Build failure rate
Also known as Build failure rate metric, Build failure rate in DevOps
Definition
Build failure rate is a software delivery concept used to describe a specific event, interval, control, or operating condition in the path from source change to production behavior. A useful definition names the boundary, unit, and decision the measure supports.
How to use the concept
Start by writing down the event that begins the clock, the event that ends it, and the population that belongs in the denominator. For build failure rate, this boundary matters because retries, approvals, parallel work, and excluded services can otherwise change the result without changing the underlying workflow.
A concrete delivery example
Imagine a change moving through build, review, validation, and production. The timeline shows 20 minutes of execution, 90 minutes of queueing, and one overnight approval wait. A build failure rate report should preserve those stages so the team can address the dominant delay instead of shortening a convenient but minor step.
Limitations and interpretation
This signal is sensitive to instrumentation. Missing deployments, duplicate webhooks, hidden retries, and inconsistent labels can make build failure rate look better or worse. Preserve event-level evidence and record the policy used to include or exclude cases.
Before acting on build failure rate, compare the current observation with a compatible baseline and ask which underlying event produced it. Keep the raw records, counting policy, and ownership visible. When the signal changes, inspect the surrounding workflow for queueing, rework, failed checks, or recovery work. That practice makes the glossary term useful for diagnosis rather than a label attached to a dashboard.
How this relates to Weave
Weave's Engineering Intelligence can help teams examine build failure rate alongside code, pull request, quality, and delivery context. That view is useful for finding the workflow behind a result and deciding what to investigate next. The underlying repository, deployment, incident, or observability system remains the source of truth for the event, and teams should confirm the available integrations before relying on any field.
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