基於大語言模型的全自動混沌工程：實現低成本構建高韌性軟件系統

摘要

混沌工程（Chaos Engineering）是一种旨在提升分布式系统韧性的工程技术，其核心是通过主动向系统注入故障来测试韧性、发现潜在弱点，并在生产环境发生故障前进行修复。现有的混沌工程工具已能自动化执行预设实验，但实验规划及基于结果的系统优化仍依赖人工操作。这些过程不仅耗费大量人力，还需要多领域专业知识。为应对这些挑战并实现低成本构建高韧性系统的目标，本文提出ChaosEater系统——基于大语言模型实现全周期自动化的混沌工程框架。该系统依据标准化的混沌工程周期预设智能体工作流，并将流程中的细分任务分配给大语言模型。ChaosEater专注于基于Kubernetes的软件系统混沌工程，因此其大语言模型通过需求定义、代码生成、测试调试等软件工程任务完成完整周期。我们通过对中小型及大规模Kubernetes系统的案例研究进行评估，结果表明该系统能以极低的时间和经济成本持续完成合理的混沌工程周期，其有效性同时获得了人类工程师与大语言模型的定性验证。

English

Chaos Engineering (CE) is an engineering technique aimed at improving the resilience of distributed systems. It involves intentionally injecting faults into a system to test its resilience, uncover weaknesses, and address them before they cause failures in production. Recent CE tools automate the execution of predefined CE experiments. However, planning such experiments and improving the system based on the experimental results still remain manual. These processes are labor-intensive and require multi-domain expertise. To address these challenges and enable anyone to build resilient systems at low cost, this paper proposes ChaosEater, a system that automates the entire CE cycle with Large Language Models (LLMs). It predefines an agentic workflow according to a systematic CE cycle and assigns subdivided processes within the workflow to LLMs. ChaosEater targets CE for software systems built on Kubernetes. Therefore, the LLMs in ChaosEater complete CE cycles through software engineering tasks, including requirement definition, code generation, testing, and debugging. We evaluate ChaosEater through case studies on small- and large-scale Kubernetes systems. The results demonstrate that it consistently completes reasonable CE cycles with significantly low time and monetary costs. Its cycles are also qualitatively validated by human engineers and LLMs.

基於大語言模型的全自動混沌工程：實現低成本構建高韌性軟件系統

LLM-Powered Fully Automated Chaos Engineering: Towards Enabling Anyone to Build Resilient Software Systems at Low Cost

摘要

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