📄 中文摘要
通过将团队分散的文档重构为可由 AI 查询的格式，并将每个服务的 Splunk 日志事件建模为 TypeScript 类型，建立了一套调查工作流程。复杂的事件调查时间从约 2 小时缩短至 30 分钟，并且系统在每次归档调查后变得更智能。这一方法特别适合处理多服务间事件调查的后端和平台工程师，解决了文档更新不及时的问题。
我停止与日志工具作斗争，构建了一个 AI 协助调查者
出处: I Stopped Fighting My Logging Tools and Built an AI Co-Investigator
发布: 2026年2月25日
📄 English Summary
I Stopped Fighting My Logging Tools and Built an AI Co-Investigator
Restructuring scattered documentation into an AI-queryable format and modeling each service's Splunk log events as TypeScript types led to the creation of an investigation workflow. Complex incident investigations were reduced from approximately 2 hours to 30 minutes, and the system becomes smarter with each archived investigation. This approach is particularly beneficial for backend and platform engineers managing on-call rotations and dealing with outdated documentation across multiple services.