TECH Signal 278
Linear reworks CI to reduce pull request wait times and runner costs
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Linear has optimized its CI process, reducing pull request wait time from over 6 minutes to just over 5.
As AI coding accelerates development, CI processes can become bottlenecks, increasing costs and slowing feedback. Linear's improvements demonstrate effective strategies that other teams can adopt to enhance CI performance and reduce associated infrastructure expenses. This is crucial for maintaining developer productivity as code deployment speeds up.
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Linear reduced pull request wait time from over 6 minutes to just over 5.
Shifting workloads to faster third-party runners improved job runtime by 34% on average.
Optimizations in linting and test execution significantly decreased resource usage and CI costs.
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Linear identified that the integration of AI coding tools had made their Continuous Integration (CI) process a bottleneck, leading to increased infrastructure costs and delayed feedback on pull requests (PRs). To address this, they implemented several optimizations aimed at improving both the speed and efficiency of their CI pipeline.
One of the key changes was migrating workloads from GitHub Actions to third-party runners equipped with higher-performance CPUs and better caching. This migration resulted in an average job runtime improvement of 34%, with specific tasks, such as TypeScript compilation, seeing even greater reductions in execution time.
Further optimizations included rewriting linting rules to eliminate dependencies on TypeScript type information, which reduced both memory usage and execution times. This allowed the team to streamline their CI processes, resulting in less overhead and faster feedback loops for developers.
Additionally, Linear focused on optimizing the jobs that block other processes in the CI pipeline. By improving the speed of their change-detection jobs and limiting the amount of data fetched during these processes, they significantly reduced wait times and improved overall CI responsiveness.
The success of these changes highlights the importance of regularly reviewing and optimizing CI systems, especially as development practices evolve. As teams adopt more advanced coding techniques, such as AI-assisted coding, maintaining an efficient CI process will be essential in ensuring that development timelines remain tight and that developers can work without unnecessary delays.
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