Merge "Noisy Neighbor Strategy"

setup.cfg

@@ -53,6 +53,7 @@ watcher_goals =
     thermal_optimization = watcher.decision_engine.goal.goals:ThermalOptimization
     workload_balancing = watcher.decision_engine.goal.goals:WorkloadBalancing
     airflow_optimization = watcher.decision_engine.goal.goals:AirflowOptimization
+    noisy_neighbor = watcher.decision_engine.goal.goals:NoisyNeighborOptimization
 
 watcher_scoring_engines =
     dummy_scorer = watcher.decision_engine.scoring.dummy_scorer:DummyScorer
@@ -70,6 +71,7 @@ watcher_strategies =
     workload_stabilization = watcher.decision_engine.strategy.strategies.workload_stabilization:WorkloadStabilization
     workload_balance = watcher.decision_engine.strategy.strategies.workload_balance:WorkloadBalance
     uniform_airflow = watcher.decision_engine.strategy.strategies.uniform_airflow:UniformAirflow
+    noisy_neighbor = watcher.decision_engine.strategy.strategies.noisy_neighbor:NoisyNeighbor
 
 watcher_actions =
     migrate = watcher.applier.actions.migration:Migrate

watcher/decision_engine/goal/__init__.py

@@ -21,6 +21,8 @@ ServerConsolidation = goals.ServerConsolidation
 ThermalOptimization = goals.ThermalOptimization
 Unclassified = goals.Unclassified
 WorkloadBalancing = goals.WorkloadBalancing
+NoisyNeighbor = goals.NoisyNeighborOptimization
 
 __all__ = ("Dummy", "ServerConsolidation", "ThermalOptimization",
-           "Unclassified", "WorkloadBalancing", )
+           "Unclassified", "WorkloadBalancing",
+           "NoisyNeighborOptimization",)

watcher/decision_engine/goal/goals.py

@@ -166,3 +166,29 @@ class AirflowOptimization(base.Goal):
     def get_efficacy_specification(cls):
         """The efficacy spec for the current goal"""
         return specs.Unclassified()
+
+
+class NoisyNeighborOptimization(base.Goal):
+    """NoisyNeighborOptimization
+
+    This goal is used to identify and migrate a Noisy Neighbor -
+    a low priority VM that negatively affects peformance of a high priority VM
+    in terms of IPC by over utilizing Last Level Cache.
+    """
+
+    @classmethod
+    def get_name(cls):
+        return "noisy_neighbor"
+
+    @classmethod
+    def get_display_name(cls):
+        return _("Noisy Neighbor")
+
+    @classmethod
+    def get_translatable_display_name(cls):
+        return "Noisy Neighbor"
+
+    @classmethod
+    def get_efficacy_specification(cls):
+        """The efficacy spec for the current goal"""
+        return specs.Unclassified()

watcher/decision_engine/strategy/strategies/__init__.py

@@ -17,6 +17,7 @@
 from watcher.decision_engine.strategy.strategies import basic_consolidation
 from watcher.decision_engine.strategy.strategies import dummy_strategy
 from watcher.decision_engine.strategy.strategies import dummy_with_scorer
+from watcher.decision_engine.strategy.strategies import noisy_neighbor
 from watcher.decision_engine.strategy.strategies import outlet_temp_control
 from watcher.decision_engine.strategy.strategies import uniform_airflow
 from watcher.decision_engine.strategy.strategies import \
@@ -32,7 +33,8 @@ VMWorkloadConsolidation = vm_workload_consolidation.VMWorkloadConsolidation
 WorkloadBalance = workload_balance.WorkloadBalance
 WorkloadStabilization = workload_stabilization.WorkloadStabilization
 UniformAirflow = uniform_airflow.UniformAirflow
+NoisyNeighbor = noisy_neighbor.NoisyNeighbor
 
 __all__ = ("BasicConsolidation", "OutletTempControl", "DummyStrategy",
            "DummyWithScorer", "VMWorkloadConsolidation", "WorkloadBalance",
-           "WorkloadStabilization", "UniformAirflow")
+           "WorkloadStabilization", "UniformAirflow", "NoisyNeighbor")

watcher/decision_engine/strategy/strategies/base.py

@@ -328,3 +328,11 @@ class WorkloadStabilizationBaseStrategy(BaseStrategy):
     @classmethod
     def get_goal_name(cls):
         return "workload_balancing"
+
+
+@six.add_metaclass(abc.ABCMeta)
+class NoisyNeighborBaseStrategy(BaseStrategy):
+
+    @classmethod
+    def get_goal_name(cls):
+        return "noisy_neighbor"

watcher/decision_engine/strategy/strategies/noisy_neighbor.py

@@ -0,0 +1,304 @@
+# -*- encoding: utf-8 -*-
+# Copyright (c) 2017 Intel Corp
+#
+# Authors: Prudhvi Rao Shedimbi <prudhvi.rao.shedimbi@intel.com>
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
+# implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+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.decision_engine.strategy.strategies import base
+
+LOG = log.getLogger(__name__)
+
+
+class NoisyNeighbor(base.NoisyNeighborBaseStrategy):
+
+    MIGRATION = "migrate"
+    # The meter to report L3 cache in ceilometer
+    METER_NAME_L3 = "cpu_l3_cache"
+    DEFAULT_WATCHER_PRIORITY = 5
+
+    def __init__(self, config, osc=None):
+        """Noisy Neighbor strategy using live migration
+
+        :param config: A mapping containing the configuration of this strategy
+        :type config: dict
+        :param osc: an OpenStackClients object, defaults to None
+        :type osc: :py:class:`~.OpenStackClients` instance, optional
+        """
+
+        super(NoisyNeighbor, self).__init__(config, osc)
+
+        self.meter_name = self.METER_NAME_L3
+        self._ceilometer = None
+
+    @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
+
+    @classmethod
+    def get_name(cls):
+        return "noisy_neighbor"
+
+    @classmethod
+    def get_display_name(cls):
+        return _("Noisy Neighbor")
+
+    @classmethod
+    def get_translatable_display_name(cls):
+        return "Noisy Neighbor"
+
+    @classmethod
+    def get_schema(cls):
+        # Mandatory default setting for each element
+        return {
+            "properties": {
+                "cache_threshold": {
+                    "description": "Performance drop in L3_cache threshold "
+                                   "for migration",
+                    "type": "number",
+                    "default": 35.0
+                },
+                "period": {
+                    "description": "Aggregate time period of ceilometer",
+                    "type": "number",
+                    "default": 100.0
+                },
+            },
+        }
+
+    def get_current_and_previous_cache(self, instance):
+
+        try:
+            current_cache = self.ceilometer.statistic_aggregation(
+                resource_id=instance.uuid,
+                meter_name=self.meter_name, period=self.period,
+                aggregate='avg')
+
+            previous_cache = 2 * (
+                self.ceilometer.statistic_aggregation(
+                    resource_id=instance.uuid,
+                    meter_name=self.meter_name,
+                    period=2*self.period, aggregate='avg')) - current_cache
+
+        except Exception as exc:
+            LOG.exception(exc)
+            return None
+
+        return current_cache, previous_cache
+
+    def find_priority_instance(self, instance):
+
+        current_cache, previous_cache = \
+            self.get_current_and_previous_cache(instance)
+
+        if None in (current_cache, previous_cache):
+            LOG.warning("Ceilometer unable to pick L3 Cache "
+                        "values. Skipping the instance")
+            return None
+
+        if (current_cache < (1 - (self.cache_threshold / 100.0)) *
+                previous_cache):
+            return instance
+        else:
+            return None
+
+    def find_noisy_instance(self, instance):
+
+        noisy_current_cache, noisy_previous_cache = \
+            self.get_current_and_previous_cache(instance)
+
+        if None in (noisy_current_cache, noisy_previous_cache):
+            LOG.warning("Ceilometer unable to pick "
+                        "L3 Cache. Skipping the instance")
+            return None
+
+        if (noisy_current_cache > (1 + (self.cache_threshold / 100.0)) *
+                noisy_previous_cache):
+            return instance
+        else:
+            return None
+
+    def group_hosts(self):
+
+        nodes = self.compute_model.get_all_compute_nodes()
+        size_cluster = len(nodes)
+        if size_cluster == 0:
+            raise wexc.ClusterEmpty()
+
+        hosts_need_release = {}
+        hosts_target = []
+
+        for node in nodes.values():
+            instances_of_node = self.compute_model.get_node_instances(node)
+            node_instance_count = len(instances_of_node)
+
+            # Flag that tells us whether to skip the node or not. If True,
+            # the node is skipped. Will be true if we find a noisy instance or
+            # when potential priority instance will be same as potential noisy
+            # instance
+            loop_break_flag = False
+
+            if node_instance_count > 1:
+
+                instance_priority_list = []
+
+                for instance in instances_of_node:
+                    instance_priority_list.append(instance)
+
+                # If there is no metadata regarding watcher-priority, it takes
+                # DEFAULT_WATCHER_PRIORITY as priority.
+                instance_priority_list.sort(key=lambda a: (
+                    a.get('metadata').get('watcher-priority'),
+                    self.DEFAULT_WATCHER_PRIORITY))
+
+                instance_priority_list_reverse = list(instance_priority_list)
+                instance_priority_list_reverse.reverse()
+
+                for potential_priority_instance in instance_priority_list:
+
+                    priority_instance = self.find_priority_instance(
+                        potential_priority_instance)
+
+                    if (priority_instance is not None):
+
+                        for potential_noisy_instance in (
+                                instance_priority_list_reverse):
+                            if(potential_noisy_instance ==
+                               potential_priority_instance):
+                                loop_break_flag = True
+                                break
+
+                            noisy_instance = self.find_noisy_instance(
+                                potential_noisy_instance)
+
+                            if noisy_instance is not None:
+                                hosts_need_release[node.uuid] = {
+                                    'priority_vm': potential_priority_instance,
+                                    'noisy_vm': potential_noisy_instance}
+                                LOG.debug("Priority VM found: %s" % (
+                                    potential_priority_instance.uuid))
+                                LOG.debug("Noisy VM found: %s" % (
+                                    potential_noisy_instance.uuid))
+                                loop_break_flag = True
+                                break
+
+                    # No need to check other instances in the node
+                    if loop_break_flag is True:
+                        break
+
+            if node.uuid not in hosts_need_release:
+                hosts_target.append(node)
+
+        return hosts_need_release, hosts_target
+
+    def calc_used_resource(self, node):
+        """Calculate the used vcpus, memory and disk based on VM flavors"""
+        instances = self.compute_model.get_node_instances(node)
+        vcpus_used = 0
+        memory_mb_used = 0
+        disk_gb_used = 0
+        for instance in instances:
+            vcpus_used += instance.vcpus
+            memory_mb_used += instance.memory
+            disk_gb_used += instance.disk
+
+        return vcpus_used, memory_mb_used, disk_gb_used
+
+    def filter_dest_servers(self, hosts, instance_to_migrate):
+        required_cores = instance_to_migrate.vcpus
+        required_disk = instance_to_migrate.disk
+        required_memory = instance_to_migrate.memory
+
+        dest_servers = []
+        for host in hosts:
+            cores_used, mem_used, disk_used = self.calc_used_resource(host)
+            cores_available = host.vcpus - cores_used
+            disk_available = host.disk - disk_used
+            mem_available = host.memory - mem_used
+            if (cores_available >= required_cores and disk_available >=
+                    required_disk and mem_available >= required_memory):
+                dest_servers.append(host)
+
+        return dest_servers
+
+    def pre_execute(self):
+        LOG.debug("Initializing Noisy Neighbor strategy")
+
+        if not self.compute_model:
+            raise wexc.ClusterStateNotDefined()
+
+        if self.compute_model.stale:
+            raise wexc.ClusterStateStale()
+
+        LOG.debug(self.compute_model.to_string())
+
+    def do_execute(self):
+        self.cache_threshold = self.input_parameters.cache_threshold
+        self.period = self.input_parameters.period
+
+        hosts_need_release, hosts_target = self.group_hosts()
+
+        if len(hosts_need_release) == 0:
+            LOG.debug("No hosts require optimization")
+            return
+
+        if len(hosts_target) == 0:
+            LOG.debug("No hosts available to migrate")
+            return
+
+        mig_source_node_name = max(hosts_need_release.keys(), key=lambda a:
+                                   hosts_need_release[a]['priority_vm'])
+        instance_to_migrate = hosts_need_release[mig_source_node_name][
+            'noisy_vm']
+
+        if instance_to_migrate is None:
+            return
+
+        dest_servers = self.filter_dest_servers(hosts_target,
+                                                instance_to_migrate)
+
+        if len(dest_servers) == 0:
+            LOG.info("No proper target host could be found")
+            return
+
+        # Destination node will be the first available node in the list.
+        mig_destination_node = dest_servers[0]
+        mig_source_node = self.compute_model.get_node_by_uuid(
+            mig_source_node_name)
+
+        if self.compute_model.migrate_instance(instance_to_migrate,
+                                               mig_source_node,
+                                               mig_destination_node):
+            parameters = {'migration_type': 'live',
+                          'source_node': mig_source_node.uuid,
+                          'destination_node': mig_destination_node.uuid}
+            self.solution.add_action(action_type=self.MIGRATION,
+                                     resource_id=instance_to_migrate.uuid,
+                                     input_parameters=parameters)
+
+    def post_execute(self):
+        self.solution.model = self.compute_model
+
+        LOG.debug(self.compute_model.to_string())

watcher/tests/decision_engine/model/ceilometer_metrics.py

@@ -56,6 +56,41 @@ class FakeCeilometerMetrics(object):
             result = self.get_average_usage_instance_cpu_wb(resource_id)
         return result
 
+    def mock_get_statistics_nn(self, resource_id, meter_name, period,
+                               aggregate='avg'):
+        result = 0.0
+        if meter_name == "cpu_l3_cache" and period == 100:
+            result = self.get_average_l3_cache_current(resource_id)
+        if meter_name == "cpu_l3_cache" and period == 200:
+            result = self.get_average_l3_cache_previous(resource_id)
+        return result
+
+    @staticmethod
+    def get_average_l3_cache_current(uuid):
+        """The average l3 cache used by instance"""
+        mock = {}
+        mock['73b09e16-35b7-4922-804e-e8f5d9b740fc'] = 35 * oslo_utils.units.Ki
+        mock['cae81432-1631-4d4e-b29c-6f3acdcde906'] = 30 * oslo_utils.units.Ki
+        mock['INSTANCE_3'] = 40 * oslo_utils.units.Ki
+        mock['INSTANCE_4'] = 35 * oslo_utils.units.Ki
+        if uuid not in mock.keys():
+            mock[uuid] = 25 * oslo_utils.units.Ki
+        return mock[str(uuid)]
+
+    @staticmethod
+    def get_average_l3_cache_previous(uuid):
+        """The average l3 cache used by instance"""
+        mock = {}
+        mock['73b09e16-35b7-4922-804e-e8f5d9b740fc'] = 34.5 * (
+            oslo_utils.units.Ki)
+        mock['cae81432-1631-4d4e-b29c-6f3acdcde906'] = 30.5 * (
+            oslo_utils.units.Ki)
+        mock['INSTANCE_3'] = 60 * oslo_utils.units.Ki
+        mock['INSTANCE_4'] = 22.5 * oslo_utils.units.Ki
+        if uuid not in mock.keys():
+            mock[uuid] = 25 * oslo_utils.units.Ki
+        return mock[str(uuid)]
+
     @staticmethod
     def get_average_outlet_temperature(uuid):
         """The average outlet temperature for host"""

watcher/tests/decision_engine/model/data/scenario_7_with_2_nodes.xml

@@ -1,10 +1,10 @@
 <ModelRoot>
   <ComputeNode human_id="" uuid="Node_0" status="enabled" state="up" id="0" hostname="hostname_0" vcpus="50" disk="250" disk_capacity="250" memory="132">
-    <Instance state="active" human_id="" uuid="73b09e16-35b7-4922-804e-e8f5d9b740fc" vcpus="10" disk="20" disk_capacity="20" memory="2" metadata='{"optimize": true,"top": "floor", "nested": {"x": "y"}}'/>
-    <Instance state="active" human_id="" uuid="cae81432-1631-4d4e-b29c-6f3acdcde906" vcpus="15" disk="20" disk_capacity="20" memory="2" metadata='{"optimize": true,"top": "floor", "nested": {"x": "y"}}'/>
+    <Instance state="active" human_id="" uuid="73b09e16-35b7-4922-804e-e8f5d9b740fc" vcpus="10" disk="20" disk_capacity="20" memory="2" metadata='{"optimize": true,"top": "floor", "nested": {"x": "y"}, "watcher-priority": "8"}'/>
+    <Instance state="active" human_id="" uuid="cae81432-1631-4d4e-b29c-6f3acdcde906" vcpus="15" disk="20" disk_capacity="20" memory="2" metadata='{"optimize": true,"top": "floor", "nested": {"x": "y"}, "watcher-priority": "4"}'/>
   </ComputeNode>
   <ComputeNode human_id="" uuid="Node_1" status="enabled" state="up" id="1" hostname="hostname_1" vcpus="50" disk="250" disk_capacity="250" memory="132">
-    <Instance state="active" human_id="" uuid="INSTANCE_3" vcpus="10" disk="20" disk_capacity="20" memory="2" metadata='{"optimize": true,"top": "floor", "nested": {"x": "y"}}'/>
-    <Instance state="active" human_id="" uuid="INSTANCE_4" vcpus="10" disk="20" disk_capacity="20" memory="2" metadata='{"optimize": true,"top": "floor", "nested": {"x": "y"}}'/>
+    <Instance state="active" human_id="" uuid="INSTANCE_3" vcpus="10" disk="20" disk_capacity="20" memory="2" metadata='{"optimize": true,"top": "floor", "nested": {"x": "y"}, "watcher-priority": "1"}'/>
+    <Instance state="active" human_id="" uuid="INSTANCE_4" vcpus="10" disk="20" disk_capacity="20" memory="2" metadata='{"optimize": true,"top": "floor", "nested": {"x": "y"}, "watcher-priority": "9"}'/>
   </ComputeNode>
 </ModelRoot>

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

@@ -0,0 +1,179 @@
+# -*- encoding: utf-8 -*-
+# Copyright (c) 2017 Intel Corp
+#
+# Authors: Prudhvi Rao Shedimbi <prudhvi.rao.shedimbi@intel.com>
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
+# implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import collections
+import mock
+
+from watcher.applier.loading import default
+from watcher.common import exception
+from watcher.common import utils
+from watcher.decision_engine.model import model_root
+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
+
+
+class TestNoisyNeighbor(base.TestCase):
+
+    def setUp(self):
+        super(TestNoisyNeighbor, self).setUp()
+        # fake metrics
+        self.fake_metrics = ceilometer_metrics.FakeCeilometerMetrics()
+        # fake cluster
+        self.fake_cluster = faker_cluster_state.FakerModelCollector()
+
+        p_model = mock.patch.object(
+            strategies.NoisyNeighbor, "compute_model",
+            new_callable=mock.PropertyMock)
+        self.m_model = p_model.start()
+        self.addCleanup(p_model.stop)
+
+        p_ceilometer = mock.patch.object(
+            strategies.NoisyNeighbor, "ceilometer",
+            new_callable=mock.PropertyMock)
+        self.m_ceilometer = p_ceilometer.start()
+        self.addCleanup(p_ceilometer.stop)
+
+        p_audit_scope = mock.patch.object(
+            strategies.NoisyNeighbor, "audit_scope",
+            new_callable=mock.PropertyMock
+        )
+        self.m_audit_scope = p_audit_scope.start()
+        self.addCleanup(p_audit_scope.stop)
+
+        self.m_audit_scope.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_nn)
+        self.strategy = strategies.NoisyNeighbor(config=mock.Mock())
+
+        self.strategy.input_parameters = utils.Struct()
+        self.strategy.input_parameters.update({'cache_threshold': 35})
+        self.strategy.threshold = 35
+        self.strategy.input_parameters.update({'period': 100})
+        self.strategy.threshold = 100
+
+    def test_calc_used_resource(self):
+        model = self.fake_cluster.generate_scenario_3_with_2_nodes()
+        self.m_model.return_value = model
+        node = model.get_node_by_uuid('Node_0')
+        cores_used, mem_used, disk_used = self.strategy.calc_used_resource(
+            node)
+
+        self.assertEqual((10, 2, 20), (cores_used, mem_used, disk_used))
+
+    def test_group_hosts(self):
+        self.strategy.cache_threshold = 35
+        self.strategy.period = 100
+        model = self.fake_cluster.generate_scenario_7_with_2_nodes()
+        self.m_model.return_value = model
+        node_uuid = 'Node_1'
+        n1, n2 = self.strategy.group_hosts()
+        self.assertTrue(node_uuid in n1)
+        self.assertEqual(n1[node_uuid]['priority_vm'].uuid, 'INSTANCE_3')
+        self.assertEqual(n1[node_uuid]['noisy_vm'].uuid, 'INSTANCE_4')
+        self.assertEqual('Node_0', n2[0].uuid)
+
+    def test_find_priority_instance(self):
+        self.strategy.cache_threshold = 35
+        self.strategy.period = 100
+        model = self.fake_cluster.generate_scenario_7_with_2_nodes()
+        self.m_model.return_value = model
+        potential_prio_inst = model.get_instance_by_uuid('INSTANCE_3')
+        inst_res = self.strategy.find_priority_instance(potential_prio_inst)
+        self.assertEqual('INSTANCE_3', inst_res.uuid)
+
+    def test_find_noisy_instance(self):
+        self.strategy.cache_threshold = 35
+        self.strategy.period = 100
+        model = self.fake_cluster.generate_scenario_7_with_2_nodes()
+        self.m_model.return_value = model
+        potential_noisy_inst = model.get_instance_by_uuid('INSTANCE_4')
+        inst_res = self.strategy.find_noisy_instance(potential_noisy_inst)
+        self.assertEqual('INSTANCE_4', inst_res.uuid)
+
+    def test_filter_destination_hosts(self):
+        model = self.fake_cluster.generate_scenario_7_with_2_nodes()
+        self.m_model.return_value = model
+        self.strategy.cache_threshold = 35
+        self.strategy.period = 100
+        n1, n2 = self.strategy.group_hosts()
+        mig_source_node = max(n1.keys(), key=lambda a:
+                              n1[a]['priority_vm'])
+        instance_to_mig = n1[mig_source_node]['noisy_vm']
+        dest_hosts = self.strategy.filter_dest_servers(
+            n2, instance_to_mig)
+
+        self.assertEqual(1, len(dest_hosts))
+        self.assertEqual('Node_0', dest_hosts[0].uuid)
+
+    def test_exception_model(self):
+        self.m_model.return_value = None
+        self.assertRaises(
+            exception.ClusterStateNotDefined, self.strategy.execute)
+
+    def test_exception_cluster_empty(self):
+        model = model_root.ModelRoot()
+        self.m_model.return_value = model
+        self.assertRaises(exception.ClusterEmpty, self.strategy.execute)
+
+    def test_exception_stale_cdm(self):
+        self.fake_cluster.set_cluster_data_model_as_stale()
+        self.m_model.return_value = self.fake_cluster.cluster_data_model
+
+        self.assertRaises(
+            exception.ClusterStateNotDefined,
+            self.strategy.execute)
+
+    def test_execute_cluster_empty(self):
+        model = model_root.ModelRoot()
+        self.m_model.return_value = model
+        self.assertRaises(exception.ClusterEmpty, self.strategy.execute)
+
+    def test_execute_no_workload(self):
+        self.strategy.cache_threshold = 35
+        self.strategy.period = 100
+        model = self.fake_cluster.generate_scenario_4_with_1_node_no_instance()
+        self.m_model.return_value = model
+
+        solution = self.strategy.execute()
+        self.assertEqual([], solution.actions)
+
+    def test_execute(self):
+        self.strategy.cache_threshold = 35
+        self.strategy.period = 100
+        model = self.fake_cluster.generate_scenario_7_with_2_nodes()
+        self.m_model.return_value = model
+        solution = self.strategy.execute()
+        actions_counter = collections.Counter(
+            [action.get('action_type') for action in solution.actions])
+
+        num_migrations = actions_counter.get("migrate", 0)
+        self.assertEqual(1, num_migrations)
+
+    def test_check_parameters(self):
+        model = self.fake_cluster.generate_scenario_3_with_2_nodes()
+        self.m_model.return_value = model
+        solution = self.strategy.execute()
+        loader = default.DefaultActionLoader()
+        for action in solution.actions:
+            loaded_action = loader.load(action['action_type'])
+            loaded_action.input_parameters = action['input_parameters']
+            loaded_action.validate_parameters()