3Deployment and Orchestration of ML Workflows

• 3.1Choosing Inference Options

  Understand SageMaker inference options (real-time, serverless, asynchronous, batch transform) and choosing by traffic/latency. The starting point for "Deployment and Orchestration" in MLA-C01.

• 3.2MLOps and SageMaker Pipelines

  Understand MLOps: automating the ML lifecycle with SageMaker Pipelines, versioning/approval with the Model Registry, and CI/CD integration.

• 3.3Safe Model Deployment Strategies

  Understand low-risk model deployment: blue/green, canary/linear traffic shifting, and shadow/A-B testing (multi-variant endpoints).