Add gnocchi support in workload_balance strategy

This patch adds gnocchi support in workload_balance strategy
and adds unit tests corresponding to that change.

Change-Id: I9bc56c7b91b5c3fd0cfe97d75c3bace50ab22532
Partiallly-Implements: bp gnocchi-watcher

watcher/decision_engine/strategy/strategies/workload_balance.py

@@ -46,12 +46,15 @@ hosts nodes.
   algorithm with `CONTINUOUS` audits.
 """
 
+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
 
@@ -104,6 +107,7 @@ class WorkloadBalance(base.WorkloadStabilizationBaseStrategy):
         # reaches threshold
         self._meter = self.METER_NAME
         self._ceilometer = None
+        self._gnocchi = None
 
     @property
     def ceilometer(self):
@@ -115,6 +119,16 @@ class WorkloadBalance(base.WorkloadStabilizationBaseStrategy):
     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, gnocchi):
+        self._gnocchi = gnocchi
+
     @classmethod
     def get_name(cls):
         return "workload_balance"
@@ -127,6 +141,10 @@ class WorkloadBalance(base.WorkloadStabilizationBaseStrategy):
     def get_translatable_display_name(cls):
         return "Workload Balance Migration Strategy"
 
+    @property
+    def granularity(self):
+        return self.input_parameters.get('granularity', 300)
+
     @classmethod
     def get_schema(cls):
         # Mandatory default setting for each element
@@ -142,9 +160,25 @@ class WorkloadBalance(base.WorkloadStabilizationBaseStrategy):
                     "type": "number",
                     "default": 300
                 },
+                "granularity": {
+                    "description": "The time between two measures in an "
+                                   "aggregated timeseries of a metric.",
+                    "type": "number",
+                    "default": 300
+                },
             },
         }
 
+    @classmethod
+    def get_config_opts(cls):
+        return [
+            cfg.StrOpt(
+                "datasource",
+                help="Data source to use in order to query the needed metrics",
+                default="ceilometer",
+                choices=["ceilometer", "gnocchi"])
+        ]
+
     def calculate_used_resource(self, node):
         """Calculate the used vcpus, memory and disk based on VM flavors"""
         instances = self.compute_model.get_node_instances(node)
@@ -251,15 +285,30 @@ class WorkloadBalance(base.WorkloadStabilizationBaseStrategy):
             instances = self.compute_model.get_node_instances(node)
             node_workload = 0.0
             for instance in instances:
+                cpu_util = None
                 try:
-                    cpu_util = self.ceilometer.statistic_aggregation(
+                    if self.config.datasource == "ceilometer":
-                        resource_id=instance.uuid,
+                        cpu_util = self.ceilometer.statistic_aggregation(
-                        meter_name=self._meter,
+                            resource_id=instance.uuid,
-                        period=self._period,
+                            meter_name=self._meter,
-                        aggregate='avg')
+                            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))
+                        cpu_util = self.gnocchi.statistic_aggregation(
+                            resource_id=instance.uuid,
+                            metric=self._meter,
+                            granularity=self.granularity,
+                            start_time=start_time,
+                            stop_time=stop_time,
+                            aggregation='mean'
+                        )
                 except Exception as exc:
                     LOG.exception(exc)
-                    LOG.error("Can not get cpu_util from Ceilometer")
+                    LOG.error("Can not get cpu_util from %s",
+                              self.config.datasource)
                     continue
                 if cpu_util is None:
                     LOG.debug("Instance (%s): cpu_util is None", instance.uuid)

watcher/tests/decision_engine/model/gnocchi_metrics.py

@@ -45,6 +45,13 @@ class FakeGnocchiMetrics(object):
             result = self.get_average_power(resource_id)
         return result
 
+    def mock_get_statistics_wb(self, resource_id, metric, granularity,
+                               start_time, stop_time, aggregation='mean'):
+        result = 0.0
+        if metric == "cpu_util":
+            result = self.get_average_usage_instance_cpu_wb(resource_id)
+        return result
+
     @staticmethod
     def get_average_outlet_temperature(uuid):
         """The average outlet temperature for host"""
@@ -106,8 +113,8 @@ class FakeGnocchiMetrics(object):
     def get_usage_node_cpu(uuid):
         """The last VM CPU usage values to average
 
-        :param uuid:00
+        :param uuid: instance UUID
-        :return:
+        :return: float value
         """
         # Normalize
         mock = {}
@@ -142,8 +149,8 @@ class FakeGnocchiMetrics(object):
     def get_average_usage_instance_cpu(uuid):
         """The last VM CPU usage values to average
 
-        :param uuid:00
+        :param uuid: instance UUID
-        :return:
+        :return: int value
         """
 
         # Normalize
@@ -214,3 +221,24 @@ class FakeGnocchiMetrics(object):
             mock[uuid] = 4
 
         return mock[str(uuid)]
+
+    @staticmethod
+    def get_average_usage_instance_cpu_wb(uuid):
+        """The last VM CPU usage values to average
+
+        :param uuid: instance UUID
+        :return: float value
+        """
+        # query influxdb stream
+
+        # compute in stream
+
+        # Normalize
+        mock = {}
+        # node 0
+        mock['INSTANCE_1'] = 80
+        mock['73b09e16-35b7-4922-804e-e8f5d9b740fc'] = 50
+        # node 1
+        mock['INSTANCE_3'] = 20
+        mock['INSTANCE_4'] = 10
+        return float(mock[str(uuid)])

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

@@ -17,6 +17,7 @@
 # limitations under the License.
 #
 import collections
+import datetime
 import mock
 
 from watcher.applier.loading import default
@@ -27,14 +28,24 @@ from watcher.decision_engine.strategy import strategies
 from watcher.tests import base
 from watcher.tests.decision_engine.model import ceilometer_metrics
 from watcher.tests.decision_engine.model import faker_cluster_state
+from watcher.tests.decision_engine.model import gnocchi_metrics
 
 
 class TestWorkloadBalance(base.TestCase):
 
+    scenarios = [
+        ("Ceilometer",
+         {"datasource": "ceilometer",
+          "fake_datasource_cls": ceilometer_metrics.FakeCeilometerMetrics}),
+        ("Gnocchi",
+         {"datasource": "gnocchi",
+          "fake_datasource_cls": gnocchi_metrics.FakeGnocchiMetrics}),
+    ]
+
     def setUp(self):
         super(TestWorkloadBalance, self).setUp()
         # fake metrics
-        self.fake_metrics = ceilometer_metrics.FakeCeilometerMetrics()
+        self.fake_metrics = self.fake_datasource_cls()
         # fake cluster
         self.fake_cluster = faker_cluster_state.FakerModelCollector()
 
@@ -44,11 +55,11 @@ class TestWorkloadBalance(base.TestCase):
         self.m_model = p_model.start()
         self.addCleanup(p_model.stop)
 
-        p_ceilometer = mock.patch.object(
+        p_datasource = mock.patch.object(
-            strategies.WorkloadBalance, "ceilometer",
+            strategies.WorkloadBalance, self.datasource,
             new_callable=mock.PropertyMock)
-        self.m_ceilometer = p_ceilometer.start()
+        self.m_datasource = p_datasource.start()
-        self.addCleanup(p_ceilometer.stop)
+        self.addCleanup(p_datasource.stop)
 
         p_audit_scope = mock.patch.object(
             strategies.WorkloadBalance, "audit_scope",
@@ -58,11 +69,10 @@ class TestWorkloadBalance(base.TestCase):
         self.addCleanup(p_audit_scope.stop)
 
         self.m_audit_scope.return_value = mock.Mock()
-
+        self.m_datasource.return_value = mock.Mock(
-        self.m_model.return_value = model_root.ModelRoot()
-        self.m_ceilometer.return_value = mock.Mock(
             statistic_aggregation=self.fake_metrics.mock_get_statistics_wb)
-        self.strategy = strategies.WorkloadBalance(config=mock.Mock())
+        self.strategy = strategies.WorkloadBalance(
+            config=mock.Mock(datasource=self.datasource))
         self.strategy.input_parameters = utils.Struct()
         self.strategy.input_parameters.update({'threshold': 25.0,
                                                'period': 300})
@@ -110,7 +120,7 @@ class TestWorkloadBalance(base.TestCase):
     def test_filter_destination_hosts(self):
         model = self.fake_cluster.generate_scenario_6_with_2_nodes()
         self.m_model.return_value = model
-        self.strategy.ceilometer = mock.MagicMock(
+        self.strategy.datasource = mock.MagicMock(
             statistic_aggregation=self.fake_metrics.mock_get_statistics_wb)
         n1, n2, avg, w_map = self.strategy.group_hosts_by_cpu_util()
         instance_to_mig = self.strategy.choose_instance_to_migrate(
@@ -168,3 +178,40 @@ class TestWorkloadBalance(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_1()
+        self.m_model.return_value = model
+        p_ceilometer = mock.patch.object(
+            strategies.WorkloadBalance, "ceilometer")
+        m_ceilometer = p_ceilometer.start()
+        self.addCleanup(p_ceilometer.stop)
+        p_gnocchi = mock.patch.object(strategies.WorkloadBalance, "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_wb)
+        m_gnocchi.statistic_aggregation = mock.Mock(
+            side_effect=self.fake_metrics.mock_get_statistics_wb)
+        instance0 = model.get_instance_by_uuid("INSTANCE_0")
+        self.strategy.group_hosts_by_cpu_util()
+        if self.strategy.config.datasource == "ceilometer":
+            m_ceilometer.statistic_aggregation.assert_any_call(
+                aggregate='avg', meter_name='cpu_util',
+                period=300, resource_id=instance0.uuid)
+        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='cpu_util',
+                granularity=300, start_time=start_time, stop_time=stop_time,
+                aggregation='mean')