Merge "Zuul: Remove project name"

Zuul no longer requires the project-name for in-repo configuration.
Omitting it makes forking or renaming projects easier.

Change-Id: Ib3be82015be1d6853c44cf53faacb238237ad701

.zuul.yaml

@@ -1,5 +1,4 @@
 - project:
-    name: openstack/watcher
     check:
       jobs:
         - watcher-tempest-multinode

doc/source/glossary.rst

@@ -267,7 +267,7 @@ the same goal and same workload of the :ref:`Cluster <cluster_definition>`.
 Project
 =======
 
-:ref:`Projects <project_definition>` represent the base unit of “ownership”
+:ref:`Projects <project_definition>` represent the base unit of "ownership"
 in OpenStack, in that all :ref:`resources <managed_resource_definition>` in
 OpenStack should be owned by a specific :ref:`project <project_definition>`.
 In OpenStack Identity, a :ref:`project <project_definition>` must be owned by a

doc/source/strategies/actuation.rst

@@ -0,0 +1,86 @@
+=============
+Actuator
+=============
+
+Synopsis
+--------
+
+**display name**: ``Actuator``
+
+**goal**: ``unclassified``
+
+    .. watcher-term:: watcher.decision_engine.strategy.strategies.actuation
+
+Requirements
+------------
+
+Metrics
+*******
+
+None
+
+Cluster data model
+******************
+
+None
+
+Actions
+*******
+
+Default Watcher's actions.
+
+Planner
+*******
+
+Default Watcher's planner:
+
+    .. watcher-term:: watcher.decision_engine.planner.weight.WeightPlanner
+
+Configuration
+-------------
+
+Strategy parameters are:
+
+==================== ====== ===================== =============================
+parameter            type   default Value         description
+==================== ====== ===================== =============================
+``actions``          array  None                  Actions to be executed.
+==================== ====== ===================== =============================
+
+The elements of actions array are:
+
+==================== ====== ===================== =============================
+parameter            type   default Value         description
+==================== ====== ===================== =============================
+``action_type``      string None                  Action name defined in
+                                                  setup.cfg(mandatory)
+``resource_id``      string None                  Resource_id of the action.
+``input_parameters`` object None                  Input_parameters of the
+                                                  action(mandatory).
+==================== ====== ===================== =============================
+
+Efficacy Indicator
+------------------
+
+None
+
+Algorithm
+---------
+
+This strategy create an action plan with a predefined set of actions.
+
+How to use it ?
+---------------
+
+.. code-block:: shell
+
+    $ openstack optimize audittemplate create \
+      at1 unclassified --strategy actuator
+
+    $ openstack optimize audit create -a at1 \
+      -p actions='[{"action_type": "migrate", "resource_id": "56a40802-6fde-4b59-957c-c84baec7eaed", "input_parameters": {"migration_type": "live", "source_node": "s01"}}]'
+
+External Links
+--------------
+
+None

doc/source/strategies/zone_migration.rst

@@ -0,0 +1,154 @@
+==============
+Zone migration
+==============
+
+Synopsis
+--------
+
+**display name**: ``Zone migration``
+
+**goal**: ``hardware_maintenance``
+
+    .. watcher-term:: watcher.decision_engine.strategy.strategies.zone_migration
+
+Requirements
+------------
+
+Metrics
+*******
+
+None
+
+Cluster data model
+******************
+
+Default Watcher's Compute cluster data model:
+
+    .. watcher-term:: watcher.decision_engine.model.collector.nova.NovaClusterDataModelCollector
+
+Storage cluster data model is also required:
+
+    .. watcher-term:: watcher.decision_engine.model.collector.cinder.CinderClusterDataModelCollector
+
+Actions
+*******
+
+
+Default Watcher's actions:
+
+    .. list-table::
+       :widths: 30 30
+       :header-rows: 1
+
+       * - action
+         - description
+       * - ``migrate``
+         - .. watcher-term:: watcher.applier.actions.migration.Migrate
+       * - ``volume_migrate``
+         - .. watcher-term:: watcher.applier.actions.volume_migration.VolumeMigrate
+
+Planner
+*******
+
+Default Watcher's planner:
+
+    .. watcher-term:: watcher.decision_engine.planner.weight.WeightPlanner
+
+Configuration
+-------------
+
+Strategy parameters are:
+
+======================== ======== ============= ==============================
+parameter                type     default Value description
+======================== ======== ============= ==============================
+``compute_nodes``        array    None          Compute nodes to migrate.
+``storage_pools``        array    None          Storage pools to migrate.
+``parallel_total``       integer  6             The number of actions to be
+                                                run in parallel in total.
+``parallel_per_node``    integer  2             The number of actions to be
+                                                run in parallel per compute
+                                                node.
+``parallel_per_pool``    integer  2             The number of actions to be
+                                                run in parallel per storage
+                                                pool.
+``priority``             object   None          List prioritizes instances
+                                                and volumes.
+``with_attached_volume`` boolean  False         False: Instances will migrate
+                                                after all volumes migrate.
+                                                True: An instance will migrate
+                                                after the attached volumes
+                                                migrate.
+======================== ======== ============= ==============================
+
+The elements of compute_nodes array are:
+
+============= ======= =============== =============================
+parameter     type    default Value   description
+============= ======= =============== =============================
+``src_node``  string    None          Compute node from which
+                                      instances migrate(mandatory).
+``dst_node``  string    None          Compute node to which
+                                      instances migrate.
+============= ======= =============== =============================
+
+The elements of storage_pools array are:
+
+============= ======= =============== ==============================
+parameter     type    default Value   description
+============= ======= =============== ==============================
+``src_pool``  string    None          Storage pool from which
+                                      volumes migrate(mandatory).
+``dst_pool``  string    None          Storage pool to which
+                                      volumes migrate.
+``src_type``  string    None          Source volume type(mandatory).
+``dst_type``  string    None          Destination volume type
+                                      (mandatory).
+============= ======= =============== ==============================
+
+The elements of priority object are:
+
+================ ======= =============== ======================
+parameter        type    default Value   description
+================ ======= =============== ======================
+``project``      array   None            Project names.
+``compute_node`` array   None            Compute node names.
+``storage_pool`` array   None            Storage pool names.
+``compute``      enum    None            Instance attributes.
+                                         |compute|
+``storage``      enum    None            Volume attributes.
+                                         |storage|
+================ ======= =============== ======================
+
+.. |compute| replace:: ["vcpu_num", "mem_size", "disk_size", "created_at"]
+.. |storage| replace:: ["size", "created_at"]
+
+Efficacy Indicator
+------------------
+
+.. watcher-func::
+  :format: literal_block
+
+  watcher.decision_engine.goal.efficacy.specs.HardwareMaintenance.get_global_efficacy_indicator
+
+Algorithm
+---------
+
+For more information on the zone migration strategy please refer
+to: http://specs.openstack.org/openstack/watcher-specs/specs/queens/implemented/zone-migration-strategy.html
+
+How to use it ?
+---------------
+
+.. code-block:: shell
+
+    $ openstack optimize audittemplate create \
+      at1 hardware_maintenance --strategy zone_migration
+
+    $ openstack optimize audit create -a at1 \
+      -p compute_nodes='[{"src_node": "s01", "dst_node": "d01"}]'
+
+External Links
+--------------
+
+None

releasenotes/source/locale/en_GB/LC_MESSAGES/releasenotes.po

@@ -4,11 +4,11 @@ msgid ""
 msgstr ""
 "Project-Id-Version: watcher\n"
 "Report-Msgid-Bugs-To: \n"
-"POT-Creation-Date: 2018-01-19 11:46+0000\n"
+"POT-Creation-Date: 2018-01-26 00:18+0000\n"
 "MIME-Version: 1.0\n"
 "Content-Type: text/plain; charset=UTF-8\n"
 "Content-Transfer-Encoding: 8bit\n"
-"PO-Revision-Date: 2018-01-19 07:16+0000\n"
+"PO-Revision-Date: 2018-01-27 12:50+0000\n"
 "Last-Translator: Andi Chandler <andi@gowling.com>\n"
 "Language-Team: English (United Kingdom)\n"
 "Language: en-GB\n"
@@ -42,8 +42,8 @@ msgstr "1.5.0"
 msgid "1.6.0"
 msgstr "1.6.0"
 
-msgid "1.6.0-32"
-msgstr "1.6.0-32"
+msgid "1.7.0"
+msgstr "1.7.0"
 
 msgid "Add a service supervisor to watch Watcher deamons."
 msgstr "Add a service supervisor to watch Watcher daemons."
@@ -136,6 +136,17 @@ msgstr ""
 "Added a way to add a new action without having to amend the source code of "
 "the default planner."
 
+msgid ""
+"Added a way to check state of strategy before audit's execution. "
+"Administrator can use \"watcher strategy state <strategy_name>\" command to "
+"get information about metrics' availability, datasource's availability and "
+"CDM's availability."
+msgstr ""
+"Added a way to check state of strategy before audit's execution. "
+"Administrator can use \"watcher strategy state <strategy_name>\" command to "
+"get information about metrics' availability, datasource's availability and "
+"CDM's availability."
+
 msgid ""
 "Added a way to compare the efficacy of different strategies for a give "
 "optimization goal."
@@ -186,6 +197,18 @@ msgstr ""
 msgid "Added policies to handle user rights to access Watcher API."
 msgstr "Added policies to handle user rights to access Watcher API."
 
+msgid "Added storage capacity balance strategy."
+msgstr "Added storage capacity balance strategy."
+
+msgid ""
+"Added strategy \"Zone migration\" and it's goal \"Hardware maintenance\". "
+"The strategy migrates many instances and volumes efficiently with minimum "
+"downtime automatically."
+msgstr ""
+"Added strategy \"Zone migration\" and it's goal \"Hardware maintenance\". "
+"The strategy migrates many instances and volumes efficiently with minimum "
+"downtime automatically."
+
 msgid ""
 "Added strategy to identify and migrate a Noisy Neighbor - a low priority VM "
 "that negatively affects peformance of a high priority VM by over utilizing "
@@ -212,6 +235,13 @@ msgstr "Added using of JSONSchema instead of voluptuous to validate Actions."
 msgid "Added volume migrate action"
 msgstr "Added volume migrate action"
 
+msgid ""
+"Adds audit scoper for storage data model, now watcher users can specify "
+"audit scope for storage CDM in the same manner as compute scope."
+msgstr ""
+"Adds audit scoper for storage data model, now watcher users can specify "
+"audit scope for storage CDM in the same manner as compute scope."
+
 msgid "Adds baremetal data model in Watcher"
 msgstr "Adds baremetal data model in Watcher"
 

requirements.txt

@@ -23,7 +23,7 @@ oslo.reports>=1.18.0 # Apache-2.0
 oslo.serialization!=2.19.1,>=2.18.0 # Apache-2.0
 oslo.service!=1.28.1,>=1.24.0 # Apache-2.0
 oslo.utils>=3.33.0 # Apache-2.0
-oslo.versionedobjects>=1.28.0 # Apache-2.0
+oslo.versionedobjects>=1.31.2 # Apache-2.0
 PasteDeploy>=1.5.0 # MIT
 pbr!=2.1.0,>=2.0.0 # Apache-2.0
 pecan!=1.0.2,!=1.0.3,!=1.0.4,!=1.2,>=1.0.0 # BSD
@@ -38,7 +38,7 @@ python-monascaclient>=1.7.0 # Apache-2.0
 python-neutronclient>=6.3.0 # Apache-2.0
 python-novaclient>=9.1.0 # Apache-2.0
 python-openstackclient>=3.12.0 # Apache-2.0
-python-ironicclient>=1.14.0 # Apache-2.0
+python-ironicclient>=2.2.0 # Apache-2.0
 six>=1.10.0 # MIT
 SQLAlchemy!=1.1.5,!=1.1.6,!=1.1.7,!=1.1.8,>=1.0.10 # MIT
 stevedore>=1.20.0 # Apache-2.0

watcher/common/nova_helper.py

@@ -52,14 +52,21 @@ class NovaHelper(object):
         return self.nova.hypervisors.get(utils.Struct(id=node_id))
 
     def get_compute_node_by_hostname(self, node_hostname):
-        """Get compute node by ID (*not* UUID)"""
-        # We need to pass an object with an 'id' attribute to make it work
+        """Get compute node by hostname"""
         try:
-            compute_nodes = self.nova.hypervisors.search(node_hostname)
-            if len(compute_nodes) != 1:
+            hypervisors = [hv for hv in self.get_compute_node_list()
+                           if hv.service['host'] == node_hostname]
+            if len(hypervisors) != 1:
+                # TODO(hidekazu)
+                # this may occur if VMware vCenter driver is used
                 raise exception.ComputeNodeNotFound(name=node_hostname)
+            else:
+                compute_nodes = self.nova.hypervisors.search(
+                    hypervisors[0].hypervisor_hostname)
+                if len(compute_nodes) != 1:
+                    raise exception.ComputeNodeNotFound(name=node_hostname)
 
-            return self.get_compute_node_by_id(compute_nodes[0].id)
+                return self.get_compute_node_by_id(compute_nodes[0].id)
         except Exception as exc:
             LOG.exception(exc)
             raise exception.ComputeNodeNotFound(name=node_hostname)

watcher/datasource/base.py

@@ -57,6 +57,12 @@ class DataSourceBase(object):
                      ),
     )
 
+    @abc.abstractmethod
+    def statistic_aggregation(self, resource_id=None, meter_name=None,
+                              period=300, granularity=300, dimensions=None,
+                              aggregation='avg', group_by='*'):
+        pass
+
     @abc.abstractmethod
     def list_metrics(self):
         pass

watcher/datasource/ceilometer.py

@@ -145,24 +145,28 @@ class CeilometerHelper(base.DataSourceBase):
         else:
             return meters
 
-    def statistic_aggregation(self,
-                              resource_id,
-                              meter_name,
-                              period,
-                              aggregate='avg'):
+    def statistic_aggregation(self, resource_id=None, meter_name=None,
+                              period=300, granularity=300, dimensions=None,
+                              aggregation='avg', group_by='*'):
         """Representing a statistic aggregate by operators
 
         :param resource_id: id of resource to list statistics for.
         :param meter_name: Name of meter to list statistics for.
         :param period: Period in seconds over which to group samples.
-        :param aggregate: Available aggregates are: count, cardinality,
-                           min, max, sum, stddev, avg. Defaults to avg.
+        :param granularity: frequency of marking metric point, in seconds.
+                            This param isn't used in Ceilometer datasource.
+        :param dimensions: dimensions (dict). This param isn't used in
+                           Ceilometer datasource.
+        :param aggregation: Available aggregates are: count, cardinality,
+                            min, max, sum, stddev, avg. Defaults to avg.
+        :param group_by: list of columns to group the metrics to be returned.
+                         This param isn't used in Ceilometer datasource.
         :return: Return the latest statistical data, None if no data.
         """
 
         end_time = datetime.datetime.utcnow()
-        if aggregate == 'mean':
-            aggregate = 'avg'
+        if aggregation == 'mean':
+            aggregation = 'avg'
         start_time = end_time - datetime.timedelta(seconds=int(period))
         query = self.build_query(
             resource_id=resource_id, start_time=start_time, end_time=end_time)
@@ -171,11 +175,11 @@ class CeilometerHelper(base.DataSourceBase):
                                      q=query,
                                      period=period,
                                      aggregates=[
-                                         {'func': aggregate}])
+                                         {'func': aggregation}])
 
         item_value = None
         if statistic:
-            item_value = statistic[-1]._info.get('aggregate').get(aggregate)
+            item_value = statistic[-1]._info.get('aggregate').get(aggregation)
         return item_value
 
     def get_last_sample_values(self, resource_id, meter_name, limit=1):
@@ -204,64 +208,64 @@ class CeilometerHelper(base.DataSourceBase):
                            granularity=None):
         meter_name = self.METRIC_MAP.get('host_cpu_usage')
         return self.statistic_aggregation(resource_id, meter_name, period,
-                                          aggregate=aggregate)
+                                          granularity, aggregate=aggregate)
 
     def get_instance_cpu_usage(self, resource_id, period, aggregate,
                                granularity=None):
         meter_name = self.METRIC_MAP.get('instance_cpu_usage')
         return self.statistic_aggregation(resource_id, meter_name, period,
-                                          aggregate=aggregate)
+                                          granularity, aggregate=aggregate)
 
     def get_host_memory_usage(self, resource_id, period, aggregate,
                               granularity=None):
         meter_name = self.METRIC_MAP.get('host_memory_usage')
         return self.statistic_aggregation(resource_id, meter_name, period,
-                                          aggregate=aggregate)
+                                          granularity, aggregate=aggregate)
 
     def get_instance_memory_usage(self, resource_id, period, aggregate,
                                   granularity=None):
         meter_name = self.METRIC_MAP.get('instance_ram_usage')
         return self.statistic_aggregation(resource_id, meter_name, period,
-                                          aggregate=aggregate)
+                                          granularity, aggregate=aggregate)
 
     def get_instance_l3_cache_usage(self, resource_id, period, aggregate,
                                     granularity=None):
         meter_name = self.METRIC_MAP.get('instance_l3_cache_usage')
         return self.statistic_aggregation(resource_id, meter_name, period,
-                                          aggregate=aggregate)
+                                          granularity, aggregate=aggregate)
 
     def get_instance_ram_allocated(self, resource_id, period, aggregate,
                                    granularity=None):
         meter_name = self.METRIC_MAP.get('instance_ram_allocated')
         return self.statistic_aggregation(resource_id, meter_name, period,
-                                          aggregate=aggregate)
+                                          granularity, aggregate=aggregate)
 
     def get_instance_root_disk_allocated(self, resource_id, period, aggregate,
                                          granularity=None):
         meter_name = self.METRIC_MAP.get('instance_root_disk_size')
         return self.statistic_aggregation(resource_id, meter_name, period,
-                                          aggregate=aggregate)
+                                          granularity, aggregate=aggregate)
 
     def get_host_outlet_temperature(self, resource_id, period, aggregate,
                                     granularity=None):
         meter_name = self.METRIC_MAP.get('host_outlet_temp')
         return self.statistic_aggregation(resource_id, meter_name, period,
-                                          aggregate=aggregate)
+                                          granularity, aggregate=aggregate)
 
     def get_host_inlet_temperature(self, resource_id, period, aggregate,
                                    granularity=None):
         meter_name = self.METRIC_MAP.get('host_inlet_temp')
         return self.statistic_aggregation(resource_id, meter_name, period,
-                                          aggregate=aggregate)
+                                          granularity, aggregate=aggregate)
 
     def get_host_airflow(self, resource_id, period, aggregate,
                          granularity=None):
         meter_name = self.METRIC_MAP.get('host_airflow')
         return self.statistic_aggregation(resource_id, meter_name, period,
-                                          aggregate=aggregate)
+                                          granularity, aggregate=aggregate)
 
     def get_host_power(self, resource_id, period, aggregate,
                        granularity=None):
         meter_name = self.METRIC_MAP.get('host_power')
         return self.statistic_aggregation(resource_id, meter_name, period,
-                                          aggregate=aggregate)
+                                          granularity, aggregate=aggregate)

watcher/datasource/gnocchi.py

@@ -58,32 +58,35 @@ class GnocchiHelper(base.DataSourceBase):
             return 'not available'
         return 'available'
 
-    def _statistic_aggregation(self,
-                               resource_id,
-                               metric,
-                               granularity,
-                               start_time=None,
-                               stop_time=None,
-                               aggregation='mean'):
+    def list_metrics(self):
+        """List the user's meters."""
+        try:
+            response = self.query_retry(f=self.gnocchi.metric.list)
+        except Exception:
+            return set()
+        else:
+            return set([metric['name'] for metric in response])
+
+    def statistic_aggregation(self, resource_id=None, meter_name=None,
+                              period=300, granularity=300, dimensions=None,
+                              aggregation='avg', group_by='*'):
         """Representing a statistic aggregate by operators
 
-        :param metric: metric name of which we want the statistics
-        :param resource_id: id of resource to list statistics for
-        :param start_time: Start datetime from which metrics will be used
-        :param stop_time: End datetime from which metrics will be used
-        :param granularity: frequency of marking metric point, in seconds
+        :param resource_id: id of resource to list statistics for.
+        :param meter_name: meter name of which we want the statistics.
+        :param period: Period in seconds over which to group samples.
+        :param granularity: frequency of marking metric point, in seconds.
+        :param dimensions: dimensions (dict). This param isn't used in
+                           Gnocchi datasource.
         :param aggregation: Should be chosen in accordance with policy
-                            aggregations
+                            aggregations.
+        :param group_by: list of columns to group the metrics to be returned.
+                         This param isn't used in Gnocchi datasource.
         :return: value of aggregated metric
         """
 
-        if start_time is not None and not isinstance(start_time, datetime):
-            raise exception.InvalidParameter(parameter='start_time',
-                                             parameter_type=datetime)
-
-        if stop_time is not None and not isinstance(stop_time, datetime):
-            raise exception.InvalidParameter(parameter='stop_time',
-                                             parameter_type=datetime)
+        stop_time = datetime.utcnow()
+        start_time = stop_time - timedelta(seconds=(int(period)))
 
         if not common_utils.is_uuid_like(resource_id):
             kwargs = dict(query={"=": {"original_resource_id": resource_id}},
@@ -97,7 +100,7 @@ class GnocchiHelper(base.DataSourceBase):
             resource_id = resources[0]['id']
 
         raw_kwargs = dict(
-            metric=metric,
+            metric=meter_name,
             start=start_time,
             stop=stop_time,
             resource_id=resource_id,
@@ -115,27 +118,6 @@ class GnocchiHelper(base.DataSourceBase):
             # measure has structure [time, granularity, value]
             return statistics[-1][2]
 
-    def list_metrics(self):
-        """List the user's meters."""
-        try:
-            response = self.query_retry(f=self.gnocchi.metric.list)
-        except Exception:
-            return set()
-        else:
-            return set([metric['name'] for metric in response])
-
-    def statistic_aggregation(self, resource_id, metric, period, granularity,
-                              aggregation='mean'):
-        stop_time = datetime.utcnow()
-        start_time = stop_time - timedelta(seconds=(int(period)))
-        return self._statistic_aggregation(
-            resource_id=resource_id,
-            metric=metric,
-            granularity=granularity,
-            start_time=start_time,
-            stop_time=stop_time,
-            aggregation=aggregation)
-
     def get_host_cpu_usage(self, resource_id, period, aggregate,
                            granularity=300):
         meter_name = self.METRIC_MAP.get('host_cpu_usage')

watcher/datasource/monasca.py

@@ -21,6 +21,7 @@ import datetime
 from monascaclient import exc
 
 from watcher.common import clients
+from watcher.common import exception
 from watcher.datasource import base
 
 
@@ -97,41 +98,42 @@ class MonascaHelper(base.DataSourceBase):
 
         return statistics
 
-    def statistic_aggregation(self,
-                              meter_name,
-                              dimensions,
-                              start_time=None,
-                              end_time=None,
-                              period=None,
-                              aggregate='avg',
-                              group_by='*'):
+    def statistic_aggregation(self, resource_id=None, meter_name=None,
+                              period=300, granularity=300, dimensions=None,
+                              aggregation='avg', group_by='*'):
         """Representing a statistic aggregate by operators
 
-        :param meter_name: meter names of which we want the statistics
-        :param dimensions: dimensions (dict)
-        :param start_time: Start datetime from which metrics will be used
-        :param end_time: End datetime from which metrics will be used
+        :param resource_id: id of resource to list statistics for.
+                            This param isn't used in Monasca datasource.
+        :param meter_name: meter names of which we want the statistics.
         :param period: Sampling `period`: In seconds. If no period is given,
                        only one aggregate statistic is returned. If given, a
                        faceted result will be returned, divided into given
                        periods. Periods with no data are ignored.
-        :param aggregate: Should be either 'avg', 'count', 'min' or 'max'
+        :param granularity: frequency of marking metric point, in seconds.
+                            This param isn't used in Ceilometer datasource.
+        :param dimensions: dimensions (dict).
+        :param aggregation: Should be either 'avg', 'count', 'min' or 'max'.
+        :param group_by: list of columns to group the metrics to be returned.
         :return: A list of dict with each dict being a distinct result row
         """
-        start_timestamp, end_timestamp, period = self._format_time_params(
-            start_time, end_time, period
-        )
 
-        if aggregate == 'mean':
-            aggregate = 'avg'
+        if dimensions is None:
+            raise exception.UnsupportedDataSource(datasource='Monasca')
+
+        stop_time = datetime.datetime.utcnow()
+        start_time = stop_time - datetime.timedelta(seconds=(int(period)))
+
+        if aggregation == 'mean':
+            aggregation = 'avg'
 
         raw_kwargs = dict(
             name=meter_name,
-            start_time=start_timestamp,
-            end_time=end_timestamp,
+            start_time=start_time.isoformat(),
+            end_time=stop_time.isoformat(),
             dimensions=dimensions,
             period=period,
-            statistics=aggregate,
+            statistics=aggregation,
             group_by=group_by,
         )
 
@@ -140,45 +142,36 @@ class MonascaHelper(base.DataSourceBase):
         statistics = self.query_retry(
             f=self.monasca.metrics.list_statistics, **kwargs)
 
-        return statistics
+        cpu_usage = None
+        for stat in statistics:
+            avg_col_idx = stat['columns'].index(aggregation)
+            values = [r[avg_col_idx] for r in stat['statistics']]
+            value = float(sum(values)) / len(values)
+            cpu_usage = value
+
+        return cpu_usage
 
     def get_host_cpu_usage(self, resource_id, period, aggregate,
                            granularity=None):
         metric_name = self.METRIC_MAP.get('host_cpu_usage')
         node_uuid = resource_id.split('_')[0]
-        statistics = self.statistic_aggregation(
+        return self.statistic_aggregation(
             meter_name=metric_name,
             dimensions=dict(hostname=node_uuid),
             period=period,
-            aggregate=aggregate
+            aggregation=aggregate
         )
-        cpu_usage = None
-        for stat in statistics:
-            avg_col_idx = stat['columns'].index('avg')
-            values = [r[avg_col_idx] for r in stat['statistics']]
-            value = float(sum(values)) / len(values)
-            cpu_usage = value
-
-        return cpu_usage
 
     def get_instance_cpu_usage(self, resource_id, period, aggregate,
                                granularity=None):
         metric_name = self.METRIC_MAP.get('instance_cpu_usage')
 
-        statistics = self.statistic_aggregation(
+        return self.statistic_aggregation(
             meter_name=metric_name,
             dimensions=dict(resource_id=resource_id),
             period=period,
-            aggregate=aggregate
+            aggregation=aggregate
         )
-        cpu_usage = None
-        for stat in statistics:
-            avg_col_idx = stat['columns'].index('avg')
-            values = [r[avg_col_idx] for r in stat['statistics']]
-            value = float(sum(values)) / len(values)
-            cpu_usage = value
-
-        return cpu_usage
 
     def get_host_memory_usage(self, resource_id, period, aggregate,
                               granularity=None):

watcher/decision_engine/strategy/strategies/base.py

@@ -66,7 +66,7 @@ class StrategyEndpoint(object):
             ds_metrics = datasource.list_metrics()
             if ds_metrics is None:
                 raise exception.DataSourceNotAvailable(
-                    datasource=strategy.config.datasource)
+                    datasource=datasource.NAME)
             else:
                 for metric in strategy.DATASOURCE_METRICS:
                     original_metric_name = datasource.METRIC_MAP.get(metric)
@@ -81,7 +81,7 @@ class StrategyEndpoint(object):
         if not datasource:
             state = "Datasource is not presented for this strategy"
         else:
-            state = "%s: %s" % (strategy.config.datasource,
+            state = "%s: %s" % (datasource.NAME,
                                 datasource.check_availability())
         return {'type': 'Datasource',
                 'state': state,
@@ -104,7 +104,7 @@ class StrategyEndpoint(object):
         try:
             is_datasources = getattr(strategy.config, 'datasources', None)
             if is_datasources:
-                datasource = is_datasources[0]
+                datasource = getattr(strategy, 'datasource_backend')
             else:
                 datasource = getattr(strategy, strategy.config.datasource)
         except (AttributeError, IndexError):
@@ -272,7 +272,7 @@ class BaseStrategy(loadable.Loadable):
             collector = self.collector_manager.get_cluster_model_collector(
                 'storage', osc=self.osc)
             audit_scope_handler = collector.get_audit_scope_handler(
-                audit_scope=self.audit.scope)
+                audit_scope=self.audit_scope)
             self._storage_model = audit_scope_handler.get_scoped_model(
                 collector.get_latest_cluster_data_model())
 

watcher/decision_engine/strategy/strategies/basic_consolidation.py

@@ -149,8 +149,10 @@ class BasicConsolidation(base.ServerConsolidationBaseStrategy):
     def get_config_opts(cls):
         return [
             cfg.ListOpt(
-                "datasource",
-                help="Data source to use in order to query the needed metrics",
+                "datasources",
+                help="Datasources to use in order to query the needed metrics."
+                     " If one of strategy metric isn't available in the first"
+                     " datasource, the next datasource will be chosen.",
                 item_type=cfg.types.String(choices=['gnocchi', 'ceilometer',
                                                     'monasca']),
                 default=['gnocchi', 'ceilometer', 'monasca']),

watcher/decision_engine/strategy/strategies/noisy_neighbor.py

@@ -86,8 +86,10 @@ class NoisyNeighbor(base.NoisyNeighborBaseStrategy):
     def get_config_opts(cls):
         return [
             cfg.ListOpt(
-                "datasource",
-                help="Data source to use in order to query the needed metrics",
+                "datasources",
+                help="Datasources to use in order to query the needed metrics."
+                     " If one of strategy metric isn't available in the first"
+                     " datasource, the next datasource will be chosen.",
                 item_type=cfg.types.String(choices=['gnocchi', 'ceilometer',
                                                     'monasca']),
                 default=['gnocchi', 'ceilometer', 'monasca'])

watcher/decision_engine/strategy/strategies/outlet_temp_control.py

@@ -28,15 +28,11 @@ Outlet (Exhaust Air) Temperature is one of the important thermal
 telemetries to measure thermal/workload status of server.
 """
 
-import datetime
-
 from oslo_config import cfg
 from oslo_log import log
 
 from watcher._i18n import _
 from watcher.common import exception as wexc
-from watcher.datasource import ceilometer as ceil
-from watcher.datasource import gnocchi as gnoc
 from watcher.decision_engine.model import element
 from watcher.decision_engine.strategy.strategies import base
 
@@ -95,8 +91,6 @@ class OutletTempControl(base.ThermalOptimizationBaseStrategy):
         :type osc: :py:class:`~.OpenStackClients` instance, optional
         """
         super(OutletTempControl, self).__init__(config, osc)
-        self._ceilometer = None
-        self._gnocchi = None
 
     @classmethod
     def get_name(cls):
@@ -139,26 +133,6 @@ class OutletTempControl(base.ThermalOptimizationBaseStrategy):
             },
         }
 
-    @property
-    def ceilometer(self):
-        if self._ceilometer is None:
-            self.ceilometer = ceil.CeilometerHelper(osc=self.osc)
-        return self._ceilometer
-
-    @ceilometer.setter
-    def ceilometer(self, c):
-        self._ceilometer = c
-
-    @property
-    def gnocchi(self):
-        if self._gnocchi is None:
-            self.gnocchi = gnoc.GnocchiHelper(osc=self.osc)
-        return self._gnocchi
-
-    @gnocchi.setter
-    def gnocchi(self, g):
-        self._gnocchi = g
-
     @property
     def granularity(self):
         return self.input_parameters.get('granularity', 300)
@@ -208,25 +182,13 @@ class OutletTempControl(base.ThermalOptimizationBaseStrategy):
             resource_id = node.uuid
             outlet_temp = None
 
-            if self.config.datasource == "ceilometer":
-                outlet_temp = self.ceilometer.statistic_aggregation(
-                    resource_id=resource_id,
-                    meter_name=metric_name,
-                    period=self.period,
-                    aggregate='avg'
-                )
-            elif self.config.datasource == "gnocchi":
-                stop_time = datetime.datetime.utcnow()
-                start_time = stop_time - datetime.timedelta(
-                    seconds=int(self.period))
-                outlet_temp = self.gnocchi.statistic_aggregation(
-                    resource_id=resource_id,
-                    metric=metric_name,
-                    granularity=self.granularity,
-                    start_time=start_time,
-                    stop_time=stop_time,
-                    aggregation='mean'
-                )
+            outlet_temp = self.datasource_backend.statistic_aggregation(
+                resource_id=resource_id,
+                meter_name=metric_name,
+                period=self.period,
+                granularity=self.granularity,
+            )
+
             # some hosts may not have outlet temp meters, remove from target
             if outlet_temp is None:
                 LOG.warning("%s: no outlet temp data", resource_id)

watcher/decision_engine/strategy/strategies/uniform_airflow.py

@@ -42,15 +42,11 @@ airflow is higher than the specified threshold.
 - It assumes that live migrations are possible.
 """
 
-import datetime
-
 from oslo_config import cfg
 from oslo_log import log
 
 from watcher._i18n import _
 from watcher.common import exception as wexc
-from watcher.datasource import ceilometer as ceil
-from watcher.datasource import gnocchi as gnoc
 from watcher.decision_engine.model import element
 from watcher.decision_engine.strategy.strategies import base
 
@@ -125,30 +121,8 @@ class UniformAirflow(base.BaseStrategy):
             self.config.datasource]['host_inlet_temp']
         self.meter_name_power = self.METRIC_NAMES[
             self.config.datasource]['host_power']
-        self._ceilometer = None
-        self._gnocchi = None
         self._period = self.PERIOD
 
-    @property
-    def ceilometer(self):
-        if self._ceilometer is None:
-            self.ceilometer = ceil.CeilometerHelper(osc=self.osc)
-        return self._ceilometer
-
-    @ceilometer.setter
-    def ceilometer(self, c):
-        self._ceilometer = c
-
-    @property
-    def gnocchi(self):
-        if self._gnocchi is None:
-            self.gnocchi = gnoc.GnocchiHelper(osc=self.osc)
-        return self._gnocchi
-
-    @gnocchi.setter
-    def gnocchi(self, g):
-        self._gnocchi = g
-
     @classmethod
     def get_name(cls):
         return "uniform_airflow"
@@ -247,35 +221,16 @@ class UniformAirflow(base.BaseStrategy):
             source_instances = self.compute_model.get_node_instances(
                 source_node)
             if source_instances:
-                if self.config.datasource == "ceilometer":
-                    inlet_t = self.ceilometer.statistic_aggregation(
-                        resource_id=source_node.uuid,
-                        meter_name=self.meter_name_inlet_t,
-                        period=self._period,
-                        aggregate='avg')
-                    power = self.ceilometer.statistic_aggregation(
-                        resource_id=source_node.uuid,
-                        meter_name=self.meter_name_power,
-                        period=self._period,
-                        aggregate='avg')
-                elif self.config.datasource == "gnocchi":
-                    stop_time = datetime.datetime.utcnow()
-                    start_time = stop_time - datetime.timedelta(
-                        seconds=int(self._period))
-                    inlet_t = self.gnocchi.statistic_aggregation(
-                        resource_id=source_node.uuid,
-                        metric=self.meter_name_inlet_t,
-                        granularity=self.granularity,
-                        start_time=start_time,
-                        stop_time=stop_time,
-                        aggregation='mean')
-                    power = self.gnocchi.statistic_aggregation(
-                        resource_id=source_node.uuid,
-                        metric=self.meter_name_power,
-                        granularity=self.granularity,
-                        start_time=start_time,
-                        stop_time=stop_time,
-                        aggregation='mean')
+                inlet_t = self.datasource_backend.statistic_aggregation(
+                    resource_id=source_node.uuid,
+                    meter_name=self.meter_name_inlet_t,
+                    period=self._period,
+                    granularity=self.granularity)
+                power = self.datasource_backend.statistic_aggregation(
+                    resource_id=source_node.uuid,
+                    meter_name=self.meter_name_power,
+                    period=self._period,
+                    granularity=self.granularity)
                 if (power < self.threshold_power and
                         inlet_t < self.threshold_inlet_t):
                     # hardware issue, migrate all instances from this node
@@ -353,23 +308,11 @@ class UniformAirflow(base.BaseStrategy):
             node = self.compute_model.get_node_by_uuid(
                 node_id)
             resource_id = node.uuid
-            if self.config.datasource == "ceilometer":
-                airflow = self.ceilometer.statistic_aggregation(
-                    resource_id=resource_id,
-                    meter_name=self.meter_name_airflow,
-                    period=self._period,
-                    aggregate='avg')
-            elif self.config.datasource == "gnocchi":
-                stop_time = datetime.datetime.utcnow()
-                start_time = stop_time - datetime.timedelta(
-                    seconds=int(self._period))
-                airflow = self.gnocchi.statistic_aggregation(
-                    resource_id=resource_id,
-                    metric=self.meter_name_airflow,
-                    granularity=self.granularity,
-                    start_time=start_time,
-                    stop_time=stop_time,
-                    aggregation='mean')
+            airflow = self.datasource_backend.statistic_aggregation(
+                resource_id=resource_id,
+                meter_name=self.meter_name_airflow,
+                period=self._period,
+                granularity=self.granularity)
             # some hosts may not have airflow meter, remove from target
             if airflow is None:
                 LOG.warning("%s: no airflow data", resource_id)

watcher/decision_engine/strategy/strategies/vm_workload_consolidation.py

@@ -52,7 +52,6 @@ correctly on all compute nodes within the cluster.
 This strategy assumes it is possible to live migrate any VM from
 an active compute node to any other active compute node.
 """
-import datetime
 
 from oslo_config import cfg
 from oslo_log import log
@@ -60,8 +59,6 @@ import six
 
 from watcher._i18n import _
 from watcher.common import exception
-from watcher.datasource import ceilometer as ceil
-from watcher.datasource import gnocchi as gnoc
 from watcher.decision_engine.model import element
 from watcher.decision_engine.strategy.strategies import base
 
@@ -118,26 +115,6 @@ class VMWorkloadConsolidation(base.ServerConsolidationBaseStrategy):
     def period(self):
         return self.input_parameters.get('period', 3600)
 
-    @property
-    def ceilometer(self):
-        if self._ceilometer is None:
-            self.ceilometer = ceil.CeilometerHelper(osc=self.osc)
-        return self._ceilometer
-
-    @ceilometer.setter
-    def ceilometer(self, ceilometer):
-        self._ceilometer = ceilometer
-
-    @property
-    def gnocchi(self):
-        if self._gnocchi is None:
-            self.gnocchi = gnoc.GnocchiHelper(osc=self.osc)
-        return self._gnocchi
-
-    @gnocchi.setter
-    def gnocchi(self, gnocchi):
-        self._gnocchi = gnocchi
-
     @property
     def granularity(self):
         return self.input_parameters.get('granularity', 300)
@@ -315,57 +292,28 @@ class VMWorkloadConsolidation(base.ServerConsolidationBaseStrategy):
         disk_alloc_metric = self.METRIC_NAMES[
             self.config.datasource]['disk_alloc_metric']
 
-        if self.config.datasource == "ceilometer":
-            instance_cpu_util = self.ceilometer.statistic_aggregation(
-                resource_id=instance.uuid, meter_name=cpu_util_metric,
-                period=self.period, aggregate='avg')
-            instance_ram_util = self.ceilometer.statistic_aggregation(
-                resource_id=instance.uuid, meter_name=ram_util_metric,
-                period=self.period, aggregate='avg')
-            if not instance_ram_util:
-                instance_ram_util = self.ceilometer.statistic_aggregation(
-                    resource_id=instance.uuid, meter_name=ram_alloc_metric,
-                    period=self.period, aggregate='avg')
-            instance_disk_util = self.ceilometer.statistic_aggregation(
-                resource_id=instance.uuid, meter_name=disk_alloc_metric,
-                period=self.period, aggregate='avg')
-        elif self.config.datasource == "gnocchi":
-            stop_time = datetime.datetime.utcnow()
-            start_time = stop_time - datetime.timedelta(
-                seconds=int(self.period))
-            instance_cpu_util = self.gnocchi.statistic_aggregation(
+        instance_cpu_util = self.datasource_backend.statistic_aggregation(
+            resource_id=instance.uuid,
+            meter_name=cpu_util_metric,
+            period=self.period,
+            granularity=self.granularity)
+        instance_ram_util = self.datasource_backend.statistic_aggregation(
+            resource_id=instance.uuid,
+            meter_name=ram_util_metric,
+            period=self.period,
+            granularity=self.granularity)
+        if not instance_ram_util:
+            instance_ram_util = self.datasource_backend.statistic_aggregation(
                 resource_id=instance.uuid,
-                metric=cpu_util_metric,
-                granularity=self.granularity,
-                start_time=start_time,
-                stop_time=stop_time,
-                aggregation='mean'
-            )
-            instance_ram_util = self.gnocchi.statistic_aggregation(
-                resource_id=instance.uuid,
-                metric=ram_util_metric,
-                granularity=self.granularity,
-                start_time=start_time,
-                stop_time=stop_time,
-                aggregation='mean'
-            )
-            if not instance_ram_util:
-                instance_ram_util = self.gnocchi.statistic_aggregation(
-                    resource_id=instance.uuid,
-                    metric=ram_alloc_metric,
-                    granularity=self.granularity,
-                    start_time=start_time,
-                    stop_time=stop_time,
-                    aggregation='mean'
-                )
-            instance_disk_util = self.gnocchi.statistic_aggregation(
-                resource_id=instance.uuid,
-                metric=disk_alloc_metric,
-                granularity=self.granularity,
-                start_time=start_time,
-                stop_time=stop_time,
-                aggregation='mean'
-            )
+                meter_name=ram_alloc_metric,
+                period=self.period,
+                granularity=self.granularity)
+        instance_disk_util = self.datasource_backend.statistic_aggregation(
+            resource_id=instance.uuid,
+            meter_name=disk_alloc_metric,
+            period=self.period,
+            granularity=self.granularity)
+
         if instance_cpu_util:
             total_cpu_utilization = (
                 instance.vcpus * (instance_cpu_util / 100.0))

watcher/decision_engine/strategy/strategies/workload_balance.py

@@ -290,8 +290,9 @@ class WorkloadBalance(base.WorkloadStabilizationBaseStrategy):
                 util = None
                 try:
                     util = self.datasource_backend.statistic_aggregation(
-                        instance.uuid, self._meter, self._period, 'mean',
-                        granularity=self.granularity)
+                        instance.uuid, self._meter, self._period,
+                        self._granularity, aggregation='mean',
+                        dimensions=dict(resource_id=instance.uuid))
                 except Exception as exc:
                     LOG.exception(exc)
                     LOG.error("Can not get %s from %s", self._meter,
@@ -352,6 +353,7 @@ class WorkloadBalance(base.WorkloadStabilizationBaseStrategy):
         self.threshold = self.input_parameters.threshold
         self._period = self.input_parameters.period
         self._meter = self.input_parameters.metrics
+        self._granularity = self.input_parameters.granularity
         source_nodes, target_nodes, avg_workload, workload_cache = (
             self.group_hosts_by_cpu_or_ram_util())
 

watcher/decision_engine/strategy/strategies/workload_stabilization.py

@@ -198,8 +198,8 @@ class WorkloadStabilization(base.WorkloadStabilizationBaseStrategy):
         instance_load = {'uuid': instance.uuid, 'vcpus': instance.vcpus}
         for meter in self.metrics:
             avg_meter = self.datasource_backend.statistic_aggregation(
-                instance.uuid, meter, self.periods['instance'], 'mean',
-                granularity=self.granularity)
+                instance.uuid, meter, self.periods['instance'],
+                self.granularity, aggregation='mean')
             if avg_meter is None:
                 LOG.warning(
                     "No values returned by %(resource_id)s "
@@ -242,8 +242,7 @@ class WorkloadStabilization(base.WorkloadStabilizationBaseStrategy):
                     resource_id = node_id
                 avg_meter = self.datasource_backend.statistic_aggregation(
                     resource_id, self.instance_metrics[metric],
-                    self.periods['node'], 'mean', granularity=self.granularity)
-
+                    self.periods['node'], self.granularity, aggregation='mean')
                 if avg_meter is None:
                     LOG.warning('No values returned by node %s for %s',
                                 node_id, meter_name)

watcher/decision_engine/strategy/strategies/zone_migration.py

@@ -10,6 +10,14 @@
 # implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
+#
+"""
+*Zone migration using instance and volume migration*
+
+This is zone migration strategy to migrate many instances and volumes
+efficiently with minimum downtime for hardware maintenance.
+
+"""
 
 from dateutil.parser import parse
 import six
@@ -40,6 +48,7 @@ IN_USE = "in-use"
 
 
 class ZoneMigration(base.ZoneMigrationBaseStrategy):
+    """Zone migration using instance and volume migration"""
 
     def __init__(self, config, osc=None):
 
@@ -371,15 +380,6 @@ class ZoneMigration(base.ZoneMigrationBaseStrategy):
         :param pool: pool name
         :returns: host name
         """
-
-        # TODO(hidekazu) use this
-        # mapping = zonemgr.get_host_pool_mapping()
-        # for host, pools in six.iteritems(mapping):
-        #    for _pool in pools:
-        #        if pool == _pool:
-        #            return host
-        # LOG.warning(self.msg_not_exist_corresponding_host % pool)
-        # return pool
         return pool.split('@')[0]
 
     def get_dst_node(self, src_node):

watcher/hacking/checks.py

@@ -60,6 +60,7 @@ log_warn = re.compile(
     r"(.)*LOG\.(warn)\(\s*('|\"|_)")
 unittest_imports_dot = re.compile(r"\bimport[\s]+unittest\b")
 unittest_imports_from = re.compile(r"\bfrom[\s]+unittest\b")
+re_redundant_import_alias = re.compile(r".*import (.+) as \1$")
 
 
 @flake8ext
@@ -271,6 +272,18 @@ def check_builtins_gettext(logical_line, tokens, filename, lines, noqa):
             yield (0, msg)
 
 
+@flake8ext
+def no_redundant_import_alias(logical_line):
+    """Checking no redundant import alias.
+
+    https://bugs.launchpad.net/watcher/+bug/1745527
+
+    N342
+    """
+    if re.match(re_redundant_import_alias, logical_line):
+        yield(0, "N342: No redundant import alias.")
+
+
 def factory(register):
     register(use_jsonutils)
     register(check_assert_called_once_with)
@@ -286,3 +299,4 @@ def factory(register):
     register(check_log_warn_deprecated)
     register(check_oslo_i18n_wrapper)
     register(check_builtins_gettext)
+    register(no_redundant_import_alias)

watcher/locale/en_GB/LC_MESSAGES/watcher.po

@@ -4,11 +4,11 @@ msgid ""
 msgstr ""
 "Project-Id-Version: watcher VERSION\n"
 "Report-Msgid-Bugs-To: https://bugs.launchpad.net/openstack-i18n/\n"
-"POT-Creation-Date: 2018-01-19 11:46+0000\n"
+"POT-Creation-Date: 2018-01-26 00:18+0000\n"
 "MIME-Version: 1.0\n"
 "Content-Type: text/plain; charset=UTF-8\n"
 "Content-Transfer-Encoding: 8bit\n"
-"PO-Revision-Date: 2018-01-19 08:01+0000\n"
+"PO-Revision-Date: 2018-01-27 12:51+0000\n"
 "Last-Translator: Andi Chandler <andi@gowling.com>\n"
 "Language-Team: English (United Kingdom)\n"
 "Language: en-GB\n"
@@ -280,6 +280,10 @@ msgstr "Couldn't apply patch '%(patch)s'. Reason: %(reason)s"
 msgid "Couldn't delete when state is '%(state)s'."
 msgstr "Couldn't delete when state is '%(state)s'."
 
+#, python-format
+msgid "Datasource %(datasource)s is not available."
+msgstr "Datasource %(datasource)s is not available."
+
 #, python-format
 msgid "Datasource %(datasource)s is not supported by strategy %(strategy)s"
 msgstr "Datasource %(datasource)s is not supported by strategy %(strategy)s"
@@ -369,6 +373,9 @@ msgstr "Goal %(goal)s is invalid"
 msgid "Goals"
 msgstr "Goals"
 
+msgid "Hardware Maintenance"
+msgstr "Hardware Maintenance"
+
 #, python-format
 msgid "Here below is a table containing the objects that can be purged%s:"
 msgstr "Here below is a table containing the objects that can be purged%s:"
@@ -506,6 +513,30 @@ msgstr "Provided cron is invalid: %(message)s"
 msgid "Purge results summary%s:"
 msgstr "Purge results summary%s:"
 
+msgid ""
+"Ratio of actual attached volumes migrated to planned attached volumes "
+"migrate."
+msgstr ""
+"Ratio of actual attached volumes migrated to planned attached volumes "
+"migrate."
+
+msgid ""
+"Ratio of actual cold migrated instances to planned cold migrate instances."
+msgstr ""
+"Ratio of actual cold migrated instances to planned cold migrate instances."
+
+msgid ""
+"Ratio of actual detached volumes migrated to planned detached volumes "
+"migrate."
+msgstr ""
+"Ratio of actual detached volumes migrated to planned detached volumes "
+"migrate."
+
+msgid ""
+"Ratio of actual live migrated instances to planned live migrate instances."
+msgstr ""
+"Ratio of actual live migrated instances to planned live migrate instances."
+
 msgid ""
 "Ratio of released compute nodes divided by the total number of enabled "
 "compute nodes."
@@ -561,6 +592,9 @@ msgstr ""
 msgid "State transition not allowed: (%(initial_state)s -> %(new_state)s)"
 msgstr "State transition not allowed: (%(initial_state)s -> %(new_state)s)"
 
+msgid "Storage Capacity Balance Strategy"
+msgstr "Storage Capacity Balance Strategy"
+
 msgid "Strategies"
 msgstr "Strategies"
 
@@ -644,15 +678,42 @@ msgstr "The Ironic node %(uuid)s could not be found"
 msgid "The list of compute node(s) in the cluster is empty"
 msgstr "The list of compute node(s) in the cluster is empty"
 
+msgid "The list of storage node(s) in the cluster is empty"
+msgstr "The list of storage node(s) in the cluster is empty"
+
 msgid "The metrics resource collector is not defined"
 msgstr "The metrics resource collector is not defined"
 
 msgid "The number of VM migrations to be performed."
 msgstr "The number of VM migrations to be performed."
 
+msgid "The number of attached volumes actually migrated."
+msgstr "The number of attached volumes actually migrated."
+
+msgid "The number of attached volumes planned to migrate."
+msgstr "The number of attached volumes planned to migrate."
+
 msgid "The number of compute nodes to be released."
 msgstr "The number of compute nodes to be released."
 
+msgid "The number of detached volumes actually migrated."
+msgstr "The number of detached volumes actually migrated."
+
+msgid "The number of detached volumes planned to migrate."
+msgstr "The number of detached volumes planned to migrate."
+
+msgid "The number of instances actually cold migrated."
+msgstr "The number of instances actually cold migrated."
+
+msgid "The number of instances actually live migrated."
+msgstr "The number of instances actually live migrated."
+
+msgid "The number of instances planned to cold migrate."
+msgstr "The number of instances planned to cold migrate."
+
+msgid "The number of instances planned to live migrate."
+msgstr "The number of instances planned to live migrate."
+
 #, python-format
 msgid ""
 "The number of objects (%(num)s) to delete from the database exceeds the "
@@ -766,6 +827,9 @@ msgstr ""
 "You shouldn't use any other IDs of %(resource)s if you use wildcard "
 "character."
 
+msgid "Zone migration"
+msgstr "Zone migration"
+
 msgid "destination type is required when migration type is swap"
 msgstr "destination type is required when migration type is swap"
 

watcher/notifications/exception.py

@@ -16,7 +16,7 @@ import sys
 import six
 
 from watcher.notifications import base as notificationbase
-from watcher.objects import base as base
+from watcher.objects import base
 from watcher.objects import fields as wfields
 
 

watcher/tests/datasource/test_ceilometer_helper.py

@@ -55,7 +55,8 @@ class TestCeilometerHelper(base.BaseTestCase):
         val = cm.statistic_aggregation(
             resource_id="INSTANCE_ID",
             meter_name="cpu_util",
-            period="7300"
+            period="7300",
+            granularity=None
         )
         self.assertEqual(expected_result, val)
 
@@ -100,7 +101,7 @@ class TestCeilometerHelper(base.BaseTestCase):
         helper = ceilometer_helper.CeilometerHelper()
         helper.get_host_cpu_usage('compute1', 600, 'mean')
         mock_aggregation.assert_called_once_with(
-            'compute1', helper.METRIC_MAP['host_cpu_usage'], 600,
+            'compute1', helper.METRIC_MAP['host_cpu_usage'], 600, None,
             aggregate='mean')
 
     @mock.patch.object(ceilometer_helper.CeilometerHelper,
@@ -109,7 +110,7 @@ class TestCeilometerHelper(base.BaseTestCase):
         helper = ceilometer_helper.CeilometerHelper()
         helper.get_instance_cpu_usage('compute1', 600, 'mean')
         mock_aggregation.assert_called_once_with(
-            'compute1', helper.METRIC_MAP['instance_cpu_usage'], 600,
+            'compute1', helper.METRIC_MAP['instance_cpu_usage'], 600, None,
             aggregate='mean')
 
     @mock.patch.object(ceilometer_helper.CeilometerHelper,
@@ -118,7 +119,7 @@ class TestCeilometerHelper(base.BaseTestCase):
         helper = ceilometer_helper.CeilometerHelper()
         helper.get_host_memory_usage('compute1', 600, 'mean')
         mock_aggregation.assert_called_once_with(
-            'compute1', helper.METRIC_MAP['host_memory_usage'], 600,
+            'compute1', helper.METRIC_MAP['host_memory_usage'], 600, None,
             aggregate='mean')
 
     @mock.patch.object(ceilometer_helper.CeilometerHelper,
@@ -128,7 +129,7 @@ class TestCeilometerHelper(base.BaseTestCase):
         helper = ceilometer_helper.CeilometerHelper()
         helper.get_instance_memory_usage('compute1', 600, 'mean')
         mock_aggregation.assert_called_once_with(
-            'compute1', helper.METRIC_MAP['instance_ram_usage'], 600,
+            'compute1', helper.METRIC_MAP['instance_ram_usage'], 600, None,
             aggregate='mean')
 
     @mock.patch.object(ceilometer_helper.CeilometerHelper,
@@ -139,7 +140,7 @@ class TestCeilometerHelper(base.BaseTestCase):
         helper.get_instance_l3_cache_usage('compute1', 600, 'mean')
         mock_aggregation.assert_called_once_with(
             'compute1', helper.METRIC_MAP['instance_l3_cache_usage'], 600,
-            aggregate='mean')
+            None, aggregate='mean')
 
     @mock.patch.object(ceilometer_helper.CeilometerHelper,
                        'statistic_aggregation')
@@ -148,7 +149,7 @@ class TestCeilometerHelper(base.BaseTestCase):
         helper = ceilometer_helper.CeilometerHelper()
         helper.get_instance_ram_allocated('compute1', 600, 'mean')
         mock_aggregation.assert_called_once_with(
-            'compute1', helper.METRIC_MAP['instance_ram_allocated'], 600,
+            'compute1', helper.METRIC_MAP['instance_ram_allocated'], 600, None,
             aggregate='mean')
 
     @mock.patch.object(ceilometer_helper.CeilometerHelper,
@@ -159,7 +160,7 @@ class TestCeilometerHelper(base.BaseTestCase):
         helper.get_instance_root_disk_allocated('compute1', 600, 'mean')
         mock_aggregation.assert_called_once_with(
             'compute1', helper.METRIC_MAP['instance_root_disk_size'], 600,
-            aggregate='mean')
+            None, aggregate='mean')
 
     @mock.patch.object(ceilometer_helper.CeilometerHelper,
                        'statistic_aggregation')
@@ -168,7 +169,7 @@ class TestCeilometerHelper(base.BaseTestCase):
         helper = ceilometer_helper.CeilometerHelper()
         helper.get_host_outlet_temperature('compute1', 600, 'mean')
         mock_aggregation.assert_called_once_with(
-            'compute1', helper.METRIC_MAP['host_outlet_temp'], 600,
+            'compute1', helper.METRIC_MAP['host_outlet_temp'], 600, None,
             aggregate='mean')
 
     @mock.patch.object(ceilometer_helper.CeilometerHelper,
@@ -178,7 +179,7 @@ class TestCeilometerHelper(base.BaseTestCase):
         helper = ceilometer_helper.CeilometerHelper()
         helper.get_host_inlet_temperature('compute1', 600, 'mean')
         mock_aggregation.assert_called_once_with(
-            'compute1', helper.METRIC_MAP['host_inlet_temp'], 600,
+            'compute1', helper.METRIC_MAP['host_inlet_temp'], 600, None,
             aggregate='mean')
 
     @mock.patch.object(ceilometer_helper.CeilometerHelper,
@@ -187,7 +188,7 @@ class TestCeilometerHelper(base.BaseTestCase):
         helper = ceilometer_helper.CeilometerHelper()
         helper.get_host_airflow('compute1', 600, 'mean')
         mock_aggregation.assert_called_once_with(
-            'compute1', helper.METRIC_MAP['host_airflow'], 600,
+            'compute1', helper.METRIC_MAP['host_airflow'], 600, None,
             aggregate='mean')
 
     @mock.patch.object(ceilometer_helper.CeilometerHelper,
@@ -196,7 +197,7 @@ class TestCeilometerHelper(base.BaseTestCase):
         helper = ceilometer_helper.CeilometerHelper()
         helper.get_host_power('compute1', 600, 'mean')
         mock_aggregation.assert_called_once_with(
-            'compute1', helper.METRIC_MAP['host_power'], 600,
+            'compute1', helper.METRIC_MAP['host_power'], 600, None,
             aggregate='mean')
 
     def test_check_availability(self, mock_ceilometer):

watcher/tests/datasource/test_gnocchi_helper.py

@@ -16,10 +16,8 @@
 
 import mock
 from oslo_config import cfg
-from oslo_utils import timeutils
 
 from watcher.common import clients
-from watcher.common import exception
 from watcher.datasource import gnocchi as gnocchi_helper
 from watcher.tests import base
 
@@ -39,34 +37,17 @@ class TestGnocchiHelper(base.BaseTestCase):
         mock_gnocchi.return_value = gnocchi
 
         helper = gnocchi_helper.GnocchiHelper()
-        result = helper._statistic_aggregation(
+        result = helper.statistic_aggregation(
             resource_id='16a86790-327a-45f9-bc82-45839f062fdc',
-            metric='cpu_util',
+            meter_name='cpu_util',
+            period=300,
             granularity=360,
-            start_time=timeutils.parse_isotime("2017-02-02T09:00:00.000000"),
-            stop_time=timeutils.parse_isotime("2017-02-02T10:00:00.000000"),
-            aggregation='mean'
+            dimensions=None,
+            aggregation='mean',
+            group_by='*'
         )
         self.assertEqual(expected_result, result)
 
-    def test_gnocchi_wrong_datetime(self, mock_gnocchi):
-        gnocchi = mock.MagicMock()
-
-        expected_measures = [["2017-02-02T09:00:00.000000", 360, 5.5]]
-
-        gnocchi.metric.get_measures.return_value = expected_measures
-        mock_gnocchi.return_value = gnocchi
-
-        helper = gnocchi_helper.GnocchiHelper()
-        self.assertRaises(
-            exception.InvalidParameter, helper._statistic_aggregation,
-            resource_id='16a86790-327a-45f9-bc82-45839f062fdc',
-            metric='cpu_util',
-            granularity=360,
-            start_time="2017-02-02T09:00:00.000000",
-            stop_time=timeutils.parse_isotime("2017-02-02T10:00:00.000000"),
-            aggregation='mean')
-
     @mock.patch.object(gnocchi_helper.GnocchiHelper, 'statistic_aggregation')
     def test_get_host_cpu_usage(self, mock_aggregation, mock_gnocchi):
         helper = gnocchi_helper.GnocchiHelper()

watcher/tests/datasource/test_monasca_helper.py

@@ -16,7 +16,6 @@
 
 import mock
 from oslo_config import cfg
-from oslo_utils import timeutils
 
 from watcher.common import clients
 from watcher.datasource import monasca as monasca_helper
@@ -30,7 +29,7 @@ class TestMonascaHelper(base.BaseTestCase):
 
     def test_monasca_statistic_aggregation(self, mock_monasca):
         monasca = mock.MagicMock()
-        expected_result = [{
+        expected_stat = [{
             'columns': ['timestamp', 'avg'],
             'dimensions': {
                 'hostname': 'rdev-indeedsrv001',
@@ -39,23 +38,23 @@ class TestMonascaHelper(base.BaseTestCase):
             'name': 'cpu.percent',
             'statistics': [
                 ['2016-07-29T12:45:00Z', 0.0],
-                ['2016-07-29T12:50:00Z', 0.9100000000000001],
-                ['2016-07-29T12:55:00Z', 0.9111111111111112]]}]
+                ['2016-07-29T12:50:00Z', 0.9],
+                ['2016-07-29T12:55:00Z', 0.9]]}]
 
-        monasca.metrics.list_statistics.return_value = expected_result
+        monasca.metrics.list_statistics.return_value = expected_stat
         mock_monasca.return_value = monasca
 
         helper = monasca_helper.MonascaHelper()
         result = helper.statistic_aggregation(
+            resource_id=None,
             meter_name='cpu.percent',
-            dimensions={'hostname': 'NODE_UUID'},
-            start_time=timeutils.parse_isotime("2016-06-06T10:33:22.063176"),
-            end_time=None,
             period=7200,
-            aggregate='avg',
+            granularity=300,
+            dimensions={'hostname': 'NODE_UUID'},
+            aggregation='avg',
             group_by='*',
         )
-        self.assertEqual(expected_result, result)
+        self.assertEqual(0.6, result)
 
     def test_check_availability(self, mock_monasca):
         monasca = mock.MagicMock()
@@ -117,34 +116,14 @@ class TestMonascaHelper(base.BaseTestCase):
     @mock.patch.object(monasca_helper.MonascaHelper, 'statistic_aggregation')
     def test_get_host_cpu_usage(self, mock_aggregation, mock_monasca):
         node = "compute1_compute1"
-        mock_aggregation.return_value = [{
-            'columns': ['timestamp', 'avg'],
-            'dimensions': {
-                'hostname': 'rdev-indeedsrv001',
-                'service': 'monasca'},
-            'id': '0',
-            'name': 'cpu.percent',
-            'statistics': [
-                ['2016-07-29T12:45:00Z', 0.0],
-                ['2016-07-29T12:50:00Z', 0.9],
-                ['2016-07-29T12:55:00Z', 0.9]]}]
+        mock_aggregation.return_value = 0.6
         helper = monasca_helper.MonascaHelper()
         cpu_usage = helper.get_host_cpu_usage(node, 600, 'mean')
         self.assertEqual(0.6, cpu_usage)
 
     @mock.patch.object(monasca_helper.MonascaHelper, 'statistic_aggregation')
     def test_get_instance_cpu_usage(self, mock_aggregation, mock_monasca):
-        mock_aggregation.return_value = [{
-            'columns': ['timestamp', 'avg'],
-            'dimensions': {
-                'name': 'vm1',
-                'service': 'monasca'},
-            'id': '0',
-            'name': 'cpu.percent',
-            'statistics': [
-                ['2016-07-29T12:45:00Z', 0.0],
-                ['2016-07-29T12:50:00Z', 0.9],
-                ['2016-07-29T12:55:00Z', 0.9]]}]
+        mock_aggregation.return_value = 0.6
         helper = monasca_helper.MonascaHelper()
         cpu_usage = helper.get_instance_cpu_usage('vm1', 600, 'mean')
         self.assertEqual(0.6, cpu_usage)

watcher/tests/decision_engine/model/ceilometer_metrics.py

@@ -26,14 +26,9 @@ class FakeCeilometerMetrics(object):
     def empty_one_metric(self, emptytype):
         self.emptytype = emptytype
 
-    # TODO(alexchadin): This method is added as temporary solution until
-    # all strategies use datasource_backend property.
-    def temp_mock_get_statistics(self, resource_id, meter_name, period,
-                                 aggregate, granularity=300):
-        return self.mock_get_statistics(resource_id, meter_name, period)
-
-    def mock_get_statistics(self, resource_id, meter_name, period,
-                            aggregate='avg'):
+    def mock_get_statistics(self, resource_id=None, meter_name=None,
+                            period=None, granularity=None, dimensions=None,
+                            aggregation='avg', group_by='*'):
         result = 0
         if meter_name == "hardware.cpu.util":
             result = self.get_usage_node_cpu(resource_id)
@@ -56,7 +51,8 @@ class FakeCeilometerMetrics(object):
         return result
 
     def mock_get_statistics_wb(self, resource_id, meter_name, period,
-                               aggregate, granularity=300):
+                               granularity, dimensions=None,
+                               aggregation='avg', group_by='*'):
         result = 0.0
         if meter_name == "cpu_util":
             result = self.get_average_usage_instance_cpu_wb(resource_id)

watcher/tests/decision_engine/model/faker_cluster_and_metrics.py

@@ -84,8 +84,9 @@ class FakeCeilometerMetrics(object):
     def __init__(self, model):
         self.model = model
 
-    def mock_get_statistics(self, resource_id, meter_name, period=3600,
-                            aggregate='avg'):
+    def mock_get_statistics(self, resource_id=None, meter_name=None,
+                            period=300, granularity=300, dimensions=None,
+                            aggregation='avg', group_by='*'):
         if meter_name == "compute.node.cpu.percent":
             return self.get_node_cpu_util(resource_id)
         elif meter_name == "cpu_util":
@@ -166,15 +167,16 @@ class FakeGnocchiMetrics(object):
     def __init__(self, model):
         self.model = model
 
-    def mock_get_statistics(self, resource_id, metric, granularity,
-                            start_time, stop_time, aggregation='mean'):
-        if metric == "compute.node.cpu.percent":
+    def mock_get_statistics(self, resource_id=None, meter_name=None,
+                            period=300, granularity=300, dimensions=None,
+                            aggregation='avg', group_by='*'):
+        if meter_name == "compute.node.cpu.percent":
             return self.get_node_cpu_util(resource_id)
-        elif metric == "cpu_util":
+        elif meter_name == "cpu_util":
             return self.get_instance_cpu_util(resource_id)
-        elif metric == "memory.resident":
+        elif meter_name == "memory.resident":
             return self.get_instance_ram_util(resource_id)
-        elif metric == "disk.root.size":
+        elif meter_name == "disk.root.size":
             return self.get_instance_disk_root_size(resource_id)
 
     def get_node_cpu_util(self, r_id):

watcher/tests/decision_engine/model/gnocchi_metrics.py

@@ -21,17 +21,10 @@ class FakeGnocchiMetrics(object):
     def empty_one_metric(self, emptytype):
         self.emptytype = emptytype
 
-    # TODO(alexchadin): This method is added as temporary solution until
-    # all strategies use datasource_backend property.
-    def temp_mock_get_statistics(self, resource_id, metric, period, aggregate,
-                                 granularity=300):
-        return self.mock_get_statistics(resource_id, metric, granularity,
-                                        0, 0, aggregation='mean')
-
-    def mock_get_statistics(self, resource_id, metric, granularity,
-                            start_time, stop_time, aggregation='mean'):
+    def mock_get_statistics(self, resource_id=None, meter_name=None,
+                            period=None, granularity=None, dimensions=None,
+                            aggregation='avg', group_by='*'):
         result = 0
-        meter_name = metric
         if meter_name == "hardware.cpu.util":
             result = self.get_usage_node_cpu(resource_id)
         elif meter_name == "compute.node.cpu.percent":
@@ -87,12 +80,13 @@ class FakeGnocchiMetrics(object):
             mock[uuid] = 25 * oslo_utils.units.Ki
         return mock[str(uuid)]
 
-    def mock_get_statistics_wb(self, resource_id, metric, period, aggregate,
-                               granularity=300):
+    def mock_get_statistics_wb(self, resource_id, meter_name, period,
+                               granularity, dimensions=None,
+                               aggregation='avg', group_by='*'):
         result = 0.0
-        if metric == "cpu_util":
+        if meter_name == "cpu_util":
             result = self.get_average_usage_instance_cpu_wb(resource_id)
-        elif metric == "memory.resident":
+        elif meter_name == "memory.resident":
             result = self.get_average_usage_instance_memory_wb(resource_id)
         return result
 

watcher/tests/decision_engine/model/monasca_metrics.py

@@ -26,15 +26,9 @@ class FakeMonascaMetrics(object):
     def empty_one_metric(self, emptytype):
         self.emptytype = emptytype
 
-    # This method is added as temporary solution until all strategies use
-    # datasource_backend property
-    def temp_mock_get_statistics(self, metric, dimensions, period,
-                                 aggregate='avg', granularity=300):
-        return self.mock_get_statistics(metric, dimensions,
-                                        period, aggregate='avg')
-
-    def mock_get_statistics(self, meter_name, dimensions, period,
-                            aggregate='avg'):
+    def mock_get_statistics(self, resource_id=None, meter_name=None,
+                            period=None, granularity=None, dimensions=None,
+                            aggregation='avg', group_by='*'):
         resource_id = dimensions.get(
             "resource_id") or dimensions.get("hostname")
         result = 0.0

watcher/tests/decision_engine/strategy/strategies/test_outlet_temp_control.py

@@ -17,7 +17,6 @@
 # limitations under the License.
 #
 import collections
-import datetime
 import mock
 
 from watcher.applier.loading import default
@@ -57,7 +56,7 @@ class TestOutletTempControl(base.TestCase):
         self.addCleanup(p_model.stop)
 
         p_datasource = mock.patch.object(
-            strategies.OutletTempControl, self.datasource,
+            strategies.OutletTempControl, 'datasource_backend',
             new_callable=mock.PropertyMock)
         self.m_datasource = p_datasource.start()
         self.addCleanup(p_datasource.stop)
@@ -164,44 +163,3 @@ class TestOutletTempControl(base.TestCase):
             loaded_action = loader.load(action['action_type'])
             loaded_action.input_parameters = action['input_parameters']
             loaded_action.validate_parameters()
-
-    def test_periods(self):
-        model = self.fake_cluster.generate_scenario_3_with_2_nodes()
-        self.m_model.return_value = model
-        p_ceilometer = mock.patch.object(
-            strategies.OutletTempControl, "ceilometer")
-        m_ceilometer = p_ceilometer.start()
-        self.addCleanup(p_ceilometer.stop)
-        p_gnocchi = mock.patch.object(strategies.OutletTempControl, "gnocchi")
-        m_gnocchi = p_gnocchi.start()
-        self.addCleanup(p_gnocchi.stop)
-        datetime_patcher = mock.patch.object(
-            datetime, 'datetime',
-            mock.Mock(wraps=datetime.datetime)
-        )
-        mocked_datetime = datetime_patcher.start()
-        mocked_datetime.utcnow.return_value = datetime.datetime(
-            2017, 3, 19, 18, 53, 11, 657417)
-        self.addCleanup(datetime_patcher.stop)
-        m_ceilometer.statistic_aggregation = mock.Mock(
-            side_effect=self.fake_metrics.mock_get_statistics)
-        m_gnocchi.statistic_aggregation = mock.Mock(
-            side_effect=self.fake_metrics.mock_get_statistics)
-        node = model.get_node_by_uuid('Node_0')
-        self.strategy.input_parameters.update({'threshold': 35.0})
-        self.strategy.threshold = 35.0
-        self.strategy.group_hosts_by_outlet_temp()
-        if self.strategy.config.datasource == "ceilometer":
-            m_ceilometer.statistic_aggregation.assert_any_call(
-                aggregate='avg',
-                meter_name='hardware.ipmi.node.outlet_temperature',
-                period=30, resource_id=node.uuid)
-        elif self.strategy.config.datasource == "gnocchi":
-            stop_time = datetime.datetime.utcnow()
-            start_time = stop_time - datetime.timedelta(
-                seconds=int('30'))
-            m_gnocchi.statistic_aggregation.assert_called_with(
-                resource_id=mock.ANY,
-                metric='hardware.ipmi.node.outlet_temperature',
-                granularity=300, start_time=start_time, stop_time=stop_time,
-                aggregation='mean')

watcher/tests/decision_engine/strategy/strategies/test_strategy_endpoint.py

@@ -42,7 +42,7 @@ class TestStrategyEndpoint(base.BaseTestCase):
     def test_get_datasource_status(self):
         strategy = mock.MagicMock()
         datasource = mock.MagicMock()
-        strategy.config.datasource = "gnocchi"
+        datasource.NAME = 'gnocchi'
         datasource.check_availability.return_value = "available"
         se = strategy_base.StrategyEndpoint(mock.MagicMock())
         result = se._get_datasource_status(strategy, datasource)

watcher/tests/decision_engine/strategy/strategies/test_uniform_airflow.py

@@ -17,7 +17,6 @@
 # limitations under the License.
 #
 import collections
-import datetime
 import mock
 
 from watcher.applier.loading import default
@@ -56,7 +55,7 @@ class TestUniformAirflow(base.TestCase):
         self.addCleanup(p_model.stop)
 
         p_datasource = mock.patch.object(
-            strategies.UniformAirflow, self.datasource,
+            strategies.UniformAirflow, 'datasource_backend',
             new_callable=mock.PropertyMock)
         self.m_datasource = p_datasource.start()
         self.addCleanup(p_datasource.stop)
@@ -211,39 +210,3 @@ class TestUniformAirflow(base.TestCase):
             loaded_action = loader.load(action['action_type'])
             loaded_action.input_parameters = action['input_parameters']
             loaded_action.validate_parameters()
-
-    def test_periods(self):
-        model = self.fake_cluster.generate_scenario_7_with_2_nodes()
-        self.m_model.return_value = model
-        p_ceilometer = mock.patch.object(
-            strategies.UniformAirflow, "ceilometer")
-        m_ceilometer = p_ceilometer.start()
-        self.addCleanup(p_ceilometer.stop)
-        p_gnocchi = mock.patch.object(strategies.UniformAirflow, "gnocchi")
-        m_gnocchi = p_gnocchi.start()
-        self.addCleanup(p_gnocchi.stop)
-        datetime_patcher = mock.patch.object(
-            datetime, 'datetime',
-            mock.Mock(wraps=datetime.datetime)
-        )
-        mocked_datetime = datetime_patcher.start()
-        mocked_datetime.utcnow.return_value = datetime.datetime(
-            2017, 3, 19, 18, 53, 11, 657417)
-        self.addCleanup(datetime_patcher.stop)
-        m_ceilometer.statistic_aggregation = mock.Mock(
-            side_effect=self.fake_metrics.mock_get_statistics)
-        m_gnocchi.statistic_aggregation = mock.Mock(
-            side_effect=self.fake_metrics.mock_get_statistics)
-        self.strategy.group_hosts_by_airflow()
-        if self.strategy.config.datasource == "ceilometer":
-            m_ceilometer.statistic_aggregation.assert_any_call(
-                aggregate='avg', meter_name='hardware.ipmi.node.airflow',
-                period=300, resource_id=mock.ANY)
-        elif self.strategy.config.datasource == "gnocchi":
-            stop_time = datetime.datetime.utcnow()
-            start_time = stop_time - datetime.timedelta(
-                seconds=int('300'))
-            m_gnocchi.statistic_aggregation.assert_called_with(
-                resource_id=mock.ANY, metric='hardware.ipmi.node.airflow',
-                granularity=300, start_time=start_time, stop_time=stop_time,
-                aggregation='mean')

watcher/tests/decision_engine/strategy/strategies/test_vm_workload_consolidation.py

@@ -18,7 +18,6 @@
 # limitations under the License.
 #
 
-import datetime
 import mock
 
 from watcher.common import exception
@@ -55,7 +54,7 @@ class TestVMWorkloadConsolidation(base.TestCase):
         self.addCleanup(p_model.stop)
 
         p_datasource = mock.patch.object(
-            strategies.VMWorkloadConsolidation, self.datasource,
+            strategies.VMWorkloadConsolidation, 'datasource_backend',
             new_callable=mock.PropertyMock)
         self.m_datasource = p_datasource.start()
         self.addCleanup(p_datasource.stop)
@@ -333,41 +332,3 @@ class TestVMWorkloadConsolidation(base.TestCase):
         del expected[3]
         del expected[1]
         self.assertEqual(expected, self.strategy.solution.actions)
-
-    def test_periods(self):
-        model = self.fake_cluster.generate_scenario_1()
-        self.m_model.return_value = model
-        p_ceilometer = mock.patch.object(
-            strategies.VMWorkloadConsolidation, "ceilometer")
-        m_ceilometer = p_ceilometer.start()
-        self.addCleanup(p_ceilometer.stop)
-        p_gnocchi = mock.patch.object(
-            strategies.VMWorkloadConsolidation, "gnocchi")
-        m_gnocchi = p_gnocchi.start()
-        self.addCleanup(p_gnocchi.stop)
-        datetime_patcher = mock.patch.object(
-            datetime, 'datetime',
-            mock.Mock(wraps=datetime.datetime)
-        )
-        mocked_datetime = datetime_patcher.start()
-        mocked_datetime.utcnow.return_value = datetime.datetime(
-            2017, 3, 19, 18, 53, 11, 657417)
-        self.addCleanup(datetime_patcher.stop)
-        m_ceilometer.return_value = mock.Mock(
-            statistic_aggregation=self.fake_metrics.mock_get_statistics)
-        m_gnocchi.return_value = mock.Mock(
-            statistic_aggregation=self.fake_metrics.mock_get_statistics)
-        instance0 = model.get_instance_by_uuid("INSTANCE_0")
-        self.strategy.get_instance_utilization(instance0)
-        if self.strategy.config.datasource == "ceilometer":
-            m_ceilometer.statistic_aggregation.assert_any_call(
-                aggregate='avg', meter_name='disk.root.size',
-                period=3600, resource_id=instance0.uuid)
-        elif self.strategy.config.datasource == "gnocchi":
-            stop_time = datetime.datetime.utcnow()
-            start_time = stop_time - datetime.timedelta(
-                seconds=int('3600'))
-            m_gnocchi.statistic_aggregation.assert_called_with(
-                resource_id=instance0.uuid, metric='disk.root.size',
-                granularity=300, start_time=start_time, stop_time=stop_time,
-                aggregation='mean')

watcher/tests/decision_engine/strategy/strategies/test_workload_balance.py

@@ -75,10 +75,12 @@ class TestWorkloadBalance(base.TestCase):
         self.strategy.input_parameters = utils.Struct()
         self.strategy.input_parameters.update({'metrics': 'cpu_util',
                                                'threshold': 25.0,
-                                               'period': 300})
+                                               'period': 300,
+                                               'granularity': 300})
         self.strategy.threshold = 25.0
         self.strategy._period = 300
         self.strategy._meter = "cpu_util"
+        self.strategy._granularity = 300
 
     def test_calc_used_resource(self):
         model = self.fake_cluster.generate_scenario_6_with_2_nodes()

watcher/tests/decision_engine/strategy/strategies/test_workload_stabilization.py

@@ -83,7 +83,7 @@ class TestWorkloadStabilization(base.TestCase):
         self.m_model.return_value = model_root.ModelRoot()
         self.m_audit_scope.return_value = mock.Mock()
         self.m_datasource.return_value = mock.Mock(
-            statistic_aggregation=self.fake_metrics.temp_mock_get_statistics)
+            statistic_aggregation=self.fake_metrics.mock_get_statistics)
 
         self.strategy = strategies.WorkloadStabilization(
             config=mock.Mock(datasource=self.datasource))