The Cost of Downgrading Build Systems : A Case Study of Kubernetes
Gareema Ranjan, Mahmoud Alfadel, Gengyi Sun, Shane McIntosh
摘要
Since developers invoke the build system frequently, its performance can impact productivity. Modern artifact-based build tools accelerate builds, yet prior work shows that teams may abandon them for alternatives that are easier to maintain. While prior work shows why downgrades are performed, the implications of downgrades remain largely unexplored. In this paper, we describe a case study of the Kubernetes project, focusing on its downgrade from an artifact-based build tool (Bazel) to a language-specific solution (Go Build). We reproduce and analyze the full and incremental builds of change sets during the downgrade period. On the one hand, we find that Bazel builds are faster than Go Build, completing full builds in 23.06-38.66 % less time and incremental builds in up to 75.19 % less time. On the other hand, Bazel builds impose a larger memory footprint than Go Build of 81.42-351.07 % and 118.71-218.22 % for full and incremental builds, respectively. Bazel builds also impose a greater CPU load at parallelism settings above eight for full builds and above one for incremental builds. We estimate that downgrading from Bazel can increase CI resource costs by up to 76 %. We explore whether our observations generalize by replicating our Kubernetes study on four other projects that also downgraded from Bazel to older build tools. We observe that while build time penalties decrease, Bazel consistently consumes more memory. We conclude that abandoning artifact-based build tools, despite perceived maintainability benefits, tends to incur considerable performance costs for large projects. Our observations may help stakeholders to balance trade-offs in build tool adoption.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
它引用的顶会 Paper3
- A model for detecting faults in build specificationsThodoris Sotiropoulos, Stefanos Chaliasos, Dimitris Mitropoulos, Diomidis SpinellisOOPSLA 2020 · 被引用 16 次
- The Classics Never Go Out of Style: An Empirical Study of Downgrades from the Bazel Build TechnologyMahmoud Alfadel, Shane McIntoshICSE 2024 · 被引用 4 次
- Understanding the Implications of Changes to Build SystemsMahtab Nejati, Mahmoud Alfadel, Shane McIntoshASE 2024 · 被引用 1 次
相关 Paper
- Automated Dependency Optimization for Artifact-Based Build SystemsHongxu Xu, Zhenyang Xu, Shane McIntosh, Chengnian SunISSTA 2026
- Automating Dockerfile Refactoring to Multi-stage BuildsDongjin Chen, Wenhua Yang, Minxue Pan, Yu ZhouFSE 2026
- An Empirical Study and Benchmark of Kubernetes Misconfiguration ScannersHaeun Eom, Bohyun Suk, Sungjae HwangISSTA 2026
- Towards Understanding Docker Build Faults in Practice: Symptoms, Root Causes, and Fix PatternsYiwen Wu, Yang Zhang, Tao Wang, Bo Ding 等FSE 2025 · 被引用 4 次
- ThunderAgent: A Fast, Simple, and Program-Aware Agentic Inference SystemHao Kang, Ziyang Li, Xinyu Yang, Weili Xu 等ICML 2026 · 被引用 14 次
