Canary Deployment Calculator

Calculate rollout timeline and exposure percentage for a staged canary deployment.

About Canary Deployment Calculator

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

Worked example

With the default values below, Canary Deployment Calculator returns Total Rollout Time of 120. Change any input above and every figure here is recalculated in your browser.

Inputs used

Total Podsaccepts 1–100,000 pods: 20 pods
Starting Canary %accepts 1–100 %: 5 %
Increment Stepaccepts 1–100 %: 15 %
Evaluation Periodaccepts 1–10,000 minutes: 15 minutes

Results

Total Rollout Time: 120 minutes
Total Rollout Time: 2.00 hours
Number of Stages: 8
Initial Canary Pods: 1 pods

Step by step

1Initial canary pods= 1 pods
2Total stages to reach 100%= 8 stages
3Total rollout time: stages × evaluation period= 120 min

Assumptions and limits

The result is derived only from the 4 inputs listed above. Anything not among them is not part of the calculation.
In particular, this calculator does not take inflation, tax or fees or charges into account.
Figures are rounded for display to 2 decimal places, so totals built from several rounded parts can differ slightly from the unrounded arithmetic.

How these calculators are built and tested is described on the Methodology page. If a figure looks wrong, please report it.

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.