Your question is Model Versioning and Updates. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
How do you manage model versioning and updates in production?
Explain a practical pipeline for registering immutable model artifacts, validating compatibility with input data, promoting models across environments, and deploying updates safely. Address orchestration, reproducibility, rollback, batch and streaming consumers, data quality, model drift, and monitoring using appropriate Datadog integrations. Describe how you would handle failed deployments, retraining, backfills, and concurrent model versions without interrupting production inference.