Add notes about Virtualenvs preventing the need for custom images

docs/apache-airflow/howto/docker-compose/index.rst

@@ -294,6 +294,13 @@ to rebuild the images on-the-fly when you run other ``docker compose`` commands.
 Examples of how you can extend the image with custom providers, python packages,
 apt packages and more can be found in :doc:`Building the image <docker-stack:build>`.
 
+.. note::
+   Creating custom images means that you need to maintain also a level of automation as you need to re-create the images
+   when either the packages you want to install or Airflow is upgraded. Please do not forget about keeping these scripts.
+   Also keep in mind, that in cases when you run pure Python tasks, you can use the
+   `Python Virtualenv functions <_howto/operator:PythonVirtualenvOperator>`_ which will
+   dynamically source and install python dependencies during runtime. With Airflow 2.8.0 Virtualenvs can also be cached.
+
 Special case - adding dependencies via requirements.txt file
 ============================================================
 

docs/docker-stack/build.rst

@@ -66,6 +66,13 @@ as ``root`` will fail with an appropriate error message.
    downgrade or upgrade of airflow. If you upgrade airflow base image, you should also update the version
    to match the new version of airflow.
 
+.. note::
+   Creating custom images means that you need to maintain also a level of automation as you need to re-create the images
+   when either the packages you want to install or Airflow is upgraded. Please do not forget about keeping these scripts.
+   Also keep in mind, that in cases when you run pure Python tasks, you can use the
+   `Python Virtualenv functions <https://airflow.apache.org/docs/apache-airflow/stable/howto/operator/python.html#pythonvirtualenvoperator>`_
+   which will dynamically source and install python dependencies during runtime. With Airflow 2.8.0 Virtualenvs can also be cached.
+
 .. exampleinclude:: docker-examples/extending/add-pypi-packages/Dockerfile
     :language: Dockerfile
     :start-after: [START Dockerfile]

docs/helm-chart/quick-start.rst

@@ -91,6 +91,13 @@ The Apache Airflow community, releases Docker Images which are ``reference image
 However, when you try it out you want to add your own DAGs, custom dependencies,
 packages, or even custom providers.
 
+.. note::
+   Creating custom images means that you need to maintain also a level of automation as you need to re-create the images
+   when either the packages you want to install or Airflow is upgraded. Please do not forget about keeping these scripts.
+   Also keep in mind, that in cases when you run pure Python tasks, you can use the
+   `Python Virtualenv functions <https://airflow.apache.org/docs/apache-airflow/stable/howto/operator/python.html#pythonvirtualenvoperator>`_
+   which will dynamically source and install python dependencies during runtime. With Airflow 2.8.0 Virtualenvs can also be cached.
+
 The best way to achieve it, is to build your own, custom image.
 
 Adding DAGs to your image