Usuychik opened a new issue, #59602:
URL: https://github.com/apache/airflow/issues/59602
### Apache Airflow version
3.1.5
### If "Other Airflow 3 version" selected, which one?
_No response_
### What happened?
We have Airflow 3.1.5 deployed in kubernetes using official helm. Configured
remote logging and celery workers autoscaling:
`workers:
# Number of airflow celery workers in StatefulSet
replicas: 1
resources:
requests:
cpu: 1
memory: 9Gi
persistence:
# Enable persistent volumes
enabled: true
# Volume size for worker StatefulSet
size: 50Gi
keda:
enabled: true
cooldownPeriod: 600
minReplicaCount: 1
maxReplicaCount: 10`
`config:
logging:
remote_logging: True
delete_local_logs: True
remote_log_conn_id: airflow-logs
remote_base_log_folder: s3://yyyyyy/xxxxx`
And when we try yo check logs for failed dags it shows error like this:
`Log message source details sources=["Could not read served logs:
HTTPConnectionPool(host='airflow-worker-2.airflow-worker.xxxx.svc.cluster.local',
port=8793): Max retries exceeded with url:
/log/dag_id=xxxx/run_id=manual__xxx/task_id=yyy/map_index=25/attempt=8.log
(Caused by
NameResolutionError(\"HTTPConnection(host='airflow-worker-2.airflow-worker.xxxx.svc.cluster.local',
port=8793): Failed to resolve
'airflow-worker-2.airflow-worker.airflow-ai.svc.cluster.local' ([Errno -2] Name
or service not known)\"))"]`
In general there are no such service at all. There are only
airflow-worker.xxxx.svc.cluster.local
### What you think should happen instead?
_No response_
### How to reproduce
Airflow 3.1.5 deployed in kubernetes using official helm. Configured remote
logging and celery workers autoscaling. Try to run multiple dags so keda will
scale up and than scale down. DAGs should fail somehow at that time.
### Operating System
gcloud k8s ubuntu image
### Versions of Apache Airflow Providers
_No response_
### Deployment
Official Apache Airflow Helm Chart
### Deployment details
_No response_
### Anything else?
_No response_
### Are you willing to submit PR?
- [ ] 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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