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Runner Capacity Calculator

Work out runner capacity instantly with clear inputs, formula shown and shareable results.

About Runner Capacity Calculator

Builds in flight follow Little's law: arrival rate multiplied by build duration. Runner count is that concurrency divided by the utilisation you are willing to run at, and the utilisation target matters because queue wait grows as rho/(1-rho): at 90 percent utilisation a 12-minute build waits nearly two hours, while at 70 percent it waits under half an hour.

Formula

Runner sizing

concurrency = builds per hour x duration / 60; runners = ceil(concurrency / utilisation target); queue wait ~ rho x duration / (1 - rho)

Worked example

With the default values below, Runner Capacity Calculator returns Runners required of 26. Change any input above and every figure here is recalculated in your browser.

Inputs used

Builds per hour at peakminimum 0.1
90
Average build durationminimum 0.1 min
12 min
Acceptable queue waitminimum 0.1 min
2 min
Target runner utilisationaccepts 10–100 %
70 %

Results

Runners required
26
Builds in flight at peak
18.00
Projected runner utilisation
69.2%
Estimated queue wait
27.00 min

Step by step

  1. 1Values used
  2. 2Runner sizing
  3. 3Runners required= 26
  4. 4Builds in flight at peak= 18.00
  5. 5Projected runner utilisation= 69.2
  6. 6Estimated queue wait= 27.00 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, fees or charges or compounding frequency 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

Why not run runners at 95 percent utilisation?

Because arrivals are bursty. Queueing theory says wait time explodes near saturation, and CI traffic clusters around commits and merge windows rather than arriving smoothly.

Are ephemeral runners better than persistent ones?

They give clean environments and elastic capacity, at the cost of losing local caches. A shared remote cache recovers most of that.

Related Calculators

Runner Capacity Calculator – Calculate Runners required