apache/airflow

Add REST API metrics (latency, QPS, errors)

Open

#56034 opened on Sep 24, 2025

View on GitHub
 (7 comments) (0 reactions) (0 assignees)Python (44,809 stars) (16,781 forks)batch import
area:APIgood first issuekind:feature

Description

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

Contributor guide

Tech stack
pythonrest api
Domain
backendobservabilityperformanceapi
Issue type
feature
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
4
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
3-5 days
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
active
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
mostly clear
Prerequisites
PythonAirflow basicsREST API knowledgeObservability concepts
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
35
Research direction
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.