When our engineering team started noticing that builds were taking longer than expected, we knew we had to act quickly. Our CI pipeline had grown organically over two years, and what began as a simple workflow had become a complex web of scripts and dependencies.
Instead of reaching for new tools or rewriting our entire infrastructure, we decided to take a more measured approach. We focused on understanding exactly where time was being spent before making any changes.
Start by measuring, not guessing
Our first step was to instrument the build process with detailed timing logs. We added granular timestamps at every stage of the pipeline, from dependency installation through compilation and testing. The data revealed surprising bottlenecks that we had never suspected.
The biggest wins came from optimizing the parts we thought were already fast. — Dana Okoro
By analyzing the telemetry, we discovered that caching was inconsistent across different job types. We also identified several large dependencies that were being reinstalled on every build, even when they had not changed. A few targeted improvements to our caching strategy and dependency management yielded immediate results.
Within three weeks, average build times dropped from 14 minutes to just under 7 minutes. The most satisfying part was that we achieved this without introducing any new services or changing our core technology stack.