apache/airflow

Add REST API metrics (latency, QPS, errors)

Open

#56,034 opened on Sep 24, 2025

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

Repository metrics

Stars
 (44,809 stars)
PR merge metrics
 (Avg merge 7d 18h) (834 merged PRs in 30d)

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

Research direction
Study Airflow's existing stats/metrics implementation (e.g., StatsD) and the REST API endpoint handlers to add custom metrics for latency, QPS, and errors.
Tech stack
python
Domain
backendapiobservability
Issue type
Feature
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
3
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
1-2 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
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
40