From Telemetry to Automated Incident Response: My DevOps & Observability Journey

说明与用途

通过 OpenTelemetry 收集指标、日志和跟踪，在 Grafana 中可视化，配置 5xx 警报，自动创建事件，并将证据传递给 Codex CLI AI 编码代理，实现了在 FastAPI 应用中快速检测、调查和修复错误。

问题

A basic FastAPI order‑tracking API can fail in production without observability, making troubleshooting manual, error‑prone, and slow.

结果

The observability stack enabled automated detection of 5xx errors, automated incident creation, evidence collection, and AI‑driven code fixes, reducing manual debugging time and improving reliability.

工作流

• Instrument FastAPI with OpenTelemetry to emit HTTP route, status, logs, traces, and metrics
• Deploy OpenTelemetry Collector to receive OTLP data and route to Prometheus, Loki, and Tempo
• Configure Grafana to visualize signals and set alert rules for 5xx responses
• Implement an incident‑response service exposing POST /alerts to receive Grafana alerts and gather evidence
• Integrate Codex CLI as a coding agent that receives incident context, investigates, and applies fixes
• Restart and verify the application after remediation

证据

The project started as a basic Order Tracker application backed by SQLite.

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The final architecture introduced several components: OpenTelemetry Collector, Prometheus, Loki, Tempo, Grafana.

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After telemetry was available, I configured Grafana alerting for server‑side failures. The goal was to detect 5xx responses.

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The service exposes: POST /alerts. When Grafana sends an alert, the responder stores the incident information and gathers useful evidence.

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The most interesting part of the exercise was connecting the incident workflow to a coding agent.

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