pydantic/logfire

Celery needs to be instrumented on client side for distributed tracing

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#972 opened on Mar 31, 2025

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Description

Demo:

import logfire
from celery import Celery
from celery.signals import worker_init
from fastapi import FastAPI

@worker_init.connect()
def init_worker(*args, **kwargs):
    logfire.configure(service_name="worker")
    logfire.instrument_celery()

app = Celery("tasks", broker="redis://localhost:6379/0")

@app.task
def add(x: int, y: int):
    return x + y

fapp = FastAPI()

logfire.configure()
logfire.instrument_fastapi(fapp)
########### Important:
logfire.instrument_celery()


@fapp.get("/hello")
async def hello(name: str):
    add.delay(42, 50)
    return {"message": f"hello {name}"}


if __name__ == "__main__":
    import uvicorn

    uvicorn.run(fapp)

The top-level logfire.instrument_celery() is required for the context propagation, based on https://github.com/open-telemetry/opentelemetry-python-contrib/issues/1002#issuecomment-1275273134

This should be documented at least, maybe fixed in some other way, e.g. in OTel.

Contributor guide

Research direction
Investigate the OpenTelemetry Python Celery instrumentation and check if client side context propagation is missing. Look into the linked issue and the OpenTelemetry Python contrib repository for solutions.
Tech stack
python
Domain
backendobservability
Issue type
Bug
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.
1-3 hours
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
PythonCeleryOpenTelemetry
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
55