aws-sdk-applicationautoscaling

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 Serverless endpoint provisioned concurrency
• Amazon SageMaker inference components
• Spot Fleets (Amazon EC2)
• 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 RegisterScalableTarget 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.

Getting Started

Examples are available for many services and operations, check out the examples folder in GitHub.

The SDK provides one crate per AWS service. You must add Tokio as a dependency within your Rust project to execute asynchronous code. To add aws-sdk-applicationautoscaling to your project, add the following to your Cargo.toml file:

[dependencies]
aws-config = { version = "1.1.7", features = ["behavior-version-latest"] }
aws-sdk-applicationautoscaling = "1.22.0"
tokio = { version = "1", features = ["full"] }

Then in code, a client can be created with the following:

use aws_sdk_applicationautoscaling as applicationautoscaling;

#[::tokio::main]
async fn main() -> Result<(), applicationautoscaling::Error> {
    let config = aws_config::load_from_env().await;
    let client = aws_sdk_applicationautoscaling::Client::new(&config);

    // ... make some calls with the client

    Ok(())
}

See the client documentation for information on what calls can be made, and the inputs and outputs for each of those calls.

Using the SDK

Until the SDK is released, we will be adding information about using the SDK to the Developer Guide. Feel free to suggest additional sections for the guide by opening an issue and describing what you are trying to do.

Getting Help

• GitHub discussions - For ideas, RFCs & general questions
• GitHub issues - For bug reports & feature requests
• Generated Docs (latest version)
• Usage examples

License

This project is licensed under the Apache-2.0 License.