AI coding has made CI a bottleneck, so we reworked ours to keep up

一句话概要

We cut PR wait time and running costs by rethinking CI as a system, from the infrastructure underneath it to how work gets scheduled and tests get parallelized.

原文开头节选

Earlier this year, I opened Linear to find that Tuomas, our CTO, had assigned an issue to me, titled “CI costs are high.” While I was at it, he also wanted me to make CI faster.

Agents have made it exponentially faster to ship code, but validating those changes hasn’t quite kept up at the same rate. Every PR still has to pass through CI, so as development accelerates, CI becomes a bottleneck, driving up infrastructure costs and leaving developers and agents waiting longer for feedback.

In our pursuit to make CI more performant at Linear, we optimized for how long a PR waits on CI and how much runner time it consumes. Despite our test suites almost quadrupling since the start of the year, we brought pull request wait time down from more than 6 minutes to just over 5, while cutting runner time per test roughly in half.

Linear’s codebase is primarily TypeScript, but many of these optimizations apply across languages and toolchains.

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这条动态今日登上 Hacker News 首页(73 赞 / 61 评论,来源 linear.app)。技术雷达每日自动聚合 AI 工程、后端架构、DevOps 方向的前沿动态;相关工程落地可浏览下方的相关服务与延伸阅读,或直接与我们团队交流。