This change corrects the detected sphinx-linit issue in the existing docs and updates the contributor devstack guide to call out required and advanced. mostly the changes were simple fixes like replacing the configurable default rule with explict literal syntax `term` -> ``term`` some inline Note: comments have been promoted to .. note:: blocks and literal blocks :: have been promoted to .. code-block:: <language> directives. Change-Id: I6320c313d22bf542ad407169e6538dc6acf79901
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System Architecture
This page presents the current technical Architecture of the Watcher system.
Overview
Below you will find a diagram, showing the main components of Watcher:
Components
AMQP Bus
The AMQP message bus handles internal asynchronous communications between the different Watcher components.
Datasource
This component stores the metrics related to the cluster.
It can potentially rely on any appropriate storage system (InfluxDB, OpenTSDB, MongoDB,...) but will probably be more performant when using Time Series Databases which are optimized for handling time series data, which are arrays of numbers indexed by time (a datetime or a datetime range).
Watcher API
This component implements the REST API provided by the Watcher system to the external world.
It enables the Administrator <administrator_definition>
of a
Cluster <cluster_definition>
to control and
monitor the Watcher system via any interaction mechanism connected to
this API:
CLI <archi_watcher_cli_definition>
- Horizon plugin
- Python SDK
You can also read the detailed description of Watcher API.
Watcher Applier
This component is in charge of executing the Action Plan <action_plan_definition>
built by
the Watcher Decision Engine <watcher_decision_engine_definition>
.
Taskflow is the default workflow engine for Watcher.
It connects to the message bus <amqp_bus_definition>
and launches
the Action Plan <action_plan_definition>
whenever a
triggering message is received on a dedicated AMQP queue.
The triggering message contains the Action Plan UUID.
It then gets the detailed information about the Action Plan <action_plan_definition>
from the
Watcher Database <watcher_database_definition>
which contains the list of Actions <action_definition>
to launch.
It then loops on each Action <action_definition>
, gets the associated
class and calls the execute() method of this class. Most of the time,
this method will first request a token to the Keystone API and if it is
allowed, sends a request to the REST API of the OpenStack service which
handles this kind of atomic Action <action_definition>
.
Note that as soon as Watcher Applier <watcher_applier_definition>
starts handling a given Action <action_definition>
from the list, a
notification message is sent on the message bus <amqp_bus_definition>
indicating
that the state of the action has changed to
ONGOING.
If the Action <action_definition>
is successful, the
Watcher Applier <watcher_applier_definition>
sends a notification message on the bus <amqp_bus_definition>
informing the
other components of this.
If the Action <action_definition>
fails, the Watcher Applier <watcher_applier_definition>
tries to rollback to the previous state of the Managed resource <managed_resource_definition>
(i.e. before the command was sent to the underlying OpenStack
service).
In Stein, added a new config option 'action_execution_rule' which is a dict type. Its key field is strategy name and the value is 'ALWAYS' or 'ANY'. 'ALWAYS' means the callback function returns True as usual. 'ANY' means the return depends on the result of previous action execution. The callback returns True if previous action gets failed, and the engine continues to run the next action. If previous action executes success, the callback returns False then the next action will be ignored. For strategies that aren't in 'action_execution_rule', the callback always returns True. Please add the next section in the watcher.conf file if your strategy needs this feature.
[watcher_workflow_engines.taskflow]
action_execution_rule = {'your strategy name': 'ANY'}
Watcher CLI
The watcher command-line interface (CLI) can be used to interact with the Watcher system in order to control it or to know its current status.
Please, read the detailed documentation about Watcher CLI.
Watcher Dashboard
The Watcher Dashboard can be used to interact with the Watcher system through Horizon in order to control it or to know its current status.
Please, read the detailed documentation about Watcher Dashboard.
Watcher Database
This database stores all the Watcher domain objects which can be
requested by the Watcher API <archi_watcher_api_definition>
or
the Watcher CLI <archi_watcher_cli_definition>
:
Goals <goal_definition>
Strategies <strategy_definition>
Audit templates <audit_template_definition>
Audits <audit_definition>
Action plans <action_plan_definition>
Efficacy indicators <efficacy_indicator_definition>
via the Action Plan API.Actions <action_definition>
The Watcher domain being here "optimization of some resources provided by an OpenStack system".
Watcher Decision Engine
This component is responsible for computing a set of potential
optimization Actions <action_definition>
in order to fulfill
the Goal <goal_definition>
of an Audit <audit_definition>
.
It first reads the parameters of the Audit <audit_definition>
to know the Goal <goal_definition>
to achieve.
Unless specified, it then selects the most appropriate strategy
<strategy_definition>
from the list of available strategies
achieving this goal.
The Strategy <strategy_definition>
is then
dynamically loaded (via stevedore). The
Watcher Decision Engine <watcher_decision_engine_definition>
executes the strategy.
In order to compute the potential Solution <solution_definition>
for the Audit,
the Strategy <strategy_definition>
relies on
different sets of data:
Cluster data models <cluster_data_model_definition>
that are periodically synchronized through pluggable cluster data model collectors. These models contain the current state of variousManaged resources <managed_resource_definition>
(e.g., the data stored in the Nova database). These models gives a strategy the ability to reason on the current state of a givencluster <cluster_definition>
.- The data stored in the
Cluster Datasource <cluster_datasource_definition>
which provides information about the past of theCluster <cluster_definition>
.
Here below is a sequence diagram showing how the Decision Engine
builds and maintains the cluster data models <cluster_data_model_definition>
that are used by the strategies.
The execution of a strategy then yields a solution composed of a set
of Actions <action_definition>
as well as a set of
efficacy
indicators <efficacy_indicator_definition>
.
These Actions <action_definition>
are scheduled in
time by the Watcher Planner <watcher_planner_definition>
(i.e., it generates an Action Plan <action_plan_definition>
).
Data model
The following diagram shows the data model of Watcher, especially the functional dependency of objects from the actors (Admin, Customer) point of view (Goals, Audits, Action Plans, ...):
Here below is a diagram representing the main objects in Watcher from a database perspective:
Sequence diagrams
The following paragraph shows the messages exchanged between the different components of Watcher for the most often used scenarios.
Create a new Audit Template
The Administrator <administrator_definition>
first
creates an Audit template <audit_template_definition>
providing at least the following parameters:
- A name
- A goal to achieve
- An optional strategy
The Watcher
API makes sure that both the specified goal (mandatory) and its
associated strategy (optional) are registered inside the Watcher
Database <watcher_database_definition>
before storing a new
audit template in the Watcher Database <watcher_database_definition>
.
Create and launch a new Audit
The Administrator <administrator_definition>
can
then launch a new Audit <audit_definition>
by providing at least
the unique UUID of the previously created Audit template <audit_template_definition>
:
The Administrator <administrator_definition>
also
can specify type of Audit and interval (in case of CONTINUOUS type).
There is three types of Audit: ONESHOT, CONTINUOUS and EVENT. ONESHOT
Audit is launched once and if it succeeded executed new action plan list
will be provided; CONTINUOUS Audit creates action plans with specified
interval (in seconds or cron format, cron interval can be used like:
*/5 * * * *
), if action plan has been created, all previous
action plans get CANCELLED state; EVENT audit is launched when receiving
webhooks API.
A message is sent on the AMQP bus <amqp_bus_definition>
which triggers
the Audit in the Watcher Decision Engine <watcher_decision_engine_definition>
:
The Watcher Decision Engine <watcher_decision_engine_definition>
reads the Audit parameters from the Watcher Database <watcher_database_definition>
.
It instantiates the appropriate strategy <strategy_definition>
(using entry
points) given both the goal <goal_definition>
and the strategy
associated to the parent audit template <audit_template_definition>
of
the audit
<audit_definition>
. If no strategy is associated to the
audit template, the strategy is dynamically selected by the Decision
Engine.
The Watcher Decision Engine <watcher_decision_engine_definition>
also builds the Cluster Data Model <cluster_data_model_definition>
.
This data model is needed by the Strategy <strategy_definition>
to know the
current state and topology of the audited OpenStack cluster <cluster_definition>
.
The Watcher Decision Engine <watcher_decision_engine_definition>
calls the execute() method of the instantiated Strategy <strategy_definition>
and provides the
data model as an input parameter. This method computes a Solution <strategy_definition>
to achieve the
goal and returns it to the Decision Engine <watcher_decision_engine_definition>
.
At this point, actions are not scheduled yet.
The Watcher Decision Engine <watcher_decision_engine_definition>
dynamically loads the Watcher Planner <watcher_planner_definition>
implementation which is configured in Watcher (via entry points) and
calls the schedule() method of this class with the
solution as an input parameter. This method finds an appropriate
scheduling of Actions <action_definition>
taking into account
some scheduling rules (such as priorities between actions). It generates
a new Action Plan <action_plan_definition>
with status
RECOMMENDED and saves it into the Watcher Database
<watcher_database_definition>
. The saved action plan is now
a scheduled flow of actions to which a global efficacy is associated
alongside a number of Efficacy Indicators <efficacy_indicator_definition>
as specified by the related goal <goal_definition>
.
If every step executed successfully, the Watcher Decision Engine <watcher_decision_engine_definition>
updates the current status of the Audit to SUCCEEDED in
the Watcher Database <watcher_database_definition>
and sends a notification on the bus to inform other components that the
Audit <audit_definition>
was successful.
This internal workflow the Decision Engine follows to conduct an audit can be seen in the sequence diagram here below:
Launch Action Plan
The Administrator <administrator_definition>
can
then launch the recommended Action Plan <action_plan_definition>
:
A message is sent on the AMQP bus <amqp_bus_definition>
which triggers
the Action Plan <action_plan_definition>
in the
Watcher Applier <watcher_applier_definition>
:
The Watcher Applier <watcher_applier_definition>
will get the description of the flow of Actions <action_definition>
from the Watcher Database <watcher_database_definition>
and for each Action <action_definition>
it will instantiate a
corresponding Action <action_definition>
handler python
class.
The Watcher Applier <watcher_applier_definition>
will then call the following methods of the Action <action_definition>
handler:
- validate_parameters(): this method will make sure
that all the provided input parameters are valid:
- If all parameters are valid, the Watcher Applier moves on to the next step.
- If it is not, an error is raised and the action is not executed. A notification is sent on the bus informing other components of the failure.
- preconditions(): this method will make sure that all conditions are met before executing the action (for example, it makes sure that an instance still exists before trying to migrate it).
- execute(): this method is what triggers real commands on other OpenStack services (such as Nova, ...) in order to change target resource state. If the action is successfully executed, a notification message is sent on the bus indicating that the new state of the action is SUCCEEDED.
If every action of the action flow has been executed successfully, a
notification is sent on the bus to indicate that the whole Action Plan <action_plan_definition>
has
SUCCEEDED.
State Machine diagrams
Audit State Machine
An Audit <audit_definition>
has a life-cycle and
its current state may be one of the following:
- PENDING : a request for an
Audit <audit_definition>
has been submitted (either manually by theAdministrator <administrator_definition>
or automatically via some event handling mechanism) and is in the queue for being processed by theWatcher Decision Engine <watcher_decision_engine_definition>
- ONGOING : the
Audit <audit_definition>
is currently being processed by theWatcher Decision Engine <watcher_decision_engine_definition>
- SUCCEEDED : the
Audit <audit_definition>
has been executed successfully and at least one solution was found - FAILED : an error occurred while executing the
Audit <audit_definition>
- DELETED : the
Audit <audit_definition>
is still stored in theWatcher database <watcher_database_definition>
but is not returned any more through the Watcher APIs. - CANCELLED : the
Audit <audit_definition>
was in PENDING or ONGOING state and was cancelled by theAdministrator <administrator_definition>
- SUSPENDED : the
Audit <audit_definition>
was in ONGOING state and was suspended by theAdministrator <administrator_definition>
The following diagram shows the different possible states of an Audit <audit_definition>
and what event makes
the state change to a new value:
Action Plan State Machine
An Action Plan <action_plan_definition>
has a
life-cycle and its current state may be one of the following:
- RECOMMENDED : the
Action Plan <action_plan_definition>
is waiting for a validation from theAdministrator <administrator_definition>
- PENDING : a request for an
Action Plan <action_plan_definition>
has been submitted (due to anAdministrator <administrator_definition>
executing anAudit <audit_definition>
) and is in the queue for being processed by theWatcher Applier <watcher_applier_definition>
- ONGOING : the
Action Plan <action_plan_definition>
is currently being processed by theWatcher Applier <watcher_applier_definition>
- SUCCEEDED : the
Action Plan <action_plan_definition>
has been executed successfully (i.e. allActions <action_definition>
that it contains have been executed successfully) - FAILED : an error occurred while executing the
Action Plan <action_plan_definition>
- DELETED : the
Action Plan <action_plan_definition>
is still stored in theWatcher database <watcher_database_definition>
but is not returned any more through the Watcher APIs. - CANCELLED : the
Action Plan <action_plan_definition>
was in RECOMMENDED, PENDING or ONGOING state and was cancelled by theAdministrator <administrator_definition>
- SUPERSEDED : the
Action Plan <action_plan_definition>
was in RECOMMENDED state and was automatically superseded by Watcher, due to an expiration delay or an update of theCluster data model <cluster_data_model_definition>
The following diagram shows the different possible states of an Action Plan <action_plan_definition>
and what
event makes the state change to a new value: