wolfier opened a new issue, #56196:
URL: https://github.com/apache/airflow/issues/56196

   ### Apache Airflow version
   
   3.1.0
   
   ### If "Other Airflow 2 version" selected, which one?
   
   _No response_
   
   ### What happened?
   
   `on_failure_callback` of a task with remaining retry attempts executed when 
the worker executing the task terminated abruptly. This is not expected because 
the task has retry attempts.
   
   ### What you think should happen instead?
   
   When a task with remaining retries fails, the `on_retry_callback` should be 
executed and **NOT** `on_failure_callback`.
   
   ### How to reproduce
   
   1. Execute a long running task
   2. Terminate the worker 
   3. Allow the scheduler to identify the task instance was killed externally
   4. Examine dag processor logs for execution of the 
task's`on_failure_callback`
   
   ### Operating System
   
   Debian
   
   ### Versions of Apache Airflow Providers
   
   _No response_
   
   ### Deployment
   
   Astronomer
   
   ### Deployment details
   
   _No response_
   
   ### Anything else?
   
   When a task with either `on_failure_callback` or `on_retry_callback` is 
killed externally, a 
[TaskCallbackRequest](https://github.com/apache/airflow/blob/3.1.0/airflow-core/src/airflow/jobs/scheduler_job_runner.py#L930C31-L942)
 is sent. The request does not have `task_callback_type` set and defaults to 
`None`. The callback request is considered a [failure 
callback](https://github.com/apache/airflow/blob/3.1.0/airflow-core/src/airflow/callbacks/callback_requests.py#L69-L72)
 when `task_callback_type` is `None`. 
   
   Since the `task_callback_type` is `None`, the task's `on_failure_callback` 
is queued for execution when the dag processor processes the callback request.
   
   ```python
       if request.task_callback_type is TaskInstanceState.UP_FOR_RETRY:
           callbacks = task.on_retry_callback
       else:
           callbacks = task.on_failure_callback
   ```
   
   The `TaskCallbackRequest` should set `task_callback_type` according to 
whether the task is eligible to retry. If it is, the task should set 
`task_callback_type` to `TaskInstanceState.UP_FOR_RETRY` otherwise 
`TaskInstanceState.FAILED` is an appropriate mode.
   
   ```python
       request = TaskCallbackRequest(
           filepath=ti.dag_model.relative_fileloc,
           bundle_name=ti.dag_version.bundle_name,
           bundle_version=ti.dag_version.bundle_version,
           ti=ti,
           msg=msg,
           context_from_server=TIRunContext(
               dag_run=DRDataModel.model_validate(ti.dag_run, 
from_attributes=True),
               max_tries=ti.max_tries,
               variables=[],
               connections=[],
               xcom_keys_to_clear=[],
           ),
           task_callback_type=(
               TaskInstanceState.UP_FOR_RETRY
               if ti.is_eligible_to_retry() else
               TaskInstanceState.FAILED
           ),
       )
   ```
   
   ### 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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