Engineering
After months of incremental performance work on our CI pipelines, we finally cracked a big nut: slashing our average production build time from over twelve minutes down to just under six. The best part is we did it without replacing any of our core tooling — no swapping out Webpack, no migrating off Babel, no Kubernetes reshuffling. It was all about tightening the loop, understanding where the real bottlenecks lived, and applying targeted pressure.
We started by analyzing the entire build graph, from dependency resolution to asset compilation to final bundle output. What we found was surprising: the vast majority of time wasn't spent on the fanciest steps, but on simple serialization and I/O bottlenecks that had grown over years of adding features and plugins. By caching intermediate artifacts more aggressively and parallelizing several previously sequential plugin steps, we immediately saw a 40% reduction in wall-clock time.
Too often, engineering teams jump to rewrite or replace their build tools based on anecdotal evidence or industry hype. A senior engineer complains the build is slow, so the team spends three months migrating from one bundler to another, only to find the new one has its own set of trade-offs and the perceived slowness hasn't fully gone away. We wanted to avoid that trap entirely.
We instrumented every phase of our build with granular tracing, outputting logs that showed exact durations per file and per plugin. This data gave us a clear heat map of where to focus. The biggest win came from a plugin that was re-transpiling already-transpiled vendor bundles every time — a classic case of configuration debt that had gone unnoticed for months. Fixing that single misconfiguration cut over two minutes off the average build.
“The biggest win came from a plugin that was re-transpiling already-transpiled vendor bundles every time — a classic case of configuration debt.”
With the low-hanging fruit picked, we turned to more systemic improvements: distributing our test suite across more CPU cores, enabling filesystem caching for resolved dependencies, and extracting a particularly heavy documentation build into a separate, lazily-triggered pipeline. None of these changes required a new framework or a massive refactor. They just required the data to point us to the right problems and the discipline to fix them one at a time.
Six months later, the build is still under six minutes, and the team has a much healthier relationship with our tooling. We know what it's doing, why it's doing it, and how to fix it when it gets slow again. That, more than the time saved, is the win that will keep paying dividends.