Celery

Why deploy Celery on Render?

Celery is a distributed task queue for Python that enables asynchronous and scheduled job execution. It solves the problem of offloading time-consuming tasks (like sending emails, processing images, or running background jobs) from your main application thread, allowing your web app to remain responsive while work happens in the background.

This template deploys a complete Celery stack—worker, Redis broker, and Flower monitoring dashboard—all pre-wired with the correct environment variables so services can discover each other automatically. Instead of manually provisioning Redis, configuring connection URLs across multiple services, and setting up health checks, you get a working distributed task queue in one click. Render's native service discovery handles the internal networking, and you can scale workers independently by adjusting instance counts in the dashboard.

Architecture

What you can build

After deploying, you'll have a Celery worker running on Render that can process background tasks asynchronously from your main application. You'll also get Flower, a web dashboard for monitoring task execution, worker status, and queue health. This setup lets you offload long-running jobs like sending emails, processing uploads, or running scheduled tasks without blocking your web server.

Key features

• Celery task queue: Pre-configured Celery setup for running distributed background tasks and async job processing.
• Flower monitoring dashboard: Includes Flower web UI deployment for real-time monitoring of Celery workers, tasks, and queues.
• One-click Render deploy: Uses Render's deploy button and Blueprint for instant infrastructure provisioning from the forked repo.
• Production-ready config: Comes with render.yaml Blueprint defining the worker and monitoring services for immediate deployment.

Use cases

• Backend developer offloads slow email sending to background workers
• Data engineer schedules nightly report generation jobs automatically
• SaaS founder monitors task queues via Flower dashboard
• E-commerce dev processes image thumbnails asynchronously after upload

What's included

Next steps

1. Open the Flower dashboard URL in your browser — You should see the Celery worker listed as online with a green status indicator and zero active tasks
2. Test a sample task by triggering one from your application or the Flower dashboard — You should see the task appear in Flower's task list with a 'SUCCESS' state within a few seconds
3. Configure your application code to connect to the Celery broker using the provided Redis URL — You should be able to call .delay() on a task and see it queued and processed in the Flower monitor

Resources

• Celery official site