potiuk commented on code in PR #28300:
URL: https://github.com/apache/airflow/pull/28300#discussion_r1046552210


##########
docs/apache-airflow/index.rst:
##########
@@ -79,6 +79,49 @@ seen running over time:
 Each column represents one DAG run. These are two of the most used views in 
Airflow, but there are several
 other views which allow you to deep dive into the state of your workflows.
 
+Customizing Airflow
+===================
+
+There are a number of ways to extend the capabilities of Apache Airflow. Some 
common methods
+for extending Airflow include:
+
+* Writing :doc:`Custom Operators <howto/custom-operator>`_ : Operators are the 
building blocks of DAGs in
+  Airflow, and can be used to perform specific tasks within a DAG. By writing 
custom operators,
+  you can add new functionality to Airflow, such as the ability to connect to 
and interact
+  with external services, or to perform complex data transformations.
+
+* Writing :doc:`Custom Decorators <howto/create-custom-decorator>`_ : Custom 
decorators are a way to
+  extend the functionality of the Airflow ``@task`` decorator. By writing 
custom decorators,
+  you can add new functionality to Airflow, such as the ability to connect to 
and interact
+  with external services, or to perform complex data transformations.
+
+* Creating custom :doc:`plugins`: Airflow plugins are extensions to the core 
system that provide additional
+  features and functionality. By creating custom plugins, you can add new 
capabilities to Airflow,
+  such as adding custom UI components, creating custom macros, creating your 
own TimeTables,
+  adding Operator Extra Links, Listeners.
+
+* Writing custom :doc:`provider packages <apache-airflow-providers:index>`: 
Providers are the components
+  of Airflow that are responsible for connecting to and interacting with 
external services. By writing
+  custom providers, you can add support for new types of external services, 
such as databases or
+  cloud services, to Airflow.
+
+With all the above methods, you can use the :doc:`public-airflow-api` to write 
your
+custom Python code to interact with Airflow.
+
+However, you can also extend Airflow without directly integrating your Python 
code - via the
+:doc:`stable-rest-api-ref` and the :doc:`stable-cli-ref`. These methods allow 
you to interact with
+Airflow as an external system:
+
+Particularly, the doc:`stable-rest-api-ref` of Apache Airflow provides a 
number of methods for programmatic

Review Comment:
   Removed altogether.



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