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Doc: Add Callbacks Section to Logging & Monitoring (#18842)
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Airflow users often ask for an easy way to monitor the success or failure of tasks and/or DAGs. The use of callbacks, such as on_success_callback, helps users monitor DAG runs in an easily configurable way.

This document provides an overview of available callbacks, linked to the relevant section in the Tasks document. It also provides a simple example of calling a function on any task failure in the DAG, as well as a separate function that is called upon the success of the last task in the DAG.
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81 changes: 81 additions & 0 deletions docs/apache-airflow/logging-monitoring/callbacks.rst
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.. Licensed to the Apache Software Foundation (ASF) under one
or more contributor license agreements. See the NOTICE file
distributed with this work for additional information
regarding copyright ownership. The ASF licenses this file
to you under the Apache License, Version 2.0 (the
"License"); you may not use this file except in compliance
with the License. You may obtain a copy of the License at
.. http://www.apache.org/licenses/LICENSE-2.0
.. Unless required by applicable law or agreed to in writing,
software distributed under the License is distributed on an
"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
KIND, either express or implied. See the License for the
specific language governing permissions and limitations
under the License.
Callbacks
=========

A valuable component of logging and monitoring is the use of task callbacks to act upon changes in state of a given task, or across all tasks in a given DAG.
For example, you may wish to alert when certain tasks have failed, or have the last task in your DAG invoke a callback when it succeeds.

.. note::

Callback functions are only invoked when the task state changes due to execution by a worker.
As such, task changes set by the command line interface (:doc:`CLI <../usage-cli>`) or user interface (:doc:`UI <../ui>`) do not
execute callback functions.

Callback Types
--------------

There are four types of task events that can trigger a callback:

=========================================== ================================================================
Name Description
=========================================== ================================================================
``on_success_callback`` Invoked when the task :ref:`succeeds <concepts:task-instances>`
``on_failure_callback`` Invoked when the task :ref:`fails <concepts:task-instances>`
``sla_miss_callback`` Invoked when a task misses its defined :ref:`SLA <concepts:slas>`
``on_retry_callback`` Invoked when the task is :ref:`up for retry <concepts:task-instances>`
=========================================== ================================================================


Example
-------

In the following example, failures in any task call the ``task_failure_alert`` function, and success in the last task calls the ``dag_success_alert`` function:

.. code-block:: python
from datetime import datetime, timedelta
from airflow import DAG
from airflow.operators.dummy import DummyOperator
def task_failure_alert(context):
print(f"Task has failed, task_instance_key_str: {context['task_instance_key_str']}")
def dag_success_alert(context):
print(f"DAG has succeeded, run_id: {context['run_id']}")
with DAG(
dag_id="example_callback",
schedule_interval=None,
start_date=datetime(2021, 1, 1),
dagrun_timeout=timedelta(minutes=60),
catchup=False,
on_success_callback=None,
on_failure_callback=task_failure_alert,
tags=["example"],
) as dag:
task1 = DummyOperator(task_id="task1")
task2 = DummyOperator(task_id="task2")
task3 = DummyOperator(task_id="task3", on_success_callback=dag_success_alert)
task1 >> task2 >> task3
1 change: 1 addition & 0 deletions docs/apache-airflow/logging-monitoring/index.rst
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Expand Up @@ -31,6 +31,7 @@ In addition to the standard logging and metrics capabilities, Airflow supports t
logging-architecture
logging-tasks
metrics
callbacks

check-health
errors
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