: false,
            },
          ],
        },
      },
    ],
    mode: "ForecastOnly", # accepts ForecastOnly, ForecastAndScale
    scheduling_buffer_time: 1,
    max_capacity_breach_behavior: "HonorMaxCapacity", # accepts HonorMaxCapacity, IncreaseMaxCapacity
    max_capacity_buffer: 1,
  },
})

Response structure


resp.policy_arn #=> String
resp.alarms #=> Array
resp.alarms[0].alarm_name #=> String
resp.alarms[0].alarm_arn #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :policy_name (required, String) —

    The name of the scaling policy.

    You cannot change the name of a scaling policy, but you can delete the original scaling policy and create a new scaling policy with the same settings and a different name.

  • :service_namespace (required, String) —

    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.

  • :resource_id (required, String) —

    The identifier of the resource associated with the scaling policy. 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`.

    • 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`.

    [1]: github.com/aws/aws-auto-scaling-custom-resource

  • :scalable_dimension (required, String) —

    The scalable dimension. 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: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.

  • :policy_type (String) —

    The scaling policy type. This parameter is required if you are creating a scaling policy.

    The following policy types are supported:

    ‘TargetTrackingScaling`—Not supported for Amazon EMR.

    ‘StepScaling`—Not supported for DynamoDB, Amazon Comprehend, Lambda, Amazon Keyspaces, Amazon MSK, Amazon ElastiCache, or Neptune.

    For more information, see [Target tracking scaling policies] and

    Step scaling policies][2

    in the *Application Auto Scaling User

    Guide*.

    [1]: docs.aws.amazon.com/autoscaling/application/userguide/application-auto-scaling-target-tracking.html [2]: docs.aws.amazon.com/autoscaling/application/userguide/application-auto-scaling-step-scaling-policies.html

  • :step_scaling_policy_configuration (Types::StepScalingPolicyConfiguration) —

    A step scaling policy.

    This parameter is required if you are creating a policy and the policy type is ‘StepScaling`.

  • :target_tracking_scaling_policy_configuration (Types::TargetTrackingScalingPolicyConfiguration) —

    A target tracking scaling policy. Includes support for predefined or customized metrics.

    This parameter is required if you are creating a policy and the policy type is ‘TargetTrackingScaling`.

  • :predictive_scaling_policy_configuration (Types::PredictiveScalingPolicyConfiguration) —

    The configuration of the predictive scaling policy.

Returns:

See Also:



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# File 'lib/aws-sdk-applicationautoscaling/client.rb', line 2923

def put_scaling_policy(params = {}, options = {})
  req = build_request(:put_scaling_policy, params)
  req.send_request(options)
end

#put_scheduled_action(params = {}) ⇒ Struct

Creates or updates a scheduled action for an Application Auto Scaling scalable target.

Each scalable target is identified by a service namespace, resource ID, and scalable dimension. A scheduled action applies to the scalable target identified by those three attributes. You cannot create a scheduled action until you have registered the resource as a scalable target.

When you specify start and end times with a recurring schedule using a cron expression or rates, they form the boundaries for when the recurring action starts and stops.

To update a scheduled action, specify the parameters that you want to change. If you don’t specify start and end times, the old values are deleted.

For more information, see [Scheduled scaling] in the *Application Auto Scaling User Guide*.

<note markdown=“1”> If a scalable target is deregistered, the scalable target is no longer available to run scheduled actions. Any scheduled actions that were specified for the scalable target are deleted.

</note>

[1]: docs.aws.amazon.com/autoscaling/application/userguide/application-auto-scaling-scheduled-scaling.html

Examples:

Example: To create a recurring scheduled action


# This example adds a scheduled action to a DynamoDB table called TestTable to scale out on a recurring schedule. On the
# specified schedule (every day at 12:15pm UTC), if the current capacity is below the value specified for MinCapacity,
# Application Auto Scaling scales out to the value specified by MinCapacity.

resp = client.put_scheduled_action({
  resource_id: "table/TestTable", 
  scalable_dimension: "dynamodb:table:WriteCapacityUnits", 
  scalable_target_action: {
    min_capacity: 6, 
  }, 
  schedule: "cron(15 12 * * ? *)", 
  scheduled_action_name: "my-recurring-action", 
  service_namespace: "dynamodb", 
})

resp.to_h outputs the following:
{
}

Request syntax with placeholder values


resp = client.put_scheduled_action({
  service_namespace: "ecs", # required, accepts ecs, elasticmapreduce, ec2, appstream, dynamodb, rds, sagemaker, custom-resource, comprehend, lambda, cassandra, kafka, elasticache, neptune, workspaces
  schedule: "ResourceIdMaxLen1600",
  timezone: "ResourceIdMaxLen1600",
  scheduled_action_name: "ScheduledActionName", # required
  resource_id: "ResourceIdMaxLen1600", # required
  scalable_dimension: "ecs:service:DesiredCount", # required, accepts ecs:service:DesiredCount, ec2:spot-fleet-request:TargetCapacity, elasticmapreduce:instancegroup:InstanceCount, appstream:fleet:DesiredCapacity, dynamodb:table:ReadCapacityUnits, dynamodb:table:WriteCapacityUnits, dynamodb:index:ReadCapacityUnits, dynamodb:index:WriteCapacityUnits, rds:cluster:ReadReplicaCount, sagemaker:variant:DesiredInstanceCount, custom-resource:ResourceType:Property, comprehend:document-classifier-endpoint:DesiredInferenceUnits, comprehend:entity-recognizer-endpoint:DesiredInferenceUnits, lambda:function:ProvisionedConcurrency, cassandra:table:ReadCapacityUnits, cassandra:table:WriteCapacityUnits, kafka:broker-storage:VolumeSize, elasticache:replication-group:NodeGroups, elasticache:replication-group:Replicas, neptune:cluster:ReadReplicaCount, sagemaker:variant:DesiredProvisionedConcurrency, sagemaker:inference-component:DesiredCopyCount, workspaces:workspacespool:DesiredUserSessions
  start_time: Time.now,
  end_time: Time.now,
  scalable_target_action: {
    min_capacity: 1,
    max_capacity: 1,
  },
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :service_namespace (required, String) —

    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.

  • :schedule (String) —

    The schedule for this action. The following formats are supported:

    • At expressions - “‘at(yyyy-mm-ddThh:mm:ss)`”

    • Rate expressions - “‘rate(value unit)`”

    • Cron expressions - “‘cron(fields)`”

    At expressions are useful for one-time schedules. Cron expressions are useful for scheduled actions that run periodically at a specified date and time, and rate expressions are useful for scheduled actions that run at a regular interval.

    At and cron expressions use Universal Coordinated Time (UTC) by default.

    The cron format consists of six fields separated by white spaces: [Minutes] [Hours] [Day_of_Month] [Month] [Day_of_Week] [Year].

    For rate expressions, value is a positive integer and unit is ‘minute` | `minutes` | `hour` | `hours` | `day` | `days`.

    For more information, see [Schedule recurring scaling actions using cron expressions] in the *Application Auto Scaling User Guide*.

    [1]: docs.aws.amazon.com/autoscaling/application/userguide/scheduled-scaling-using-cron-expressions.html

  • :timezone (String) —

    Specifies the time zone used when setting a scheduled action by using an at or cron expression. If a time zone is not provided, UTC is used by default.

    Valid values are the canonical names of the IANA time zones supported by Joda-Time (such as ‘Etc/GMT+9` or `Pacific/Tahiti`). For more information, see [www.joda.org/joda-time/timezones.html][1].

    [1]: www.joda.org/joda-time/timezones.html

  • :scheduled_action_name (required, String) —

    The name of the scheduled action. This name must be unique among all other scheduled actions on the specified scalable target.

  • :resource_id (required, String) —

    The identifier of the resource associated with the scheduled action. 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`.

    • 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`.

    [1]: github.com/aws/aws-auto-scaling-custom-resource

  • :scalable_dimension (required, String) —

    The scalable dimension. 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: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.

  • :start_time (Time, DateTime, Date, Integer, String) —

    The date and time for this scheduled action to start, in UTC.

  • :end_time (Time, DateTime, Date, Integer, String) —

    The date and time for the recurring schedule to end, in UTC.

  • :scalable_target_action (Types::ScalableTargetAction) —

    The new minimum and maximum capacity. You can set both values or just one. At the scheduled time, if the current capacity is below the minimum capacity, Application Auto Scaling scales out to the minimum capacity. If the current capacity is above the maximum capacity, Application Auto Scaling scales in to the maximum capacity.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'lib/aws-sdk-applicationautoscaling/client.rb', line 3228

def put_scheduled_action(params = {}, options = {})
  req = build_request(:put_scheduled_action, params)
  req.send_request(options)
end

#register_scalable_target(params = {}) ⇒ Types::RegisterScalableTargetResponse

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.

<note markdown=“1”> 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.

</note>

[1]: docs.aws.amazon.com/autoscaling/application/APIReference/API_DescribeScalableTargets.html [2]: docs.aws.amazon.com/autoscaling/application/APIReference/API_DeregisterScalableTarget.html [3]: en.wikipedia.org/wiki/Eventual_consistency

Examples:

Example: To register an ECS service as a scalable target


# This example registers a scalable target from an Amazon ECS service called web-app that is running on the default
# cluster, with a minimum desired count of 1 task and a maximum desired count of 10 tasks.

resp = client.register_scalable_target({
  max_capacity: 10, 
  min_capacity: 1, 
  resource_id: "service/default/web-app", 
  scalable_dimension: "ecs:service:DesiredCount", 
  service_namespace: "ecs", 
})

resp.to_h outputs the following:
{
  scalable_target_arn: "arn:aws:application-autoscaling:us-east-1:123456789012:scalable-target/1234abcd56ab78cd901ef1234567890ab123", 
}

Request syntax with placeholder values


resp = client.register_scalable_target({
  service_namespace: "ecs", # required, accepts ecs, elasticmapreduce, ec2, appstream, dynamodb, rds, sagemaker, custom-resource, comprehend, lambda, cassandra, kafka, elasticache, neptune, workspaces
  resource_id: "ResourceIdMaxLen1600", # required
  scalable_dimension: "ecs:service:DesiredCount", # required, accepts ecs:service:DesiredCount, ec2:spot-fleet-request:TargetCapacity, elasticmapreduce:instancegroup:InstanceCount, appstream:fleet:DesiredCapacity, dynamodb:table:ReadCapacityUnits, dynamodb:table:WriteCapacityUnits, dynamodb:index:ReadCapacityUnits, dynamodb:index:WriteCapacityUnits, rds:cluster:ReadReplicaCount, sagemaker:variant:DesiredInstanceCount, custom-resource:ResourceType:Property, comprehend:document-classifier-endpoint:DesiredInferenceUnits, comprehend:entity-recognizer-endpoint:DesiredInferenceUnits, lambda:function:ProvisionedConcurrency, cassandra:table:ReadCapacityUnits, cassandra:table:WriteCapacityUnits, kafka:broker-storage:VolumeSize, elasticache:replication-group:NodeGroups, elasticache:replication-group:Replicas, neptune:cluster:ReadReplicaCount, sagemaker:variant:DesiredProvisionedConcurrency, sagemaker:inference-component:DesiredCopyCount, workspaces:workspacespool:DesiredUserSessions
  min_capacity: 1,
  max_capacity: 1,
  role_arn: "ResourceIdMaxLen1600",
  suspended_state: {
    dynamic_scaling_in_suspended: false,
    dynamic_scaling_out_suspended: false,
    scheduled_scaling_suspended: false,
  },
  tags: {
    "TagKey" => "TagValue",
  },
})

Response structure


resp.scalable_target_arn #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :service_namespace (required, String) —

    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.

  • :resource_id (required, 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`.

    • 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`.

    [1]: github.com/aws/aws-auto-scaling-custom-resource

  • :scalable_dimension (required, String) —

    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: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.

  • :min_capacity (Integer) —

    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.

  • :max_capacity (Integer) —

    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*.

    [1]: docs.aws.amazon.com/general/latest/gr/aws-service-information.html

  • :role_arn (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].

    [1]: docs.aws.amazon.com/autoscaling/application/userguide/security_iam_service-with-iam.html

  • :suspended_state (Types::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*.

    [1]: docs.aws.amazon.com/autoscaling/application/userguide/application-auto-scaling-suspend-resume-scaling.html

  • :tags (Hash<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*.

    [1]: docs.aws.amazon.com/autoscaling/application/userguide/resource-tagging-support.html

Returns:

See Also:



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# File 'lib/aws-sdk-applicationautoscaling/client.rb', line 3619

def register_scalable_target(params = {}, options = {})
  req = build_request(:register_scalable_target, params)
  req.send_request(options)
end

#tag_resource(params = {}) ⇒ Struct

Adds or edits tags on an Application Auto Scaling scalable target.

Each tag consists of a tag key and a tag value, which are both case-sensitive strings. To add a tag, specify a new tag key and a tag value. To edit a tag, specify an existing tag key and a new tag value.

You can use this operation to tag an Application Auto Scaling scalable target, but you cannot tag a scaling policy or scheduled action.

You can also add tags to an Application Auto Scaling scalable target while creating it (‘RegisterScalableTarget`).

For general information about tags, including the format and syntax, see [Tagging your Amazon Web Services resources] in the *Amazon Web Services General Reference*.

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*.

[1]: docs.aws.amazon.com/general/latest/gr/aws_tagging.html [2]: docs.aws.amazon.com/autoscaling/application/userguide/resource-tagging-support.html

Examples:

Example: To add a tag to a scalable target


# This example adds a tag with the key name "environment" and the value "production" to the scalable target specified by
# its ARN.

resp = client.tag_resource({
  resource_arn: "arn:aws:application-autoscaling:us-west-2:123456789012:scalable-target/1234abcd56ab78cd901ef1234567890ab123", 
  tags: {
    "environment" => "production", 
  }, 
})

resp.to_h outputs the following:
{
}

Request syntax with placeholder values


resp = client.tag_resource({
  resource_arn: "AmazonResourceName", # required
  tags: { # required
    "TagKey" => "TagValue",
  },
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :resource_arn (required, String) —

    Identifies the Application Auto Scaling scalable target that you want to apply tags to.

    For example: ‘arn:aws:application-autoscaling:us-east-1:123456789012:scalable-target/1234abcd56ab78cd901ef1234567890ab123`

    To get the ARN for a scalable target, use DescribeScalableTargets.

  • :tags (required, Hash<String,String>) —

    The tags assigned to the resource. A tag is a label that you assign to an Amazon Web Services resource.

    Each tag consists of a tag key and a tag value.

    You cannot have more than one tag on an Application Auto Scaling scalable target with the same tag key. If you specify an existing tag key with a different tag value, Application Auto Scaling replaces the current tag value with the specified one.

    For information about the rules that apply to tag keys and tag values, see [User-defined tag restrictions] in the *Amazon Web Services Billing User Guide*.

    [1]: docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/allocation-tag-restrictions.html

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'lib/aws-sdk-applicationautoscaling/client.rb', line 3709

def tag_resource(params = {}, options = {})
  req = build_request(:tag_resource, params)
  req.send_request(options)
end

#untag_resource(params = {}) ⇒ Struct

Deletes tags from an Application Auto Scaling scalable target. To delete a tag, specify the tag key and the Application Auto Scaling scalable target.

Examples:

Example: To remove a tag from a scalable target


# This example removes the tag pair with the key name "environment" from the scalable target specified by its ARN.

resp = client.untag_resource({
  resource_arn: "arn:aws:application-autoscaling:us-west-2:123456789012:scalable-target/1234abcd56ab78cd901ef1234567890ab123", 
  tag_keys: [
    "environment", 
  ], 
})

resp.to_h outputs the following:
{
}

Request syntax with placeholder values


resp = client.untag_resource({
  resource_arn: "AmazonResourceName", # required
  tag_keys: ["TagKey"], # required
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :resource_arn (required, String) —

    Identifies the Application Auto Scaling scalable target from which to remove tags.

    For example: ‘arn:aws:application-autoscaling:us-east-1:123456789012:scalable-target/1234abcd56ab78cd901ef1234567890ab123`

    To get the ARN for a scalable target, use DescribeScalableTargets.

  • :tag_keys (required, Array<String>) —

    One or more tag keys. Specify only the tag keys, not the tag values.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'lib/aws-sdk-applicationautoscaling/client.rb', line 3759

def untag_resource(params = {}, options = {})
  req = build_request(:untag_resource, params)
  req.send_request(options)
end

#waiter_names ⇒ Object

This method is part of a private API. You should avoid using this method if possible, as it may be removed or be changed in the future.

Deprecated. 


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# File 'lib/aws-sdk-applicationautoscaling/client.rb', line 3788

def waiter_names
  []
end