Doc on how to implement a custom Watcher action

This documentation describes step-by-step the process for implementing
a new action in Watcher.

Change-Id: I978b81cdf9ac6dcf43eb3ecbb79ab64ae4fd6f72
Closes-Bug: #1534639

doc/source/dev/plugin/action-plugin.rst

@@ -0,0 +1,159 @@
+..
+      Except where otherwise noted, this document is licensed under Creative
+      Commons Attribution 3.0 License.  You can view the license at:
+
+          https://creativecommons.org/licenses/by/3.0/
+
+==================
+Build a new action
+==================
+
+Watcher Applier has an external :ref:`action <action_definition>` plugin
+interface which gives anyone the ability to integrate an external
+:ref:`action <action_definition>` in order to extend the initial set of actions
+Watcher provides.
+
+This section gives some guidelines on how to implement and integrate custom
+actions with Watcher.
+
+
+Creating a new plugin
+=====================
+
+First of all you have to extend the base :py:class:`BaseAction` class which
+defines a set of abstract methods and/or properties that you will have to
+implement:
+
+ - The :py:attr:`~.BaseAction.schema` is an abstract property that you have to
+   implement. This is the first function to be called by the
+   :ref:`applier <watcher_applier_definition>` before any further processing
+   and its role is to validate the input parameters that were provided to it.
+ - The :py:meth:`~.BaseAction.precondition` is called before the execution of
+   an action. This method is a hook that can be used to perform some
+   initializations or to make some more advanced validation on its input
+   parameters. If you wish to block the execution based on this factor, you
+   simply have to ``raise`` an exception.
+ - The :py:meth:`~.BaseAction.postcondition` is called after the execution of
+   an action. As this function is called regardless of whether an action
+   succeeded or not, this can prove itself useful to perform cleanup
+   operations.
+ - The :py:meth:`~.BaseAction.execute` is the main component of an action.
+   This is where you should implement the logic of your action.
+ - The :py:meth:`~.BaseAction.revert` allows you to roll back the targeted
+   resource to its original state following a faulty execution. Indeed, this
+   method is called by the workflow engine whenever an action raises an
+   exception.
+
+Here is an example showing how you can write a plugin called ``DummyAction``:
+
+.. code-block:: python
+
+    # Filepath = <PROJECT_DIR>/thirdparty/dummy.py
+    # Import path = thirdparty.dummy
+    from watcher.applier.actions import base
+
+
+    class DummyAction(baseBaseAction):
+
+        @property
+        def schema(self):
+            return Schema({})
+
+        def execute(self):
+            # Does nothing
+            pass  # Only returning False is considered as a failure
+
+        def revert(self):
+            # Does nothing
+            pass
+
+        def precondition(self):
+            # No pre-checks are done here
+            pass
+
+        def postcondition(self):
+            # Nothing done here
+            pass
+
+
+This implementation is the most basic one. So if you want to have more advanced
+examples, have a look at the implementation of the actions already provided
+by Watcher like.
+To get a better understanding on how to implement a more advanced action,
+have a look at the :py:class:`~watcher.applier.actions.migration.Migrate`
+class.
+
+Abstract Plugin Class
+=====================
+
+Here below is the abstract ``BaseAction`` class that every single action
+should implement:
+
+.. autoclass:: watcher.applier.actions.base.BaseAction
+    :members:
+    :noindex:
+
+    .. py:attribute:: schema
+
+        Defines a Schema that the input parameters shall comply to
+
+        :returns: A schema declaring the input parameters this action should be
+                  provided along with their respective constraints
+                  (e.g. type, value range, ...)
+        :rtype: :py:class:`voluptuous.Schema` instance
+
+
+Register a new entry point
+==========================
+
+In order for the Watcher Applier to load your new action, the
+action must be registered as a named entry point under the
+``watcher_actions`` entry point of your ``setup.py`` file. If you are using
+pbr_, this entry point should be placed in your ``setup.cfg`` file.
+
+The name you give to your entry point has to be unique.
+
+Here below is how you would proceed to register ``DummyAction`` using pbr_:
+
+.. code-block:: ini
+
+    [entry_points]
+    watcher_actions =
+        dummy = thirdparty.dummy:DummyAction
+
+.. _pbr: http://docs.openstack.org/developer/pbr/
+
+
+Using action plugins
+====================
+
+The Watcher Applier service will automatically discover any installed plugins
+when it is restarted. If a Python package containing a custom plugin is
+installed within the same environment as Watcher, Watcher will automatically
+make that plugin available for use.
+
+At this point, you can use your new action plugin in your :ref:`strategy plugin
+<implement_strategy_plugin>` if you reference it via the use of the
+:py:meth:`~.Solution.add_action` method:
+
+.. code-block:: python
+
+    # [...]
+    self.solution.add_action(
+        action_type="dummy",  # Name of the entry point we registered earlier
+        applies_to="",
+        input_parameters={})
+
+By doing so, your action will be saved within the Watcher Database, ready to be
+processed by the planner for creating an action plan which can then be executed
+by the Watcher Applier via its workflow engine.
+
+
+Scheduling of an action plugin
+==============================
+
+Watcher provides a basic built-in :ref:`planner <watcher_planner_definition>`
+which is only able to process the Watcher built-in actions. Therefore, you will
+either have to use an existing third-party planner or :ref:`implement another
+planner <implement_planner_plugin>` that will be able to take into account your
+new action plugin.

doc/source/dev/strategy-plugin.rst

@@ -4,6 +4,8 @@
 
           https://creativecommons.org/licenses/by/3.0/
 
+.. _implement_strategy_plugin:
+
 =================================
 Build a new optimization strategy
 =================================

doc/source/index.rst

@@ -72,6 +72,7 @@ Plugins
 
   dev/strategy-plugin
   dev/plugins
+  dev/plugin/action-plugin
 
 
 Admin Guide

watcher/applier/actions/base.py

@@ -58,22 +58,57 @@ class BaseAction(object):
 
     @abc.abstractmethod
     def execute(self):
+        """Executes the main logic of the action
+
+        This method can be used to perform an action on a given set of input
+        parameters to accomplish some type of operation. This operation may
+        return a boolean value as a result of its execution. If False, this
+        will be considered as an error and will then trigger the reverting of
+        the actions.
+
+        :returns: A flag indicating whether or not the action succeeded
+        :rtype: bool
+        """
         raise NotImplementedError()
 
     @abc.abstractmethod
     def revert(self):
+        """Revert this action
+
+        This method should rollback the resource to its initial state in the
+        event of a faulty execution. This happens when the action raised an
+        exception during its :py:meth:`~.BaseAction.execute`.
+        """
         raise NotImplementedError()
 
     @abc.abstractmethod
     def precondition(self):
+        """Hook: called before the execution of an action
+
+        This method can be used to perform some initializations or to make
+        some more advanced validation on its input parameters. So if you wish
+        to block its execution based on this factor, `raise` the related
+        exception.
+        """
         raise NotImplementedError()
 
     @abc.abstractmethod
     def postcondition(self):
+        """Hook: called after the execution of an action
+
+        This function is called regardless of whether an action succeded or
+        not. So you can use it to perform cleanup operations.
+        """
         raise NotImplementedError()
 
     @abc.abstractproperty
     def schema(self):
+        """Defines a Schema that the input parameters shall comply to
+
+        :returns: A schema declaring the input parameters this action should be
+                  provided along with their respective constraints
+        :rtype: :py:class:`voluptuous.Schema` instance
+        """
         raise NotImplementedError()
 
     def validate_parameters(self):