paws (version 0.1.12)

applicationautoscaling: Application Auto Scaling

Description

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

• Amazon ECS services

• Amazon EC2 Spot Fleet requests

• Amazon EMR clusters

• Amazon AppStream 2.0 fleets

• Amazon DynamoDB tables and global secondary indexes throughput capacity

• Amazon Aurora Replicas

• Amazon SageMaker endpoint variants

• Custom resources provided by your own applications or services

• Amazon Comprehend document classification and entity recognizer endpoints

• AWS Lambda function provisioned concurrency

• Amazon Keyspaces (for Apache Cassandra) tables

• Amazon Managed Streaming for Apache Kafka cluster storage

API Summary

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

• Register and manage scalable targets - Register AWS 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.

To learn more about Application Auto Scaling, including information about granting IAM users required permissions for Application Auto Scaling actions, see the Application Auto Scaling User Guide.

Usage

applicationautoscaling(config = list())

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.

Arguments

config

Optional configuration of credentials, endpoint, and/or region.

Service syntax

svc <- applicationautoscaling(
  config = list(
    credentials = list(
      creds = list(
        access_key_id = "string",
        secret_access_key = "string",
        session_token = "string"
      ),
      profile = "string"
    ),
    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
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

Examples

if (FALSE) {
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"
)
}