ML Workflow Orchestration with AWS Step Functions
Overview AWS Step Functions lets you orchestrate multi-step workflows as state machines — each state can invoke an AWS service, branch on conditions, retry on failure, or run steps in parallel. This project uses Step Functions to wire together SageMaker Processing, Training, and Batch Transform jobs into a production-grade ML workflow that can be triggered on a schedule or by an event. The key difference from SageMaker Pipelines: Step Functions is AWS-native orchestration for any service combination (SageMaker + Lambda + Glue + SNS), whereas SageMaker Pipelines is ML-specific. For workflows that touch multiple AWS services, Step Functions is the right tool. ...