What is a canary release for ML models?
easyAnswer
- Canary release routes a small percentage of traffic (e.g., 1-5%) to the new model, monitors metrics and errors closely, and gradually increases traffic if healthy.
- If a regression is detected, you roll back quickly.
- Combines with automated guardrails on latency, error rate, and business metrics.
- Standard modern deployment strategy for both ML models and general services.
Check yourself — multiple choice
- Canary sends all traffic to the new model immediately
- Canary sends a small share of traffic and ramps up if healthy
- Canary is only for offline evaluation
- Canary requires no rollback plan
Start small, watch metrics, ramp up — that's the canary pattern.
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