Merge pull request #14 from airflow-laminar/tkp/init

update docs

README.md

@@ -13,8 +13,27 @@ This library provides a configuration-driven way of generating [supervisor](http
 
 ## How To: Use in Airflow
 
-Docs coming soon!
+`airflow-supervisor` can be installed in your airflow server environment and imported in your dag files. It provides two convenient top level DAG subclasses:
 
-## How To: Use as a standalone supervisord frontend
+- `SupervisorLocal`: creates a DAG representing a local supervisor instance running on the airflow worker node (underlying task will use `PythonOperator` and `BashOperator` to communicate between airflow and supervisor)
+- `SupervisorRemote`: creates a DAG representing a remote supervisor instance running on another machine (underlying tasks will use `SSHOperator` to communicate between airflow and supervisor)
+
+We expose DAGs composed of a variety of tasks and sensors, which are exposed as a discrete pipeline of steps:
+1. Setup `supervisord` configuration
+2. Start the `supervisord` daemon
+3. Start the supervised programs with `supervisorctl`
+4. Start sensors to query the programs' state via [supervisor's XML-RPC API](http://supervisord.org/api.html)
+5. Evaluate and take action according to the program's state changes
+6. Restart programs if necessary
+7. Tear down the sensors from (4)
+8. Stop the supervised programs from (3)
+9. Stop the `supervisord` daemon from (2)
+10. Remove configuration from (1)
+
+This setup provides maximal configureability with a minimal requirements on the machine (for example, no requirements on an existing `supervisord` daemon via e.g. `systemd`). It also lets you hook your own tasks into any step of the process. For example, if we detect a process has died in step (5), you could configure your own task to take some custom action before/instead of the default restart of step 6.
+
+More docs and code examples coming soon!
+
+## How To: Use as a supervisord configuration frontend
 
 This library can be used outside airflow as a generic supervisord configuration framework, with the static typing benefits that entails. For an example, look at the [hydra configuration test](./airflow_supervisor/tests/hydra/test_hydra.py). This example generates a supervisor configuration file by composing independent hydra configs.