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.
Dagger introduces a portable, reproducible development and CI/CD environment using containers. It acts as a programmable shell, allowing developers to define their build pipelines as code using a simple, declarative language (CUE). This approach eliminates environment inconsistencies by executing every step within containers, from dependency installation to testing and deployment. Dagger caches build steps efficiently, speeding up development cycles, and its container-native nature ensures builds behave identically across different machines, from developer laptops to CI servers. This allows developers to focus on building software, not wrestling with environment configurations.
Hacker News users discussed Dagger's potential, its similarity to other tools, and its reliance on Go. Several commenters saw it as a promising evolution of build systems and CI/CD, praising its portability and potential to simplify complex workflows. Comparisons were made to Nix, BuildKit, and Earthly, with some arguing Dagger offered a more user-friendly approach using a familiar shell-like syntax. Concerns were raised about the Go dependency, potentially limiting its adoption in non-Go environments and adding complexity for tasks like cross-compilation. The dependence on a container runtime was also noted, while some appreciated the declarative nature of configurations, others expressed skepticism about its long-term practicality. There was also interest in its ability to interface with existing tools like Docker Compose and Kubernetes.
Wild is a new, fast linker for Linux designed for significantly faster linking than traditional linkers like ld. It leverages parallelization and a novel approach to symbol resolution, claiming to be up to 4x faster for large projects like Firefox and Chromium. Wild aims to be drop-in compatible with existing workflows, requiring no changes to source code or build systems. It also offers advanced features like incremental linking and link-time optimization, further enhancing development speed. While still under development, Wild shows promise as a powerful tool to accelerate the build process for complex C++ projects.
HN commenters generally praised Wild's speed and innovative approach to linking. Several expressed excitement about its potential to significantly improve build times, particularly for large C++ projects. Some questioned its compatibility and maturity, noting it's still early in development. A few users shared their experiences testing Wild, reporting positive results but also mentioning some limitations and areas for improvement, like debugging support and handling of complex linking scenarios. There was also discussion about the technical details behind Wild's performance gains, including its use of parallelization and caching. A few commenters drew comparisons to other linkers like mold and lld, discussing their relative strengths and weaknesses.
JReleaser simplifies and automates project releases across various platforms. It streamlines the process of creating release artifacts, generating checksums, and publishing them to a variety of distribution channels, including package managers like Homebrew, SDKMAN!, and Chocolatey, as well as artifact repositories like Maven Central, and GitHub Releases. JReleaser supports multiple project types (Java, Go, Kotlin, etc.) and offers flexible configuration through its declarative approach, allowing developers to define release logic in a centralized manner and avoid tedious manual steps. This frees up developers to focus on coding rather than deployment logistics.
Hacker News users generally reacted positively to JReleaser, praising its simplicity and ease of use compared to more complex tools. Several commenters appreciated its support for various platforms and package managers, finding it particularly useful for Java projects but also applicable to other languages. Some pointed out potential alternatives like goreleaser, while others discussed the benefits of standardizing release processes. A few users inquired about specific features, such as signing and checksum generation, while others shared their personal experiences using JReleaser for their own projects. The overall sentiment leaned towards JReleaser being a valuable tool for streamlining and automating the release process.
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.