Issue 1:
Checklist

I have checked the issues list

for similar or identical feature requests.

I have checked the pull requests list

for existing proposed implementations of this feature.

I have checked the commit log

to find out if the if the same feature was already implemented in the

master branch.

I have included all related issues and possible duplicate issues

in this issue (If there are none, check this box anyway).

Related Issues and Possible Duplicates

Related Issues

None

Possible Duplicates

None

Brief Summary

The main idea is to allow settings some flag that will specify the number of tasks the worker should execute before exiting.

The reason to do so is to able to scale celery workers over Kubernetes in a reasonable matter.

You would create a pod with a worker set to consume 1 message and then exiting, in Kubernetes you will create a job for each message in the broker queue that will start that said pod.

The current way to do something like that is kinda ugly since the auto scaler of Kubernetes might decide to scale down a worker that is currently running and in long-running tasks that can be problematic

Design

Architectural Considerations

None

Proposed Behavior

Proposed UI/UX

Diagrams

N/A

Alternatives

None

Issue 2:
Checklist

I have verified that the issue exists against the master branch of Celery.

This has already been asked to the discussion group first.

I have read the relevant section in the

contribution guide

on reporting bugs.

I have checked the issues list

for similar or identical bug reports.

I have checked the pull requests list

for existing proposed fixes.

I have checked the commit log

to find out if the bug was already fixed in the master branch.

I have included all related issues and possible duplicate issues

in this issue (If there are none, check this box anyway).

Mandatory Debugging Information

I have included the output of celery -A proj report in the issue.

(if you are not able to do this, then at least specify the Celery

version affected).

I have verified that the issue exists against the master branch of Celery.

I have included the contents of pip freeze in the issue.

I have included all the versions of all the external dependencies required

to reproduce this bug.

Optional Debugging Information

I have tried reproducing the issue on more than one Python version

and/or implementation.

I have tried reproducing the issue on more than one message broker and/or

result backend.

I have tried reproducing the issue on more than one version of the message

broker and/or result backend.

I have tried reproducing the issue on more than one operating system.

I have tried reproducing the issue on more than one workers pool.

I have tried reproducing the issue with autoscaling, retries,

ETA/Countdown & rate limits disabled.

I have tried reproducing the issue after downgrading

and/or upgrading Celery and its dependencies.

Related Issues and Possible Duplicates

Related Issues

None

Possible Duplicates

None

Environment & Settings

Celery version:

celery report Output:

Steps to Reproduce

Required Dependencies

Minimal Python Version: N/A or Unknown

Minimal Celery Version: N/A or Unknown

Minimal Kombu Version: N/A or Unknown

Minimal Broker Version: N/A or Unknown

Minimal Result Backend Version: N/A or Unknown

Minimal OS and/or Kernel Version: N/A or Unknown

Minimal Broker Client Version: N/A or Unknown

Minimal Result Backend Client Version: N/A or Unknown

Python Packages

pip freeze Output:

Other Dependencies

N/A

Minimally Reproducible Test Case

Expected Behavior

Actual Behavior

Hi,

We have an issue when we create a python exe file for our app. The app run one celery worker but the exe run infinite number of workers.

It's a blocking point for us