AWS Solutions Architects demonstrate how to build an end-to-end MLOps workflow combining DVC for data versioning, Amazon SageMaker AI for scalable training, and SageMaker AI MLflow Apps for experiment tracking and lineage. The post presents two deployable patterns: dataset-level lineage (foundational) and record-level lineage (healthcare compliance with individual record traceability), enabling full reproducibility and audit capabilities for regulated industries.