Before launching a new model to all users, how would you use shadow mode, canaries, and guardrails to reduce risk?
formulate your answer, then —
tldr
Shadow deployment runs the model on real traffic without affecting users; canary deployment exposes a small user slice. Shadow catches serving and parity issues. Canary measures real user impact. Senior launch plans define guardrails, rollback criteria, segment monitoring, and delayed-label readouts before ramping.
follow-up
- What can shadow mode not tell you?
- How do delayed labels affect canary evaluation?
- What guardrails would you add for a ranking model launch?