First-Time Pass Rate

First-Time Pass Rate measures the percentage of CI/CD pipeline runs that succeed on the first attempt. It reflects how reliably code moves through automated delivery pipelines without the need for re-runs, retries, or manual intervention.

Calculation

A first-time pass is defined as a pipeline run that completes all required stages—such as build, test, or deploy—without failure or retries. This excludes successful re-runs after previous failures.

The metric is calculated as:

first-time pass rate = successful first-attempt runs ÷ total pipeline runs × 100

Goals

First-Time Pass Rate helps teams assess the reliability of their pipelines and the stability of new changes. It answers questions like:

• How often does code pass validation cleanly the first time?
• Are our tests, infrastructure, and build scripts stable and trustworthy?
• Are re-runs masking underlying quality issues or flakiness?

A higher first-time pass rate leads to faster feedback, fewer wasted cycles, and more confidence in automation.

Variations

This metric is sometimes referred to as Clean Run Rate, Initial Success Rate, or Pass Without Retry Rate. Common variations include:

• By pipeline stage, such as build-only or test-only first pass rates
• By service or team, to localize failure sources
• By type of trigger, such as pull request, merge, or scheduled runs
• By failure reason, like infrastructure, test, or config-related issues
• By environment, such as staging vs. production

Some teams also track First-Time Merge Pass Rate, which isolates runs triggered by PR merges.

Limitations

This metric focuses on technical pipeline success—not whether the code is valuable, safe, or production-ready. A high pass rate may still include low-quality or under-tested changes.

It also doesn’t differentiate between user-caused and system-caused failures. Without root cause analysis, teams may misinterpret who or what is responsible for failed attempts.

To understand pipeline stability more holistically, pair this metric with:

Complementary Metric	Why It’s Relevant
Pipeline Success Rate	Shows the total percentage of successful runs, including those that required retries
Change Failure Rate	Helps determine whether pipeline passes are catching defects before release
Review Latency	Reveals whether time spent waiting on repeated failures is delaying code reviews

Optimization

Improving First-Time Pass Rate involves strengthening test reliability, pipeline hygiene, and code quality practices.

• Fix flaky tests. Eliminate non-deterministic failures that cause false negatives and waste developer time

• Validate pipeline changes in isolation. Test infra updates, new tools, or config changes before rolling them out to production pipelines

• Add clear failure diagnostics. Improve logs and error messaging to reduce the time it takes to fix root causes of failure

• Use fast feedback steps. Catch errors early with pre-build checks like linting or static analysis before triggering full test or deployment stages

• Track pass rate trends. Identify drops in first-time pass rate as an early signal of technical debt or pipeline degradation

First-Time Pass Rate reflects how smooth your engineering workflow really is. The fewer retries it takes to move changes forward, the more time teams have to build meaningful things.