notatallshaw-work opened a new issue, #26566: URL: https://github.com/apache/airflow/issues/26566
### What do you see as an issue? The [SLA documentation](https://airflow.apache.org/docs/apache-airflow/stable/concepts/tasks.html#slas) currently states the following: > An SLA, or a Service Level Agreement, is an expectation for the maximum time a Task should take. If a task takes longer than this to run However this is not how SLAs currently work in Airflow, the SLA time is calculated from the start of the DAG not from the start of the task. For example if you have a DAG like this the SLA will always trigger after the DAG has started for 5 minutes even though the task never takes 5 minutes to run: ```python import datetime from airflow import DAG from airflow.sensors.time_sensor import TimeSensor from airflow.operators.python import PythonOperator with DAG(dag_id="my_dag", schedule_interval="0 0 * * *") as dag: wait_time_mins = TimeSensor(target_time=datetime.time(minute=10)) run_fast = PythonOperator( python_callable=lambda *a, **kwargs: True, sla=datetime.timedelta(minutes=5), ) run_fast.set_upstream(wait_time_mins) ``` ### Solving the problem Update the docs to explain how SLAs work in reality. ### Anything else _No response_ ### Are you willing to submit PR? - [X] 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]
