openstack
/
watcher
Code Issues Proposed changes

use parameters to set the threshold 

use parameters to set the threshold for strategies
of Uniform Airflow,Workload balance.

Change-Id: I5a547929eb1e2413468e9a5de16d3fd42cabadf9
Close-bug: #1600707
This commit is contained in:
junjie huang 2016-07-14 18:11:06 +00:00 committed by Edwin Zhai
parent 8db3427665
commit 5dee934565
4 changed files with 73 additions and 39 deletions
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47
watcher/decision_engine/strategy/strategies/uniform_airflow.py
View File

@ -60,15 +60,7 @@ class UniformAirflow(base.BaseStrategy):
METER_NAME_INLET_T = "hardware.ipmi.node.temperature"
# The meter to report system power of physical server in ceilometer
METER_NAME_POWER = "hardware.ipmi.node.power"
# TODO(Junjie): make below thresholds configurable
# Unit: 0.1 CFM
THRESHOLD_AIRFLOW = 400.0
# Unit: degree C
THRESHOLD_INLET_T = 28.0
# Unit: watts
THRESHOLD_POWER = 350.0
# choose 300 seconds as the default duration of meter aggregation
# TODO(Junjie): make it configurable
PERIOD = 300
MIGRATION = "migrate"
@ -83,10 +75,6 @@ class UniformAirflow(base.BaseStrategy):
super(UniformAirflow, self).__init__(config, osc)
# The migration plan will be triggered when the airflow reaches
# threshold
# TODO(Junjie): Threshold should be configurable for each audit
self.threshold_airflow = self.THRESHOLD_AIRFLOW
self.threshold_inlet_t = self.THRESHOLD_INLET_T
self.threshold_power = self.THRESHOLD_POWER
self.meter_name_airflow = self.METER_NAME_AIRFLOW
self.meter_name_inlet_t = self.METER_NAME_INLET_T
self.meter_name_power = self.METER_NAME_POWER
@ -127,6 +115,37 @@ class UniformAirflow(base.BaseStrategy):
def get_translatable_goal_display_name(cls):
return "Airflow optimization"
@classmethod
def get_schema(cls):
# Mandatory default setting for each element
return {
"properties": {
"threshold_airflow": {
"description": "airflow threshold for migration, Unit is\
0.1CFM",
"type": "number",
"default": 400.0
},
"threshold_inlet_t": {
"description": "inlet temperature threshold for migration\
decision",
"type": "number",
"default": 28.0
},
"threshold_power": {
"description": "system power threshold for migration\
decision",
"type": "number",
"default": 350.0
},
"period": {
"description": "aggregate time period of ceilometer",
"type": "number",
"default": 300
},
},
}
def calculate_used_resource(self, hypervisor, cap_cores, cap_mem,
cap_disk):
"""Calculate the used vcpus, memory and disk based on VM flavors"""
@ -274,6 +293,10 @@ class UniformAirflow(base.BaseStrategy):
raise wexc.ClusterStateNotDefined()
def do_execute(self):
self.threshold_airflow = self.input_parameters.threshold_airflow
self.threshold_inlet_t = self.input_parameters.threshold_inlet_t
self.threshold_power = self.input_parameters.threshold_power
self._period = self.input_parameters.period
src_hypervisors, target_hypervisors = (
self.group_hosts_by_airflow())

28
watcher/decision_engine/strategy/strategies/workload_balance.py
View File

@ -59,11 +59,6 @@ class WorkloadBalance(base.WorkloadStabilizationBaseStrategy):
# The meter to report CPU utilization % of VM in ceilometer
METER_NAME = "cpu_util"
# Unit: %, value range is [0 , 100]
# TODO(Junjie): make it configurable
THRESHOLD = 25.0
# choose 300 seconds as the default duration of meter aggregation
# TODO(Junjie): make it configurable
PERIOD = 300
MIGRATION = "migrate"
@ -77,11 +72,8 @@ class WorkloadBalance(base.WorkloadStabilizationBaseStrategy):
super(WorkloadBalance, self).__init__(config, osc)
# the migration plan will be triggered when the CPU utlization %
# reaches threshold
# TODO(Junjie): Threshold should be configurable for each audit
self.threshold = self.THRESHOLD
self._meter = self.METER_NAME
self._ceilometer = None
self._period = self.PERIOD
@property
def ceilometer(self):
@ -105,6 +97,24 @@ class WorkloadBalance(base.WorkloadStabilizationBaseStrategy):
def get_translatable_display_name(cls):
return "Workload Balance Migration Strategy"
@classmethod
def get_schema(cls):
# Mandatory default setting for each element
return {
"properties": {
"threshold": {
"description": "workload threshold for migration",
"type": "number",
"default": 25.0
},
"period": {
"description": "aggregate time period of ceilometer",
"type": "number",
"default": 300
},
},
}
def calculate_used_resource(self, hypervisor, cap_cores, cap_mem,
cap_disk):
"""Calculate the used vcpus, memory and disk based on VM flavors"""
@ -270,6 +280,8 @@ class WorkloadBalance(base.WorkloadStabilizationBaseStrategy):
This phase is where you should put the main logic of your strategy.
"""
self.threshold = self.input_parameters.threshold
self._period = self.input_parameters.period
src_hypervisors, target_hypervisors, avg_workload, workload_cache = (
self.group_hosts_by_cpu_util())

10
watcher/tests/decision_engine/strategy/strategies/test_uniform_airflow.py
View File

@ -21,6 +21,7 @@ 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.model import resource
from watcher.decision_engine.strategy import strategies
@ -56,6 +57,15 @@ class TestUniformAirflow(base.BaseTestCase):
self.m_ceilometer.return_value = mock.Mock(
statistic_aggregation=self.fake_metrics.mock_get_statistics)
self.strategy = strategies.UniformAirflow(config=mock.Mock())
self.strategy.input_parameters = utils.Struct()
self.strategy.input_parameters.update({'threshold_airflow': 400.0,
'threshold_inlet_t': 28.0,
'threshold_power': 350.0,
'period': 300})
self.strategy.threshold_airflow = 400
self.strategy.threshold_inlet_t = 28
self.strategy.threshold_power = 350
self._period = 300
def test_calc_used_res(self):
model = self.fake_cluster.generate_scenario_7_with_2_hypervisors()

27
watcher/tests/decision_engine/strategy/strategies/test_workload_balance.py
View File

@ -21,6 +21,7 @@ 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.model import resource
from watcher.decision_engine.strategy import strategies
@ -47,15 +48,20 @@ class TestWorkloadBalance(base.BaseTestCase):
self.addCleanup(p_model.stop)
p_ceilometer = mock.patch.object(
strategies.BasicConsolidation, "ceilometer",
strategies.WorkloadBalance, "ceilometer",
new_callable=mock.PropertyMock)
self.m_ceilometer = p_ceilometer.start()
self.addCleanup(p_ceilometer.stop)
self.m_model.return_value = model_root.ModelRoot()
self.m_ceilometer.return_value = mock.Mock(
statistic_aggregation=self.fake_metrics.mock_get_statistics)
statistic_aggregation=self.fake_metrics.mock_get_statistics_wb)
self.strategy = strategies.WorkloadBalance(config=mock.Mock())
self.strategy.input_parameters = utils.Struct()
self.strategy.input_parameters.update({'threshold': 25.0,
'period': 300})
self.strategy.threshold = 25.0
self.strategy._period = 300
def test_calc_used_res(self):
model = self.fake_cluster.generate_scenario_6_with_2_hypervisors()
@ -74,10 +80,7 @@ class TestWorkloadBalance(base.BaseTestCase):
model = self.fake_cluster.generate_scenario_6_with_2_hypervisors()
self.m_model.return_value = model
self.strategy.threshold = 30
self.strategy.ceilometer = mock.MagicMock(
statistic_aggregation=self.fake_metrics.mock_get_statistics_wb)
h1, h2, avg, w_map = self.strategy.group_hosts_by_cpu_util()
# print h1, h2, avg, w_map
self.assertEqual(h1[0]['hv'].uuid, 'Node_0')
self.assertEqual(h2[0]['hv'].uuid, 'Node_1')
self.assertEqual(avg, 8.0)
@ -85,8 +88,6 @@ class TestWorkloadBalance(base.BaseTestCase):
def test_choose_vm_to_migrate(self):
model = self.fake_cluster.generate_scenario_6_with_2_hypervisors()
self.m_model.return_value = model
self.strategy.ceilometer = mock.MagicMock(
statistic_aggregation=self.fake_metrics.mock_get_statistics_wb)
h1, h2, avg, w_map = self.strategy.group_hosts_by_cpu_util()
vm_to_mig = self.strategy.choose_vm_to_migrate(h1, avg, w_map)
self.assertEqual(vm_to_mig[0].uuid, 'Node_0')
@ -96,8 +97,6 @@ class TestWorkloadBalance(base.BaseTestCase):
def test_choose_vm_notfound(self):
model = self.fake_cluster.generate_scenario_6_with_2_hypervisors()
self.m_model.return_value = model
self.strategy.ceilometer = mock.MagicMock(
statistic_aggregation=self.fake_metrics.mock_get_statistics_wb)
h1, h2, avg, w_map = self.strategy.group_hosts_by_cpu_util()
vms = model.get_all_vms()
vms.clear()
@ -107,8 +106,6 @@ class TestWorkloadBalance(base.BaseTestCase):
def test_filter_destination_hosts(self):
model = self.fake_cluster.generate_scenario_6_with_2_hypervisors()
self.m_model.return_value = model
self.strategy.ceilometer = mock.MagicMock(
statistic_aggregation=self.fake_metrics.mock_get_statistics_wb)
h1, h2, avg, w_map = self.strategy.group_hosts_by_cpu_util()
vm_to_mig = self.strategy.choose_vm_to_migrate(h1, avg, w_map)
dest_hosts = self.strategy.filter_destination_hosts(
@ -129,23 +126,17 @@ class TestWorkloadBalance(base.BaseTestCase):
def test_execute_cluster_empty(self):
model = model_root.ModelRoot()
self.m_model.return_value = model
self.strategy.ceilometer = mock.MagicMock(
statistic_aggregation=self.fake_metrics.mock_get_statistics_wb)
self.assertRaises(exception.ClusterEmpty, self.strategy.execute)
def test_execute_no_workload(self):
model = self.fake_cluster.generate_scenario_4_with_1_hypervisor_no_vm()
self.m_model.return_value = model
self.strategy.ceilometer = mock.MagicMock(
statistic_aggregation=self.fake_metrics.mock_get_statistics_wb)
solution = self.strategy.execute()
self.assertEqual([], solution.actions)
def test_execute(self):
model = self.fake_cluster.generate_scenario_6_with_2_hypervisors()
self.m_model.return_value = model
self.strategy.ceilometer = mock.MagicMock(
statistic_aggregation=self.fake_metrics.mock_get_statistics_wb)
solution = self.strategy.execute()
actions_counter = collections.Counter(
[action.get('action_type') for action in solution.actions])
@ -156,8 +147,6 @@ class TestWorkloadBalance(base.BaseTestCase):
def test_check_parameters(self):
model = self.fake_cluster.generate_scenario_6_with_2_hypervisors()
self.m_model.return_value = model
self.strategy.ceilometer = mock.MagicMock(
statistic_aggregation=self.fake_metrics.mock_get_statistics_wb)
solution = self.strategy.execute()
loader = default.DefaultActionLoader()
for action in solution.actions: