Add periods input parameter

This patch set adds new periods strategy input
parameter that allows to specify the time length of
statistic aggregation.

Change-Id: Id6c7900e7b909b0b325281c4038e07dc695847a1

doc/source/strategies/workload-stabilization.rst

@@ -92,12 +92,22 @@ parameter            type   default Value         description
                                                   host from list.
 ``retry_count``      number 1                     Count of random returned
                                                   hosts.
+``periods``          object |periods|             These periods are used to get
+                                                  statistic aggregation for
+                                                  instance and host metrics.
+                                                  The period is simply a
+                                                  repeating interval of time
+                                                  into which the samples are
+                                                  grouped for aggregation.
+                                                  Watcher uses only the last
+                                                  period of all recieved ones.
 ==================== ====== ===================== =============================
 
 .. |metrics| replace:: ["cpu_util", "memory.resident"]
 .. |thresholds| replace:: {"cpu_util": 0.2, "memory.resident": 0.2}
 .. |weights| replace:: {"cpu_util_weight": 1.0, "memory.resident_weight": 1.0}
 .. |instance_metrics| replace:: {"cpu_util": "compute.node.cpu.percent", "memory.resident": "hardware.memory.used"}
+.. |periods| replace:: {"instance": 720, "node": 600}
 
 Efficacy Indicator
 ------------------

watcher/decision_engine/strategy/strategies/workload_stabilization.py

@@ -80,6 +80,7 @@ class WorkloadStabilization(base.WorkloadStabilizationBaseStrategy):
         self.host_choice = None
         self.instance_metrics = None
         self.retry_count = None
+        self.periods = None
 
     @classmethod
     def get_name(cls):
@@ -138,6 +139,17 @@ class WorkloadStabilization(base.WorkloadStabilizationBaseStrategy):
                     "description": "Count of random returned hosts",
                     "type": "number",
                     "default": 1
+                },
+                "periods": {
+                    "description": "These periods are used to get statistic "
+                                   "aggregation for instance and host "
+                                   "metrics. The period is simply a repeating"
+                                   " interval of time into which the samples"
+                                   " are grouped for aggregation. Watcher "
+                                   "uses only the last period of all recieved"
+                                   " ones.",
+                    "type": "object",
+                    "default": {"instance": 720, "node": 600}
                 }
             }
         }
@@ -190,7 +202,7 @@ class WorkloadStabilization(base.WorkloadStabilizationBaseStrategy):
             avg_meter = self.ceilometer.statistic_aggregation(
                 resource_id=instance_uuid,
                 meter_name=meter,
-                period="120",
+                period=self.periods['instance'],
                 aggregate='min'
             )
             if avg_meter is None:
@@ -244,7 +256,7 @@ class WorkloadStabilization(base.WorkloadStabilizationBaseStrategy):
                 avg_meter = self.ceilometer.statistic_aggregation(
                     resource_id=resource_id,
                     meter_name=self.instance_metrics[metric],
-                    period="60",
+                    period=self.periods['node'],
                     aggregate='avg'
                 )
                 if avg_meter is None:
@@ -414,6 +426,7 @@ class WorkloadStabilization(base.WorkloadStabilizationBaseStrategy):
         self.host_choice = self.input_parameters.host_choice
         self.instance_metrics = self.input_parameters.instance_metrics
         self.retry_count = self.input_parameters.retry_count
+        self.periods = self.input_parameters.periods
 
     def do_execute(self):
         migration = self.check_threshold()

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

@@ -79,7 +79,8 @@ class TestWorkloadStabilization(base.TestCase):
                  {"cpu_util": "compute.node.cpu.percent",
                   "memory.resident": "hardware.memory.used"},
              'host_choice': 'retry',
-             'retry_count': 1})
+             'retry_count': 1,
+             'periods': {"instance": 720, "node": 600}})
         self.strategy.metrics = ["cpu_util", "memory.resident"]
         self.strategy.thresholds = {"cpu_util": 0.2, "memory.resident": 0.2}
         self.strategy.weights = {"cpu_util_weight": 1.0,
@@ -89,6 +90,7 @@ class TestWorkloadStabilization(base.TestCase):
             "memory.resident": "hardware.memory.used"}
         self.strategy.host_choice = 'retry'
         self.strategy.retry_count = 1
+        self.strategy.periods = {"instance": 720, "node": 600}
 
     def test_get_instance_load(self):
         self.m_model.return_value = self.fake_cluster.generate_scenario_1()
@@ -98,6 +100,23 @@ class TestWorkloadStabilization(base.TestCase):
         self.assertEqual(
             instance_0_dict, self.strategy.get_instance_load("INSTANCE_0"))
 
+    def test_periods(self):
+        self.m_model.return_value = self.fake_cluster.generate_scenario_1()
+        p_ceilometer = mock.patch.object(
+            strategies.WorkloadStabilization, "ceilometer")
+        m_ceilometer = p_ceilometer.start()
+        self.addCleanup(p_ceilometer.stop)
+        m_ceilometer.return_value = mock.Mock(
+            statistic_aggregation=self.fake_metrics.mock_get_statistics)
+        self.strategy.get_instance_load("INSTANCE_0")
+        m_ceilometer.statistic_aggregation.assert_called_with(
+            aggregate='min', meter_name='memory.resident',
+            period=720, resource_id='INSTANCE_0')
+        self.strategy.get_hosts_load()
+        m_ceilometer.statistic_aggregation.assert_called_with(
+            aggregate='avg', meter_name='hardware.memory.used',
+            period=600, resource_id=mock.ANY)
+
     def test_normalize_hosts_load(self):
         self.m_model.return_value = self.fake_cluster.generate_scenario_1()
         fake_hosts = {'Node_0': {'cpu_util': 0.07, 'memory.resident': 7},