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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.
Activity
boring-cyborg commentedon Nov 10, 2020
Thanks for opening your first issue here! Be sure to follow the issue template!
garacio commentedon Nov 12, 2020
Same in bare metal k8s installation
aitflow version 1.10.12
k8s version v1.17.5
gdtroszak commentedon Nov 13, 2020
We're observing the same thing.
Airflow version 1.10.9
k8s API server version v1.15.12
bhavaniravi commentedon Nov 17, 2020
Same issue with airflow 1.10.10
gakhrejah commentedon Nov 17, 2020
Hi All,
Can anybody let me know , how we can resolve this issue . It seems like this is still an open issue with Airflow.
gdtroszak commentedon Nov 17, 2020
This issue seems to outline a workaround. It essentially amounts to downgrading the k8s client to
v11.0.0.potiuk commentedon Nov 17, 2020
@kaxil @ashb -> looks like we should limit the k8s client to <12.0.0 IMHO. WDYT ?
kaxil commentedon Nov 17, 2020
Yup, this will be fixed in 1.10.13. Already fixed in Master by #11974
edikmkoyan commentedon Dec 24, 2020
it isn't fixed in 1.10.13
kaxil commentedon Dec 24, 2020
https://github.com/apache/airflow/blob/1.10.13/setup.py#L313
It is fixed, check the link I posted
edikmkoyan commentedon Feb 15, 2021
I used helmchart to helm install the airflow, didn't used the setup.py anyhow, I guess the docker image used has the wrong version ok the k8s client. I have the issue with the airflow 2.0.1.
kaxil commentedon Feb 17, 2021
setup.py is used when you or the tool you use run
pip install apache-airflow. The docker image seems to have the correct version, check below:itayB commentedon Jan 16, 2022
@kaxil and all other friends - this is something that still happening in v2.2.3.
The installed version is:
Do I still need to downgrade that much?
I see that this limitation has removed recently - will it solve the issue in the upcoming Airflow version?
potiuk commentedon Jan 16, 2022
This issue has long been closed. If you see similar issue (I assume with resource too old), and have some logs. please open a new issue with all the details because it's very likely this is completely unrelated issue.
By specifying "this is something that still happening in v2.2.3" you basically do not tell - what happens, what logs, how often, is this an intermitten issue etc. There is no way we can even attempt to answer your question without knowing all the details.
So if you have similar issue. Please open a new issue and provide all details - or better - if you are not sure if this is an airflow issue at all, open a Github Discussion instead (still provide all the details there - maybe this is a K8S deployment issue that someone can help you solve there.