AWS Step Functions Documentation

Using AWS Step Functions, you define your workflows as state machines, which transforms code into easier to understand statements and diagrams. Read more about how Step Functions works.

AWS Step Functions provides ready-made steps for your workflow called states that implement basic service primitives for you, which means you can remove that logic from your application. States can pass data to other states and microservices, handle exceptions, add timeouts, make decisions, execute multiple paths in parallel, and more. Learn more about states.

Using AWS Step Functions Service Integrations, you can configure your Step Functions workflow to call other AWS services. This includes compute services (AWS Lambda, Amazon ECS, Amazon EKS, and AWS Fargate), database services (Amazon DynamoDB), messaging services (Amazon SNS and Amazon SQS), data processing and analytics services (Amazon Athena, AWS Batch, AWS Glue, Amazon EMR, and AWS Glue DataBrew), machine learning services (Amazon SageMaker), and APIs created by Amazon API Gateway. Learn more about Service Integrations.

AWS Step Functions allow you to coordinate applications that make an HTTPS connection from various host locations—for example, on Amazon EC2 instances, mobile devices, or on-premises servers. Using Step Functions, you can create distributed applications that leverage AWS services as well as your own microservices. Learn more about activity tasks.

With AWS Step Functions, you can coordinate your existing Lambda functions and microservices into applications, and lets you rewire them into new compositions. The tasks in your workflow can run on instances, containers, functions, and mobile devices. Learn how to reuse existing application components.

AWS Step Functions allows you to keep the logic of your application separated from the implementation of your application. You can add, move, swap, and reorder steps without making changes to your business logic. Through this separation of concerns, your workflows gain modularity, simplified maintenance, scalability, and code reuse.

You can use AWS Step Functions to handle errors and exceptions with try/catch and retry. You can retry failed or timed-out tasks, respond differently to different types of errors, and recover by falling back to designated cleanup and recovery code. Learn more about Step Functions error handling and how you can handle error conditions using a state machine.

AWS Step Functions delivers real-time diagnostics and dashboards, integrates with Amazon CloudWatch and AWS CloudTrail, and logs every execution, including overall state, failed steps, inputs, and outputs. If things go wrong, you can identify where and why, and troubleshoot and remediate failures. Learn more about Step Functions monitoring and logging.

You can launch an application by pressing a button, then watch the steps execute visually, so you can verify that everything is operating in order – and as expected. The console highlights errors, so you can pinpoint their root-cause, and troubleshoot issues.

AWS Step Functions has fault tolerance and maintains service capacity across multiple Availability Zones in each region.

AWS Step Functions scales the operations and underlying compute to run the steps of your application for you in response to changing workloads. Step Functions scales to help the performance of your application workflow remain consistent as the frequency of requests increases.

Step Functions can iterate over objects such as images, logs, or CSV files stored in Amazon S3, then launch and coordinate thousands of parallel workflows to process the data. You can scale thousands of concurrent workflow executions, helping you analyze large volumes of logs, iterate over terabytes of data or process documents, images, and video files. Learn more about the Step Functions Map state.

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