Django and Celery structured event monitoring

Test the integration

Send and verify events with Django and Celery structured event monitoring

Use Django and Celery structured event monitoring where your app knows the final result. Collect only the fields you need, then verify a test event before building charts.

1
Choose the outcome
Django API monitoring
2
Define the contract
task_name, task_id, queue_name, and status
3
Log the final result
Emit one final event from Celery success and failure handlers instead of logging the full task payload.
4
Check the stored event
Exercise a known fixture, then inspect job_completed for one correctly typed terminal row.

Before you start

A server-side TELEMETRY_API_KEY
telemetry-sh initialized once per process
A propagated request or workflow identifier

Delivery setup

Install and initialize server-side

Initialize Telemetry for synchronous code or TelemetryAsync for asyncio code once per process with a server-side key. Keep ingestion credentials out of browser bundles, client-visible environment variables, source control, logs, and exception messages.

django-celery-install

pip installation

bash

python -m pip install telemetry-sh

1Create one reusable server-side client. Set its timeout and retry limit.
2Log an event when the operation succeeds, fails, retries, or times out.
3Send test events with known results and inspect the stored rows before enabling an alert.

Snippet

Start with one structured event

Add this shape where the workflow completes, fails, or retries. Then build the dashboard from real fields.

django-celery

Django and Celery structured event monitoring event

python

@task_postrun.connect
def record_task(sender, task_id, state, retval, **kwargs):
    telemetry.log("job_completed", {
        "job_name": sender.name,
        "job_id": task_id,
        "queue_name": sender.request.delivery_info.get("routing_key"),
        "status": "success" if state == "SUCCESS" else "failed",
        "attempt": sender.request.retries + 1,
        "duration_ms": task_duration_ms(task_id),
        "error_type": categorize_error(retval) if state != "SUCCESS" else None,
    })

Event schema

task_name, task_id, queue_name, and status

attempt, duration_ms, error_type, and item_count

request_id, account_id, environment, and release

Check your setup

Checkpoint 1

Emit one final event from Celery success and failure handlers instead of logging the full task payload.

Checkpoint 2

Preserve the same task ID across retries and record the attempt separately.

Checkpoint 3

Keep Django request instrumentation independent from task completion so async latency remains visible.

Verification

Prove the event arrived

Run this after exercising known success and failure cases. Replace the fallback table name if your final event contract differs from the snippet.

django-celery-verification

Django and Celery structured event monitoring verification query

sql

SELECT *
FROM job_completed
ORDER BY timestamp_utc DESC
LIMIT 20;

Confirm one terminal row per logical outcome, with the expected status, identifiers, units, and UTC time.

Inspect the inferred schema and verify that retries do not change field types or generate a new logical event ID.

Search the stored fields for credentials, raw payloads, prompts, private content, and unbounded error messages.

Exercise a provider timeout, ingestion rejection, and process shutdown before treating the dashboard as complete.

Implementation references

Review the event contract, data-safety guidance, and upstream primary documentation before enabling a new production path.

Python SDK Queue worker guide Celery task signals Django logging

Where to log

Keep the outcome event small and recoverable

This pattern provides

Record the outcome as an event you can query with SQL.
Stable fields for dashboards, alerts, and cross-event correlation.
Test events for checking success, failure, retries, and timeouts.

This pattern does not provide

An OTLP exporter, automatic collection pipeline, or replacement for detailed traces and diagnostic logs.
Exactly-once delivery merely because the payload contains an event ID.
Permission to collect raw provider payloads, user content, credentials, or regulated data.

Delivery and idempotency Batching and shutdown Troubleshoot ingestion

Example event schemas

Check what each event records, when to send it, and which field types it needs. Review the example payload and privacy checklist before using it in production.

Async reliability11 fields