Key Takeaway
ML pipeline design docs should explicitly document data dependencies and retraining triggers, because these are the most common sources of production pipeline failures.
When to Use This Template
Use this design doc when proposing a new ML training and serving pipeline, planning a major refactoring of an existing pipeline, or integrating a new model into an existing ML platform. This template covers the full lifecycle from data ingestion through model serving, with particular emphasis on reproducibility, experiment tracking, and operational readiness.
Template Sections
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