4Machine Learning Implementation and Operations

• 4.1Deploying Models

  Serve inference—understand real-time endpoints, batch transform, serverless/async inference, auto scaling, and multi-model endpoints. Choose the serving mode by use case.

• 4.2Monitoring and Retraining

  Protect in production—understand Model Monitor, data drift, CloudWatch (latency/errors/invocations), and drift-triggered retraining. Models degrade over time.

• 4.3MLOps and Security

  Automation and safety—understand SageMaker Pipelines, Model Registry, safe rollout (A/B/canary), and security via IAM/KMS/VPC. Achieve reproducible, secure ML operations.