Taragolis commented on issue #34339:
URL: https://github.com/apache/airflow/issues/34339#issuecomment-1718328867

   > Ah, yeah, in that case, then no - it's run inside a docker container, so 
effectively completely independent from the airflow process.
   
   About timeouts, it seems a bit suspicious when 200 dags can't be processed 
in reasonable time, so I guess this some dynamic DAGs, which created from 
single python file.
   
   The might be a good reason why some bad things happen, just because Airflow 
could decide that DAG might be deleted. I'm not sure in this case it is a bug 
or it's "by design". Some links which might improve your DAG parsing time
   
   - [Fine tuning your scheduler 
performance](https://airflow.apache.org/docs/apache-airflow/stable/administration-and-deployment/scheduler.html#fine-tuning-your-scheduler-performance)
   - [How to control DAG file parsing timeout for different DAG 
files?](https://airflow.apache.org/docs/apache-airflow/stable/faq.html#how-to-control-dag-file-parsing-timeout-for-different-dag-files)
   - [Dynamic DAG 
Generation](https://airflow.apache.org/docs/apache-airflow/stable/best-practices.html#dynamic-dag-generation)
   - [Optimizing DAG parsing delays during 
execution](https://airflow.apache.org/docs/apache-airflow/stable/howto/dynamic-dag-generation.html#optimizing-dag-parsing-delays-during-execution)
   - [DAG File 
Processing](https://airflow.apache.org/docs/apache-airflow/stable/authoring-and-scheduling/dagfile-processing.html)
 see standalone DAG Processor and [`airflow dag-processor` 
cli](https://airflow.apache.org/docs/apache-airflow/stable/cli-and-env-variables-ref.html#dag-processor)
   - 
[.airflowignore](https://airflow.apache.org/docs/apache-airflow/stable/core-concepts/dags.html#airflowignore)
   
   
   <details>
     <summary>Just out of my curiosity</summary>
     
   The flow something like: AIrflow -> CeleryExecutor -> BashOperator -> Docker 
-> Prefect ?
     
   </details>


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