canary

Patching is easy; surviving the rollout is the interview. Staged rings with health gates, what livepatching can and cannot buy you, and the rollback plan you write before starting.

The loop is easy; the statistics are not. This question finds engineers who can size a traffic slice against sample noise and name the false rollback that kills trust in automation.

Compare rollout capacity, traffic exposure and state compatibility, then work through a payments canary with too little evidence to promote.

The automation stopped because it could not decide, which is the correct behaviour and an incomplete design. Somebody has to decide, and the interesting question is what evidence that decision needs.

Comparing the canary against last week is how a Tuesday afternoon looks like a regression. Compare it against a baseline running the same traffic at the same moment, and decide with a threshold somebody can defend.

Code rollouts ask 'does it work'; model rollouts ask 'is it better', and the second question has no HTTP status code. Shadow traffic, offline eval gates and quality canaries replace the 500-rate dashboards you cannot use.

The infrastructure win is real and easy to measure. The quality regression is real, harder to measure, and will not show up in your latency dashboards at all.