Canary release

Releasing to a small percentage of users first, watching the metrics, then widening or rolling back before it reaches everyone.

roll out to 5% firsttest on a few userscanary deploymentcanery releaserelease to a small group before everyonegradual traffic rollouttry it on a slice of trafficsoft launch to some users

See it

Live demo coming soon

What it is

A canary release sends the new version to a small slice of real traffic (1%, then 5%, then 25%) while everyone else stays on the old one. You watch error rate, latency, and the business metric you actually care about. Numbers hold, you widen. Numbers move the wrong way, you route everyone back and the blast radius was one user in a hundred. The name comes from the canary in the coal mine, and it is grim on purpose: the point is that a few people hit the bug so the rest never do.

Reach for it on changes where staging cannot tell you the truth: a new recommendation model, a rewritten checkout, a database driver swap, anything whose failure mode only shows up under real traffic and real data. Routing happens at the load balancer or edge, or in code via a percentage feature flag, which is the cheap version most teams start with.

Gotcha: a canary without automated metric comparison is just a slower deploy that nobody is watching. Define the pass/fail thresholds and the bake time before you start, and wire automatic rollback to them. Also make routing sticky per user, because a customer bouncing between old and new mid-session gets weird bugs and inconsistent UI. Note the difference from an A/B test: a canary asks 'is this broken', an A/B test asks 'is this better', and they need very different sample sizes.

Ask AI for it

Set up a canary release for this service. Route a configurable percentage of traffic to the new version starting at 5%, keeping routing sticky per user by hashing the user or session id so nobody flips between versions mid-session. Tag metrics and logs with the version so error rate and p95 latency can be compared between canary and baseline. Add an automated gate: bake for 10 minutes at each step, promote to 25% then 50% then 100% if error rate and latency stay within threshold of baseline, and automatically route all traffic back to the old version if they do not.

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staged rolloutfeature flagautomated rollbackblue green deploymentrollback