AWS CLI Command Reference

[ aws . application-autoscaling ]

register-scalable-target

Description

Registers or updates a scalable target, 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 choose to 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

If you call the RegisterScalableTarget API to update an existing scalable target, Application Auto Scaling retrieves the current capacity of the resource. If it is 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.

See also: AWS API Documentation

Synopsis

  register-scalable-target
--service-namespace <value>
--resource-id <value>
--scalable-dimension <value>
[--min-capacity <value>]
[--max-capacity <value>]
[--role-arn <value>]
[--suspended-state <value>]
[--cli-input-json | --cli-input-yaml]
[--generate-cli-skeleton <value>]
[--debug]
[--endpoint-url <value>]
[--no-verify-ssl]
[--no-paginate]
[--output <value>]
[--query <value>]
[--profile <value>]
[--region <value>]
[--version <value>]
[--color <value>]
[--no-sign-request]
[--ca-bundle <value>]
[--cli-read-timeout <value>]
[--cli-connect-timeout <value>]
[--cli-binary-format <value>]
[--no-cli-pager]
[--cli-auto-prompt]
[--no-cli-auto-prompt]

Options

--service-namespace (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.

Possible values:

  • ecs

  • elasticmapreduce

  • ec2

  • appstream

  • dynamodb

  • rds

  • sagemaker

  • custom-resource

  • comprehend

  • lambda

  • cassandra

  • kafka

  • elasticache

  • neptune

--resource-id (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/default/sample-webapp .

  • 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 .

--scalable-dimension (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 desired 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 desired 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.

Possible values:

  • 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

--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

  • 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 may 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 .

--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 Application Auto Scaling IAM roles .

--suspended-state (structure)

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 Suspending and resuming scaling in the Application Auto Scaling User Guide .

DynamicScalingInSuspended -> (boolean)

Whether scale in by a target tracking scaling policy or a step scaling policy is suspended. Set the value to true if you don’t want Application Auto Scaling to remove capacity when a scaling policy is triggered. The default is false .

DynamicScalingOutSuspended -> (boolean)

Whether scale out by a target tracking scaling policy or a step scaling policy is suspended. Set the value to true if you don’t want Application Auto Scaling to add capacity when a scaling policy is triggered. The default is false .

ScheduledScalingSuspended -> (boolean)

Whether scheduled scaling is suspended. Set the value to true if you don’t want Application Auto Scaling to add or remove capacity by initiating scheduled actions. The default is false .

Shorthand Syntax:

DynamicScalingInSuspended=boolean,DynamicScalingOutSuspended=boolean,ScheduledScalingSuspended=boolean

JSON Syntax:

{
  "DynamicScalingInSuspended": true|false,
  "DynamicScalingOutSuspended": true|false,
  "ScheduledScalingSuspended": true|false
}

--cli-input-json | --cli-input-yaml (string) Reads arguments from the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton. If other arguments are provided on the command line, those values will override the JSON-provided values. It is not possible to pass arbitrary binary values using a JSON-provided value as the string will be taken literally. This may not be specified along with --cli-input-yaml.

--generate-cli-skeleton (string) Prints a JSON skeleton to standard output without sending an API request. If provided with no value or the value input, prints a sample input JSON that can be used as an argument for --cli-input-json. Similarly, if provided yaml-input it will print a sample input YAML that can be used with --cli-input-yaml. If provided with the value output, it validates the command inputs and returns a sample output JSON for that command. The generated JSON skeleton is not stable between versions of the AWS CLI and there are no backwards compatibility guarantees in the JSON skeleton generated.

Global Options

--debug (boolean)

Turn on debug logging.

--endpoint-url (string)

Override command’s default URL with the given URL.

--no-verify-ssl (boolean)

By default, the AWS CLI uses SSL when communicating with AWS services. For each SSL connection, the AWS CLI will verify SSL certificates. This option overrides the default behavior of verifying SSL certificates.

--no-paginate (boolean)

Disable automatic pagination.

--output (string)

The formatting style for command output.

  • json

  • text

  • table

  • yaml

  • yaml-stream

--query (string)

A JMESPath query to use in filtering the response data.

--profile (string)

Use a specific profile from your credential file.

--region (string)

The region to use. Overrides config/env settings.

--version (string)

Display the version of this tool.

--color (string)

Turn on/off color output.

  • on

  • off

  • auto

--no-sign-request (boolean)

Do not sign requests. Credentials will not be loaded if this argument is provided.

--ca-bundle (string)

The CA certificate bundle to use when verifying SSL certificates. Overrides config/env settings.

--cli-read-timeout (int)

The maximum socket read time in seconds. If the value is set to 0, the socket read will be blocking and not timeout. The default value is 60 seconds.

--cli-connect-timeout (int)

The maximum socket connect time in seconds. If the value is set to 0, the socket connect will be blocking and not timeout. The default value is 60 seconds.

--cli-binary-format (string)

The formatting style to be used for binary blobs. The default format is base64. The base64 format expects binary blobs to be provided as a base64 encoded string. The raw-in-base64-out format preserves compatibility with AWS CLI V1 behavior and binary values must be passed literally. When providing contents from a file that map to a binary blob fileb:// will always be treated as binary and use the file contents directly regardless of the cli-binary-format setting. When using file:// the file contents will need to properly formatted for the configured cli-binary-format.

  • base64

  • raw-in-base64-out

--no-cli-pager (boolean)

Disable cli pager for output.

--cli-auto-prompt (boolean)

Automatically prompt for CLI input parameters.

--no-cli-auto-prompt (boolean)

Disable automatically prompt for CLI input parameters.

Examples

Note

To use the following examples, you must have the AWS CLI installed and configured. See the Getting started guide in the AWS CLI User Guide for more information.

Unless otherwise stated, all examples have unix-like quotation rules. These examples will need to be adapted to your terminal’s quoting rules. See Using quotation marks with strings in the AWS CLI User Guide .

Example 1: To register a new scalable target for Amazon ECS

The following register-scalable-target example registers a scalable target for an Amazon ECS service called web-app, running on the default cluster, with a minimum desired count of 1 task and a maximum desired count of 10 tasks.

aws application-autoscaling register-scalable-target \
    --service-namespace ecs \
    --scalable-dimension ecs:service:DesiredCount \
    --resource-id service/default/web-app \
    --min-capacity 1 \
    --max-capacity 10

Example 2: To register a new scalable target for a Spot Fleet

The following register-scalable-target example registers the target capacity of an Amazon EC2 Spot Fleet request using its request ID, with a minimum capacity of 2 instances and a maximum capacity of 10 instances.

aws application-autoscaling register-scalable-target \
    --service-namespace ec2 \
    --scalable-dimension ec2:spot-fleet-request:TargetCapacity \
    --resource-id spot-fleet-request/sfr-73fbd2ce-aa30-494c-8788-1cee4EXAMPLE \
    --min-capacity 2 \
    --max-capacity 10

Example 3: To register a new scalable target for AppStream 2.0

The following register-scalable-target example registers the desired capacity of an AppStream 2.0 fleet called sample-fleet, with a minimum capacity of 1 fleet instance and a maximum capacity of 5 fleet instances.

aws application-autoscaling register-scalable-target \
    --service-namespace appstream \
    --scalable-dimension appstream:fleet:DesiredCapacity \
    --resource-id fleet/sample-fleet \
    --min-capacity 1 \
    --max-capacity 5

Example 4: To register a new scalable target for a DynamoDB table

The following register-scalable-target example registers the provisioned write capacity of a DynamoDB table called my-table, with a minimum capacity of 5 write capacity units and a maximum capacity of 10 write capacity units.

aws application-autoscaling register-scalable-target \
    --service-namespace dynamodb \
    --scalable-dimension dynamodb:table:WriteCapacityUnits \
    --resource-id table/my-table \
    --min-capacity 5 \
    --max-capacity 10

Example 5: To register a new scalable target for a DynamoDB global secondary index

The following register-scalable-target example registers the provisioned write capacity of a DynamoDB global secondary index called my-table-index, with a minimum capacity of 5 write capacity units and a maximum capacity of 10 write capacity units.

aws application-autoscaling register-scalable-target \
    --service-namespace dynamodb \
    --scalable-dimension dynamodb:index:WriteCapacityUnits \
    --resource-id table/my-table/index/my-table-index \
    --min-capacity 5 \
    --max-capacity 10

Example 6: To register a new scalable target for Aurora DB

The following register-scalable-target example registers the count of Aurora Replicas in an Aurora DB cluster called my-db-cluster, with a minimum capacity of 1 Aurora Replica and a maximum capacity of 8 Aurora Replicas.

aws application-autoscaling register-scalable-target \
    --service-namespace rds \
    --scalable-dimension rds:cluster:ReadReplicaCount \
    --resource-id cluster:my-db-cluster \
    --min-capacity 1 \
    --max-capacity 8

Example 7: To register a new scalable target for Amazon Sagemaker

The following register-scalable-target example registers the desired EC2 instance count for an Amazon Sagemaker product variant called my-variant, running on the my-endpoint endpoint, with a minimum capacity of 1 instance and a maximum capacity of 8 instances.

aws application-autoscaling register-scalable-target \
    --service-namespace sagemaker \
    --scalable-dimension sagemaker:variant:DesiredInstanceCount \
    --resource-id endpoint/my-endpoint/variant/my-variant \
    --min-capacity 1 \
    --max-capacity 8

Example 8: To register a new scalable target for a custom resource

The following register-scalable-target example registers a custom resource as a scalable target, with a minimum desired count of 1 capacity unit and a maximum desired count of 10 capacity units. The custom-resource-id.txt file contains a string that identifies the Resource ID, which for a custom resource is the path to the custom resource through your Amazon API Gateway endpoint.

aws application-autoscaling register-scalable-target \
    --service-namespace custom-resource \
    --scalable-dimension custom-resource:ResourceType:Property \
    --resource-id file://~/custom-resource-id.txt \
    --min-capacity 1 \
    --max-capacity 10

Contents of custom-resource-id.txt:

https://example.execute-api.us-west-2.amazonaws.com/prod/scalableTargetDimensions/1-23456789

Example 9: To register a new scalable target for Amazon Comprehend

The following register-scalable-target example registers the desired number of inference units to be used by the model for an Amazon Comprehend document classifier endpoint using the endpoint’s ARN, with a minimum capacity of 1 inference unit and a maximum capacity of 3 inference units. Each inference unit represents a throughput of 100 characters per second.

aws application-autoscaling register-scalable-target \
    --service-namespace comprehend \
    --scalable-dimension comprehend:document-classifier-endpoint:DesiredInferenceUnits \
    --resource-id arn:aws:comprehend:us-west-2:123456789012:document-classifier-endpoint/EXAMPLE \
    --min-capacity 1 \
    --max-capacity 3

Example 10: To register a new scalable target for AWS Lambda

The following register-scalable-target example registers the provisioned concurrency for an alias called BLUE for the Lambda function called my-function, with a minimum capacity of 0 and a maximum capacity of 100.

aws application-autoscaling register-scalable-target \
    --service-namespace lambda \
    --scalable-dimension lambda:function:ProvisionedConcurrency \
    --resource-id function:my-function:BLUE \
    --min-capacity 0 \
    --max-capacity 100

For more information, see the Application Auto Scaling User Guide.

Output

None

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