A team deploys a new fraud model using canary deployment with 15% o…

Question

A team deploys a new fraud model using canary deployment with 15% of traffic. The champion continues receiving 85%. After 2 weeks, the canary achieves statistically significantly better precision. What distinguishes canary deployment from A/B testing in this context?

Accepted Answer

Canary deployment gradually increases the canary traffic share with a promotion criterion, while A/B testing maintains a fixed split for the duration of the experiment — Here's the deal — b is correct because canary deployment is designed for progressive rollout: the canary starts at a small traffic fraction and is gradually promoted to 100% if it meets performance thresholds. A/B testing maintains a fixed split for statistical comparison over a defined experiment window, with no automatic gradual promotion.

Answer

Canary deployment uses predictions of both models to make real decisions for all users simultaneously

Answer

A/B testing requires randomized assignment; canary deployment routes by request order

Answer

Canary deployment only logs the new model's predictions without acting on them

A team deploys a new fraud model using canary deployment with 15% of traffic. The champion continues receiving 85%. After 2 weeks, the canary achieves statistically significantly better precision. What distinguishes canary deployment from A/B testing in this context?

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