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Description
Hi Team,
We are getting below error Logs while running the Apache Airflow On AWS EKS .
All the Pods(Tasks) are in completed state but not removed by Airflow. I had to do manual restart of scheduler it everything works for 2-3 days. Then again all the tasks are stuck .
ERROR LOGS
[2020-11-10 07:00:07,752] {{kubernetes_executor.py:447}} ERROR - Error while health checking kube watcher process. Process died for unknown reasons
[2020-11-10 07:00:07,765] {{kubernetes_executor.py:351}} INFO - Event: and now my watch begins starting at resource_version: 107544455
[2020-11-10 07:00:07,782] {{kubernetes_executor.py:342}} ERROR - Unknown error in KubernetesJobWatcher. Failing
Traceback (most recent call last):
File "/usr/local/lib/python3.7/site-packages/airflow/contrib/executors/kubernetes_executor.py", line 340, in run
self.worker_uuid, self.kube_config)
File "/usr/local/lib/python3.7/site-packages/airflow/contrib/executors/kubernetes_executor.py", line 364, in _run
**kwargs):
File "/usr/local/lib/python3.7/site-packages/kubernetes/watch/watch.py", line 177, in stream
status=obj['code'], reason=reason)
kubernetes.client.exceptions.ApiException: (410)
Reason: Gone: too old resource version: 107544455 (108550177)
Process KubernetesJobWatcher-135237:
Traceback (most recent call last):
File "/usr/local/lib/python3.7/multiprocessing/process.py", line 297, in _bootstrap
self.run()
File "/usr/local/lib/python3.7/site-packages/airflow/contrib/executors/kubernetes_executor.py", line 340, in run
self.worker_uuid, self.kube_config)
File "/usr/local/lib/python3.7/site-packages/airflow/contrib/executors/kubernetes_executor.py", line 364, in _run
**kwargs):
File "/usr/local/lib/python3.7/site-packages/kubernetes/watch/watch.py", line 177, in stream
status=obj['code'], reason=reason)
kubernetes.client.exceptions.ApiException: (410)
Reason: Gone: too old resource version: 107544455 (108550177)
AIRFLOW_VERSION=1.10.9
ENVIRONMENT: QA| PROD
Docker Image : python:3.7-slim-buster
Please let us know if you require any more information and how we can resolve this issue . We have also tried to upgrade the AIRFLOW version to 1.10.10 but no luck.