Build Success Rate Calculator
Calculate the percentage of CI builds that pass over a given time window.
About Build Success Rate Calculator
Build success rate is the simple percentage of builds that passed out of all builds run, giving a snapshot reliability metric for a pipeline or team over a period. Mean Time Between Failures complements it with a time-based view — total elapsed time divided by the number of failures — which better reflects how often a team actually experiences a broken build in practice, since a low-frequency but high-volume pipeline can have the same success rate as a high-frequency one while producing failures at a very different real-world cadence.
Formulas
Success rate
successRate = (successfulBuilds / totalBuilds) × 100
- S
- Number of successful builds
- N
- Total builds
- r
- Success rate percentage
MTBF
MTBF = totalTime / failures
- T
- Total elapsed time in hours
- F
- Number of failures
- \text{MTBF}
- Mean time between failures in hours
Worked example
With the default values below, Build Success Rate Calculator returns Build Success Rate of 92.00%. Change any input above and every figure here is recalculated in your browser.
Inputs used
- Total Buildsaccepts 1–10,000,000 builds
- 500 builds
- Successful Buildsaccepts 0–10,000,000 builds
- 460 builds
- Total Elapsed Timeaccepts 0.01–1,000,000 hr
- 720 hr
Results
- Build Success Rate
- 92.00%
- Mean Time Between Failures
- 18.00 hr
- Total Failed Builds
- 40 builds
Step by step
- 1Success rate = successes ÷ total × 100= 92.00%
- 2Failures = total − successes= 40 failures
- 3MTBF = total time ÷ failures= 18.00hr
Assumptions and limits
- The result is derived only from the 3 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
Why track both success rate and MTBF instead of just one?
Success rate is volume-normalized and ignores build frequency, while MTBF is time-normalized and ignores how many builds ran — a pipeline running 10x more builds per day at the same success rate has a proportionally shorter MTBF, which is often the more actionable signal for on-call/interrupt burden.
What's considered a healthy build success rate?
Mature CI pipelines with good test isolation typically target 90%+ on main-branch builds; consistently lower rates often point to flaky tests, unstable infrastructure, or a broken-build culture where failures aren't fixed before more commits land.
Should failures caused by infrastructure be counted the same as test failures?
For an honest reliability picture, track them separately if possible — infrastructure flakiness (agent crashes, network blips) and genuine code/test failures point to very different remediation, even though both count as 'failed builds' in a raw success rate.