Bazel's next generation focuses on improving build performance and developer experience. Key changes include Starlark, a Python-like language for build rules offering more flexibility and maintainability, as well as a transition to a new execution phase, Skyframe v2, designed for increased parallelism and scalability. These upgrades aim to simplify complex build processes, especially for large projects, while also reducing overall build times and improving caching effectiveness through more granular dependency tracking and action invalidation. Additionally, remote execution and caching are being streamlined, further contributing to faster builds by distributing workload and reusing previously built artifacts more efficiently.
GitHub Actions workflows, especially those involving Node.js projects, can suffer from significant disk I/O bottlenecks, primarily during dependency installation (npm install). These bottlenecks stem from the limited I/O performance of the virtual machines used by GitHub Actions runners. This leads to dramatically slower execution times compared to local machines with faster disks. The blog post explores this issue by benchmarking npm install operations across various runner types and demonstrates substantial performance improvements when using self-hosted runners or alternative CI/CD platforms with better I/O capabilities. Ultimately, developers should be aware of these potential bottlenecks and consider optimizing their workflows, exploring different runner options, or utilizing caching strategies to mitigate the performance impact.
HN users discussed the surprising performance disparity between GitHub-hosted and self-hosted runners, with several suggesting network latency as a significant factor beyond raw disk I/O. Some pointed out the potential impact of ephemeral runner environments and the overhead of network file systems. Others highlighted the benefits of using actions/cache or alternative CI providers with better I/O performance for specific workloads. A few users shared their experiences, with one noting significant improvements from self-hosting and another mentioning the challenges of optimizing build processes within GitHub Actions. The general consensus leaned towards self-hosting for I/O-bound tasks, while acknowledging the convenience of GitHub's hosted runners for less demanding workflows.
Summary of Comments ( 50 )
https://news.ycombinator.com/item?id=43601356
Hacker News commenters generally agree that Bazel's remote caching and execution are powerful features, offering significant build speed improvements. Several users shared positive experiences, particularly with large monorepos. Some pointed out the steep learning curve and initial setup complexity as drawbacks, with one commenter mentioning it took their team six months to fully integrate Bazel. The discussion also touched upon the benefits for dependency management and build reproducibility. A few commenters questioned Bazel's suitability for smaller projects, suggesting the overhead might outweigh the advantages. Others expressed interest in alternative build systems like BuildStream and Buck2. A recurring theme was the desire for better documentation and easier integration with various languages and platforms.
The Hacker News post titled "The next generation of Bazel builds" (linking to a blogsystem5.substack.com article about Bazel) has generated a moderate number of comments, many of which delve into the nuances and practicalities of using Bazel.
Several commenters discuss Bazel's performance characteristics. One notes that while Bazel boasts impressive incremental build speeds, clean builds can be significantly slower, sometimes even outpaced by traditional tools like Make. Another commenter points out the high resource demands of Bazel, particularly its memory consumption, posing challenges for developers with limited resources.
The conversation also touches upon Bazel's complexity and the learning curve associated with its adoption. Some commenters acknowledge the initial investment required to understand Bazel's concepts and configuration but argue that the long-term benefits in terms of build speed and scalability justify the effort. Others express frustration with the perceived opacity of Bazel's inner workings and the difficulty of debugging build issues.
A few commenters share their experiences with Bazel in different environments. One recounts success using Bazel to manage a complex C++ project, praising its ability to handle dependencies and enforce build consistency. Another describes challenges integrating Bazel with existing workflows and tooling.
The topic of remote caching and execution also emerges, with commenters highlighting the potential for significant performance gains by leveraging shared caches and distributed build infrastructure. However, the discussion also acknowledges the practical considerations of setting up and maintaining such systems.
Overall, the comments paint a picture of Bazel as a powerful but complex build tool. While many appreciate its capabilities, they also acknowledge the challenges and trade-offs involved in its adoption. The discussion doesn't reach a definitive consensus on whether Bazel is the "right" tool for every project, suggesting that the decision depends heavily on the specific needs and context of the development team.