noamst-monday opened a new issue, #49001: URL: https://github.com/apache/airflow/issues/49001
### Official Helm Chart version 1.16.0 (latest released) ### Apache Airflow version 2.10.5 ### Kubernetes Version 1.30.10 ### Helm Chart configuration Hello! When using [multiple executors](https://airflow.apache.org/docs/apache-airflow/stable/core-concepts/executor/index.html#using-multiple-executors-concurrently), tasks are routed to the appropriate executor using the `executor` attribute. However, the KEDA query in the chart uses the `queue` column in the database, which was relevant for the hybrid CeleryKubernetesExecutor. ### Docker Image customizations not relevant ### What happened Celery workers scale up even when the task is configured to use KubernetesExecutor, since its queue attribute is `default`, while its executor attribute is `KubernetesExecutor` ### What you think should happen instead When using the hybrid executor, the query should use the `queue`. Otherwise, the query should use `executor`. ### How to reproduce Deploy Airflow with keda enabled, using multiple executors, with celery being the default: ``` executor: CeleryExecutor,KubernetesExecutor workers: keda: enabled: true ``` Create a DAG to launch multiple tasks using `KubernetesExecutor` with default queue. The KEDA query will cause scale up of celery workers. ### Anything else Thank you and please let me know if any additional details are needed, or if I missed something to address this issue :) ### 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) -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
