applicationautoscaling: Application Auto Scaling

In paws.management: 'Amazon Web Services' Management & Governance Services

Application Auto Scaling

Description

With Application Auto Scaling, you can configure automatic scaling for the following resources:

• Amazon AppStream 2.0 fleets

• Amazon Aurora Replicas

• Amazon Comprehend document classification and entity recognizer endpoints

• Amazon DynamoDB tables and global secondary indexes throughput capacity

• Amazon ECS services

• Amazon ElastiCache for Redis clusters (replication groups)

• Amazon EMR clusters

• Amazon Keyspaces (for Apache Cassandra) tables

• Lambda function provisioned concurrency

• Amazon Managed Streaming for Apache Kafka broker storage

• Amazon Neptune clusters

• Amazon SageMaker endpoint variants

• Amazon SageMaker inference components

• Amazon SageMaker serverless endpoint provisioned concurrency

• Spot Fleets (Amazon EC2)

• Pool of WorkSpaces

• Custom resources provided by your own applications or services

To learn more about Application Auto Scaling, see the Application Auto Scaling User Guide.

API Summary

The Application Auto Scaling service API includes three key sets of actions:

• Register and manage scalable targets - Register Amazon Web Services or custom resources as scalable targets (a resource that Application Auto Scaling can scale), set minimum and maximum capacity limits, and retrieve information on existing scalable targets.

• Configure and manage automatic scaling - Define scaling policies to dynamically scale your resources in response to CloudWatch alarms, schedule one-time or recurring scaling actions, and retrieve your recent scaling activity history.

• Suspend and resume scaling - Temporarily suspend and later resume automatic scaling by calling the register_scalable_target API action for any Application Auto Scaling scalable target. You can suspend and resume (individually or in combination) scale-out activities that are triggered by a scaling policy, scale-in activities that are triggered by a scaling policy, and scheduled scaling.

Usage

applicationautoscaling(
  config = list(),
  credentials = list(),
  endpoint = NULL,
  region = NULL
)

Arguments

config	Optional configuration of credentials, endpoint, and/or region. credentials: creds: access_key_id: AWS access key ID secret_access_key: AWS secret access key session_token: AWS temporary session token profile: The name of a profile to use. If not given, then the default profile is used. anonymous: Set anonymous credentials. endpoint: The complete URL to use for the constructed client. region: The AWS Region used in instantiating the client. close_connection: Immediately close all HTTP connections. timeout: The time in seconds till a timeout exception is thrown when attempting to make a connection. The default is 60 seconds. s3_force_path_style: Set this to true to force the request to use path-style addressing, i.e. ⁠http://s3.amazonaws.com/BUCKET/KEY⁠. sts_regional_endpoint: Set sts regional endpoint resolver to regional or legacy https://docs.aws.amazon.com/sdkref/latest/guide/feature-sts-regionalized-endpoints.html
credentials	Optional credentials shorthand for the config parameter creds: access_key_id: AWS access key ID secret_access_key: AWS secret access key session_token: AWS temporary session token profile: The name of a profile to use. If not given, then the default profile is used. anonymous: Set anonymous credentials.
endpoint	Optional shorthand for complete URL to use for the constructed client.
region	Optional shorthand for AWS Region used in instantiating the client.

Value

A client for the service. You can call the service's operations using syntax like svc$operation(...), where svc is the name you've assigned to the client. The available operations are listed in the Operations section.

Service syntax

svc <- applicationautoscaling(
  config = list(
    credentials = list(
      creds = list(
        access_key_id = "string",
        secret_access_key = "string",
        session_token = "string"
      ),
      profile = "string",
      anonymous = "logical"
    ),
    endpoint = "string",
    region = "string",
    close_connection = "logical",
    timeout = "numeric",
    s3_force_path_style = "logical",
    sts_regional_endpoint = "string"
  ),
  credentials = list(
    creds = list(
      access_key_id = "string",
      secret_access_key = "string",
      session_token = "string"
    ),
    profile = "string",
    anonymous = "logical"
  ),
  endpoint = "string",
  region = "string"
)

Operations

delete_scaling_policy	Deletes the specified scaling policy for an Application Auto Scaling scalable target
delete_scheduled_action	Deletes the specified scheduled action for an Application Auto Scaling scalable target
deregister_scalable_target	Deregisters an Application Auto Scaling scalable target when you have finished using it
describe_scalable_targets	Gets information about the scalable targets in the specified namespace
describe_scaling_activities	Provides descriptive information about the scaling activities in the specified namespace from the previous six weeks
describe_scaling_policies	Describes the Application Auto Scaling scaling policies for the specified service namespace
describe_scheduled_actions	Describes the Application Auto Scaling scheduled actions for the specified service namespace
get_predictive_scaling_forecast	Retrieves the forecast data for a predictive scaling policy
list_tags_for_resource	Returns all the tags on the specified Application Auto Scaling scalable target
put_scaling_policy	Creates or updates a scaling policy for an Application Auto Scaling scalable target
put_scheduled_action	Creates or updates a scheduled action for an Application Auto Scaling scalable target
register_scalable_target	Registers or updates a scalable target, which is the resource that you want to scale
tag_resource	Adds or edits tags on an Application Auto Scaling scalable target
untag_resource	Deletes tags from an Application Auto Scaling scalable target

Examples

## Not run: 
svc <- applicationautoscaling()
# This example deletes a scaling policy for the Amazon ECS service called
# web-app, which is running in the default cluster.
svc$delete_scaling_policy(
  PolicyName = "web-app-cpu-lt-25",
  ResourceId = "service/default/web-app",
  ScalableDimension = "ecs:service:DesiredCount",
  ServiceNamespace = "ecs"
)

## End(Not run)

paws.management documentation built on April 3, 2025, 10:39 p.m.