apache/airflow

Add REST API metrics (latency, QPS, errors)

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#56,034 创建于 2025年9月24日

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 (7 评论) (0 反应) (0 负责人)Python (44,809 star) (16,781 fork)batch import
area:APIgood first issuekind:feature

描述

Description

Currently, Airflow’s REST API does not emit any metrics. It would be valuable to have basic API metrics for observability.

Use case/motivation

  • Track API performance (p95/p99 latency).
  • Monitor usage patterns (QPS per endpoint).
  • Alert on failures (error spikes).

Related issues

No response

Are you willing to submit a PR?

  • Yes I am willing to submit a PR!

Code of Conduct

贡献者指南

技术栈
pythonrest api
领域
backendobservabilityperformanceapi
议题类型
feature
难度面向新贡献者的预计实现难度，1 表示很小改动，5 表示专家级工作。
4
预计时间有经验贡献者完成调查、实现、测试并准备 pull request 的粗略时间范围。
3-5 days
活动状态议题当前的可参与程度：新鲜、活跃、陈旧、阻塞或等待维护者输入。
active
清晰度议题是否清楚说明期望改动、验收标准和下一步。
mostly clear
前置要求
PythonAirflow basicsREST API knowledgeObservability concepts
新手友好度1-100 的估计分数，表示该议题对首次贡献者的友好程度。
35
研究方向
Start by examining the REST API handler files in airflow/api connexion to understand request structure. Check if Airflow already has a metrics client (e.g., statsd) used elsewhere. Consider implementing a middleware that records latency, QPS, and error count per endpoint. Review how other parts of Airflow (like tasks) emit metrics for consistency. Look into using OpenTelemetry if Airflow supports it, or propose adopting it. Discuss your approach in the issue before coding.