What is zero-downtime model deployment and how is it achieved?

Zero-downtime deployment ensures model updates happen without interrupting live traffic.

Zero-downtime deployment is achieved using strategies like blue-green deployment, canary releases, and rolling updates. In ML systems, this also requires ensuring model compatibility, feature parity, and backward-compatible APIs. Traffic is gradually shifted from old to new model versions while continuously monitoring performance metrics. If anomalies are detected, automatic rollback mechanisms restore the previous stable version.