step-functions

AWS Step Functions orchestrate AWS workflows by coordinating tasks across services like Lambda and SQS using state machines. You define the workflow in Amazon States Language to manage execution flow, handle errors automatically, and monitor progress visually.

AWS state machines handle errors using robust Retry and Catch patterns within your Amazon States Language definition. These patterns allow workflows to automatically retry failed tasks or catch specific errors to route execution to fallback steps, ensuring reliable business processes.

AWS Step Functions are needed for long-running tasks, parallel execution, and nested workflows like data pipelines. They provide a visual workflow language to coordinate multiple AWS services reliably, replacing custom orchestration code with manageable state machine definitions.

The best way to define and deploy state machines is by writing definitions in Amazon States Language and deploying them via AWS CLI or SDK. This approach enables practical deployment, execution monitoring, and debugging through execution history tooling.

Yes, Step Functions support common workflow patterns including branching, parallel execution, and maps for real-time processing. They orchestrate complex business processes across AWS services, maintaining observability and reliable state management throughout execution.

Coordinating multiple AWS services without state machines is complex and error-prone, lacking built-in retries and progress monitoring. Step Functions solve this by providing a visual workflow language to reliably orchestrate tasks, manage state, and handle failures automatically.