Monitoring Background Jobs and Worker Processes (Celery, Sidekiq, RQ)

Why monitor background jobs?

Task queues are a core part of modern backend applications. If a worker crashes, a queue gets stuck, or a task hangs — you might not know until it’s too late. Monitoring helps you catch these failures early and prevent data loss or degraded performance.

What should you monitor?

• Worker activity (are they running?)
• Queue length
• Task execution time
• Execution errors

Celery

1. Check worker activity

celery -A your_app status

You can run this periodically and send results to your monitoring system via webhook or ping.

2. Monitor with Flower

Flower is a web UI and API for Celery. It provides JSON data about workers, tasks, failures, and more.

celery -A your_app flower --port=5555

You can query its API (e.g., /api/tasks) or export metrics regularly.

Sidekiq

Sidekiq includes a built-in dashboard with stats on queues, retries, and errors.

You can automate monitoring by:

• Checking queue stats periodically
• Sending pings from critical jobs (start/finish)

RQ (Redis Queue)

RQ supports a web interface via rq-dashboard:

pip install rq-dashboard
rq-dashboard

You can query the dashboard API or include pings in your job functions.

Universal pattern: "job pings"

The most reliable method is to send an HTTP ping at the start and end of each job. Example:

import requests

def task():
    requests.get("https://ev.okchecker.com/p/<api-key>/backup-db?status=start")
    try:
        # job logic here
        pass
    finally:
        requests.get("https://ev.okchecker.com/p/<api-key>/backup-db?status=success")

Alerts and logging

Add alerts via email, Slack, or Telegram if tasks fail or exceed time limits. It’s also helpful to log when jobs start, finish, or crash.

Conclusion

Monitoring your task queues helps prevent silent failures. Use health checks, pings, metrics, and alerts to stay in control of your background processing.