Canary Deployment
Gradually rolling out a new model version to a small subset of traffic before full deployment.
Overview
Canary deployment is a release strategy where a new ML model version is deployed to a small percentage of production traffic (the 'canary') while the existing model continues to serve the majority. If the new model performs well, traffic is gradually shifted; if issues arise, traffic is rolled back to the existing model.
Key Details
This approach reduces the blast radius of problematic deployments. Canary deployments monitor latency, error rates, prediction distributions, and business metrics. Automated canary analysis tools can automatically promote or roll back based on predefined criteria. This pattern is standard in production ML systems at major tech companies.