kaxil commented on a change in pull request #10998:
URL: https://github.com/apache/airflow/pull/10998#discussion_r490628079



##########
File path: README.md
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@@ -116,31 +117,42 @@ pip install apache-airflow[postgres,google]==1.10.12 \
 
 ## Official source code
 
-Apache Airflow is an [Apache Software Foundation](http://www.apache.org) (ASF) 
project, and our official source code releases:
+Apache Airflow is an [Apache Software Foundation](http://www.apache.org) (ASF) 
project,
+and our official source code releases:
 
 - Follow the [ASF Release 
Policy](http://www.apache.org/legal/release-policy.html)
 - Can be downloaded from [the ASF Distribution 
Directory](https://downloads.apache.org)
 - Are cryptographically signed by the release manager
-- Are officially voted on by the PMC members during the [Release Approval 
Process](http://www.apache.org/legal/release-policy.html#release-approval)
+- Are officially voted on by the PMC members during the
+  [Release Approval 
Process](http://www.apache.org/legal/release-policy.html#release-approval)
 
-Following the ASF rules, the source packages released must be sufficient for a 
user to build and test the release provided they have access to the appropriate 
platform and tools.
+Following the ASF rules, the source packages released must be sufficient for a 
user to build and test the
+release provided they have access to the appropriate platform and tools.
 
-Other ways of retrieving source code are "convenience" methods. For example:
+## Convenience packages
 
-- Tagging in GitHub to mark the git project sources that were used to generate 
official source packages
+There are other ways of installing and using Airflow. Those are "convenience" 
methods - they are
+not "official releases" as stated by the `ASF Release Policy`, but they can be 
used by the users
+who do not want to build the software themselves.
 
-We also have binary "convenience" packages:
+Those are - in the order of most common ways people install Airflow:
 
-- PyPI releases to install Airflow using standard python tools
-- Docker Images published in the [Apache Airflow 
DockerHub](https://hub.docker.com/repository/docker/apache/airflow).
+- [PyPI releases](https://pypi.org/project/apache-airflow/) to install Airflow 
using standard `pip` tool
+- [Docker Images](https://hub.docker.com/repository/docker/apache/airflow) to 
install airflow via
+  `docker` tool, use them in Kubernetes, Helm Charts, `docker-compose`, 
`docker swarm` etc. You can
+  read more about using, customising, and extending the images in the
+  [Latest 
docs](https://airflow.readthedocs.io/en/latest/production-deployment.html), and
+  learn details on the internals in the [IMAGES.rst](IMAGES.rst) document.
+- [Tags in GitHub](https://github.com/apache/airflow/tags) to retrieve the git 
project sources that
+  were used to generate official source packages via git
 
-These artifacts are not official releases, but they are built using officially 
released sources.
-
-> Note: Airflow Summit 2020's ["Production Docker Image 
talk"](https://youtu.be/wDr3Y7q2XoI) explains context, architecture and 
customization/extension methods.
+All those artifacts are not official releases, but they are prepared using 
officially released sources.
+Some of those artifacts are "development" or "pre-release" ones, and they are 
clearly marked as such
+following the ASF Policy.
 
 ## Project Focus
 
-Airflow works best with workflows that are mostly static and slowly changing. 
When the structure is similar from one run to the next, it allows for clarity 
around unit of work and continuity. Other similar projects include 
[Luigi](https://github.com/spotify/luigi), [Oozie](http://oozie.apache.org/) 
and [Azkaban](https://azkaban.github.io/).
+Airflow works best with workflows that are mostly static and slowly changing. 
When the structure is similarfrom one run to the next, it allows for clarity 
around unit of work and continuity. Other similar projects include 
[Luigi](https://github.com/spotify/luigi), [Oozie](http://oozie.apache.org/) 
and [Azkaban](https://azkaban.github.io/).

Review comment:
       ```suggestion
   Airflow works best with workflows that are mostly static and slowly 
changing. When the structure is similar from one run to the next, it allows for 
clarity around the unit of work and continuity. Other similar projects include 
[Luigi](https://github.com/spotify/luigi), [Oozie](http://oozie.apache.org/) 
and [Azkaban](https://azkaban.github.io/).
   ```




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