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Configure Celery for reliable delivery

  • Backend development
  • Data engineering
·Wed Aug 24 2022

Celery is probably the most used task runner in the Python ecosystem. Yet, I've found today that configuring it to support a basic scenario for such a critical piece in a software architecture surprisingly difficult and poorly documented.

So, what's the problem? Let's say we have a task taking several minutes to run. Imagine now that we have a server failure, completely independent of our source code: a server restart, a power failure, etc. Thus, the task was stopped in the middle of execution and didn't finished. Fine! Things like that happen often with computers 😏 All we want now is Celery to execute the task again after the server restart!

Well, actually, by default: it won't 🥹 This is actually an intended default of Celery. By the way, this is one of the main painpoint raised by the author of Dramatiq, a competing library.

Fortunately, there is a way to do it! And this blog post will save you hours of research 🙃


Here is the configuration you need to apply for this to work:

app = Celery(

Don't go now! I highly recommend you to read the rationale about it 👇


So what those options are doing? Basically, we need to tell Celery:

  • To acknowledge the task after their completion, not right before (task_acks_late).
  • To reject the task if the worker is lost or shutdown (task_reject_on_worker_lost).
  • By default, task rejections are persisted only in memory and thus lost if the server is stopped. So we need to setup a state file (worker_state_db).

The visibility timeout quirk

Still, if you test to manually kill the worker while a long task is running before restarting it, you'll see that the task looks like stuck and never re-executed.

Actually, this is normal behavior. Why? Because tasks are not re-delivered until they reach the visibility timeout. And by default, this timeout is 1 hour. It means that your pending task will be executed again in 1 hour.

If you set this value to 30 seconds, you'll see that your task will get executed again within 30 seconds.

It might be tempting to decrease this visibility timeout and keep a very low value but bear in mind that it'll apply for every tasks, not only the crashed ones. If you have a task that takes more than 1 hour to execute, it'll be automatically rescheduled on another worker. That's why it's important to keep it quite high, especially if we have long tasks to run.


François Voron Logo
Full-stack web developer and data scientist, I've a proven track record working in SaaS industry, with a special focus on Python backends and REST API.


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