chenyair opened a new issue, #35792:
URL: https://github.com/apache/airflow/issues/35792

   ### Apache Airflow version
   
   Other Airflow 2 version (please specify below)
   
   ### What happened
   
   I am using Airflow 2.5.2 but this issue applies to all versions of Airflow.
   When I'm creating a task and I don't have enough quota for the Airflow 
executor to create the kubernetes api returns an ApiException with the status 
code 403 that says `Reason: Forbidden` with the message: `Pods ... is 
forbidden: exceeded quota: compute-resources, ...`. The Kubernetes executor 
puts the task back in the queue because the status code is not 400 or 422, from 
`kubernetes_executor.py`:
   ```python
   # These codes indicate something is wrong with pod definition; otherwise we 
assume pod
   # definition is ok, and that retrying may work
   if e.status in (400, 422):
   ```
   The problem is that it tries excessively to run the task again and again and 
it spams the Kubernetes API which then makes kyverno write a lot of obejcts to 
etcd.
   
   ### What you think should happen instead
   
   I want to be able to control the amount of times the scheduler re-queues a 
job and the timeout between each time it tires to re-run the task if it was 
re-queued.
   
   ### How to reproduce
   
   Run an Airflow task with insufficient memory and cpu in the ACRQ
   
   ### Operating System
   
   Red Hat Enterprise Linux 8.5 (Ootpa)
   
   ### Versions of Apache Airflow Providers
   
   _No response_
   
   ### Deployment
   
   Other 3rd-party Helm chart
   
   ### Deployment details
   
   _No response_
   
   ### Anything else
   
   _No response_
   
   ### Are you willing to submit PR?
   
   - [X] Yes I am willing to submit a PR!
   
   ### Code of Conduct
   
   - [X] I agree to follow this project's [Code of 
Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)
   


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