Every deployment gate below is real. Move the sliders to change what the candidate build does, and the same statistical judge that runs in the pipeline decides — right here, in your browser — whether it reaches production.
A canary is only trustworthy if it catches real regressions and refuses to cry wolf. Try the presets: a clean build promotes, a 4% error rate fails on a critical metric alone, and a 3% latency drift is caught as significant but deliberately tolerated.
| Metric | Result | Canary | Baseline | p-value | Cliff's δ | Weight |
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The judgment above is not advisory. It decides whether traffic moves, and a rejection halts promotion before the next environment is touched.
With enough samples, a 0.3 ms latency increase is statistically significant and operationally meaningless. A gate that fails on significance alone gets disabled within a month. Every metric must clear both a p-value and an effect-size threshold.
The weighted score can be dragged up by healthy metrics. An error-rate regression fails the canary on its own, regardless of how good everything else looks.
A metric that reported nothing is excluded from the score and disclosed — never counted as a pass. Treating silence as health is how bad builds reach production.
Red/black keeps the previous version running and healthy while the canary is judged. If the canary fails, nothing needs to be redeployed under pressure — traffic simply never moved.