tirkarthi commented on issue #55768: URL: https://github.com/apache/airflow/issues/55768#issuecomment-3443725120
We are also experiencing high memory usage for api-server that grows over time reaching the memory limit assigned to the pod. The server uses `airflow api-server` with default configurations on Kubernetes. The scheduler uses KubernetesExecutor and we didn't see noticeable issues. I tried locally using memray with below command using 500 dags. The server started with 25MB and then went to 95MB, 175MB to stay there. Here is the command that gives a live view of the memory usage in case someone wants to run it a different setup. ``` PYTHONMALLOC=malloc memray run --live -m uvicorn airflow.api_fastapi.main:app --workers 1 --port 8000 ``` <img width="1850" height="1048" alt="Image" src="https://github.com/user-attachments/assets/98b4d51d-e222-4b5c-a277-e0f7f51a609a"; /> -- 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]
