用大模型自动生成云服务故障排查指南，提升响应效率。
FixItFlow: Automated Troubleshooting Guide Generation from Cloud Incidents
- 基于历史故障数据提取诊断模式，用大模型生成结构化排查指南。
- 人工评估中61.5%指南被认为清晰，关联事件处理时间缩短2.3倍。
- 适合需要快速生成和更新故障应对文档的运维团队。
云服务频繁发生故障，需快速诊断与修复。故障排查指南有助于工程师一致响应，但手动编写耗时且常不完整、过时。我们提出FixItFlow，一种基于大语言模型的自动化系统，从历史故障数据中生成排查指南。该系统提取工程师操作中的诊断模式，合成包含经验证命令的结构化指南，并通过严格验证防止虚构内容。在26名工程师的评估中，生成指南获得61.5%的正面评价，对有配套指南的事件，平均修复时间减少2.3倍。结果表明，自动化指南生成可提升故障响应效率，减轻工程团队文档负担。
原文摘要 · Abstract (English)
Cloud services experience frequent incidents that require rapid diagnosis and resolution. Troubleshooting guides help engineers respond consistently, but creating them manually is labor-intensive, resulting in incomplete coverage and outdated documentation. We present FixItFlow, an automated system that generates troubleshooting guides from historical incident data using large language models. The system extracts diagnostic patterns from engineer actions, synthesizes structured guides with verified commands, and enforces strict validation to prevent fabricated content. In our evaluation with 26 engineers, generated guides achieved 61.5\% positive ratings for clarity and demonstrated a 2.3x reduction in mitigation time for incidents with associated guides. These results indicate that automated guide generation can improve incident response while reducing documentation burden on engineering teams.
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