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Calcrivo

Canary Deployment Calculator

Calculate canary traffic allocation per pod and build a full rollout timeline given increment steps and evaluation windows.

Inputs

pods

Total replica count of the service being rolled out.

%

Initial percentage of traffic/pods routed to the canary version.

%

How much the canary percentage increases at each evaluation step.

minutes

How long metrics are observed at each canary stage before promoting further.

Total Rollout Time

120minutes

Total Rollout Time

2.00hours

Number of Stages

8

Initial Canary Pods

1pods

Step by step

  1. Initial canary pods

    20 × 5%

    = 1 pods

  2. Total stages to reach 100%

    from 5% stepping by 15%

    = 8 stages

  3. Total rollout time: stages × evaluation period

    8 × 15 min

    = 120 min

How it works

A canary deployment gradually shifts traffic from the stable version to a new version in stages, evaluating health metrics at each stage before proceeding: starting at canary%, incrementing by the step size, and holding for the evaluation period at each stage until reaching 100%. Total rollout time is the number of stages multiplied by the evaluation period per stage, giving a predictable timeline for a fully automated progressive delivery pipeline.

Formula

totalRolloutTime = stages × evaluationPeriod

C_0
Starting canary percentage
\Delta C
Increment step percentage
E
Evaluation period per stage in minutes
T
Total rollout time in minutes

Frequently Asked Questions

How do I choose an evaluation period?

It should be long enough to capture a representative sample of traffic and surface delayed failure modes (e.g. memory leaks, cache warm-up issues) — 10-30 minutes is common for high-traffic services; low-traffic services may need longer to gather statistically significant data.

Should canary percentage steps be linear or exponential?

Many teams prefer smaller early steps (5% → 10% → 25% → 50% → 100%) to limit blast radius while confidence is low, then larger steps later once the canary has proven stable.

What metrics should gate promotion between stages?

Error rate, latency percentiles (p95/p99), and any business-specific health signals compared between the canary and stable baseline — most canary automation (Flagger, Argo Rollouts) supports defining these as promotion gates.

How is this different from a blue-green deployment?

Blue-green switches all traffic at once between two fully-provisioned environments, while canary progressively shifts a fraction of traffic, allowing early detection of issues with limited exposure before full rollout.

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