airflow tends to zombie tasks that should be successful

[maxgruber19]

system versions: 24.11.0 / 2.9.3

we observed some issues with airflow running with celery executors setting some tasks to "zombie" which ran successfully. some occasions seem to correlate with 20+ dags submitted at once ( most of them are of @daily schedule) but even in case of one dag running alone it's happening.

we increased the pod memory of scheduler and workers to 8 gi (maybe thats still ways to low?) but its still an issue. I did that according to the recommendation in the error message pasted below.

log of an affected task below, the task should be listed as successfull because all the underlying steps have been completed successfully as well.

That issue rather is more a question / request for airflow experience than a typical issue / bug report

I guess you will need further details to tell us more, so please let me know what logs / stats you need to help me 😄

airflow-worker-default-1.airflow-worker-default.mesh-platform-core.svc.cluster.local 
*** Found logs in s3: 
***   * s3://BUCKETNAME/logs/dag_id=protrans/run_id=manual__2025-04-22T13:12:23.151597+00:00/task_id=load/attempt=1.log.SchedulerJob.log 
[2025-04-22, 15:25:33 CEST] {sched.py:151} ERROR - Detected zombie job: {'full_filepath': '/stackable/app/git/current/stages/int/apps/product-protrans/dags/protrans.py', 'processor_subdir': '/stackable/app/git/.worktrees/181cc3caac63f51937ffdbf7851137d5f0fd0b49/stages/int/apps', 'msg': "{'DAG Id': 'protrans', 'Task Id': 'load', 'Run Id': 'manual__2025-04-22T13:12:23.151597+00:00', 'Hostname': 'airflow-worker-default-1.airflow-worker-default.mesh-platform-core.svc.cluster.local', 'External Executor Id': '87a1cea8-0e6f-47f8-9d0f-bbb6bac1c214'}", 'simple_task_instance': <airflow.models.taskinstance.SimpleTaskInstance object at 0x7fbd99eec760>, 'is_failure_callback': True} (See https://airflow.apache.org/docs/apache-airflow/stable/core-concepts/tasks.html#zombie-undead-tasks)

[adwk67]

Hi @maxgruber19 : we had to increase the memory for airflow 2.10.4 (ok, so not 2.9.3) for our demo, even though the release notes didn't highlight anything that might require this, so OOMs could be a possible cause. And that was the webservers, which was a little unexpected. If this happens regularly enough, you can try and catch it with something like:
kubectl get events -A --watch| grep OOM

[adwk67]

Are you using gitsync to fetch your DAGs, by any chance?

[maxgruber19]

@adwk67 thanks once again, I'll try increasing resources especially for the webservers, will let you know about the outcome

Yes, all dags come via gitsync

[adwk67]

Yes, all dags come via gitsync

Depending on the size/scale of the DAGs, this can cause issues: we have an open issue here. If this seems to be the problem and it can be overcome with the overrides described in that issue, do let me know and we can prioritize that issue accordingly.