Adapt noisy_neighbor strategy to multiple datasource backend

Partially-Implements: blueprint watcher-multi-datasource
Change-Id: Ibcd5d0776280bb68ed838f88ebfcde27fc1a3d35
This commit is contained in:
Alexander Chadin 2017-12-22 12:47:18 +03:00
parent 7cdcb4743e
commit 5dd6817d47
6 changed files with 84 additions and 40 deletions

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@ -33,7 +33,7 @@ class DataSourceBase(object):
host_memory_usage='hardware.memory.used', ),
gnocchi=dict(host_cpu_usage='compute.node.cpu.percent',
instance_cpu_usage='cpu_util',
instance_l3_cache_usage=None,
instance_l3_cache_usage='cpu_l3_cache',
host_outlet_temp='hardware.ipmi.node.outlet_temperature',
host_airflow='hardware.ipmi.node.airflow',
host_inlet_temp='hardware.ipmi.node.temperature',

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@ -146,7 +146,9 @@ class GnocchiHelper(base.DataSourceBase):
def get_instance_l3_cache_usage(self, resource_id, period, aggregate,
granularity=300):
raise NotImplementedError
meter_name = self.METRIC_MAP.get('instance_l3_cache_usage')
return self.statistic_aggregation(resource_id, meter_name, period,
granularity, aggregation=aggregate)
def get_instance_ram_allocated(self, resource_id, period, aggregate,
granularity=300):

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@ -16,14 +16,15 @@
# See the License for the specific language governing permissions and
# limitations under the License.
#
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.decision_engine.strategy.strategies import base
LOG = log.getLogger(__name__)
CONF = cfg.CONF
class NoisyNeighbor(base.NoisyNeighborBaseStrategy):
@ -45,17 +46,6 @@ class NoisyNeighbor(base.NoisyNeighborBaseStrategy):
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):
@ -81,32 +71,39 @@ class NoisyNeighbor(base.NoisyNeighborBaseStrategy):
"default": 35.0
},
"period": {
"description": "Aggregate time period of ceilometer",
"description": "Aggregate time period of "
"ceilometer and gnocchi",
"type": "number",
"default": 100.0
},
},
}
@classmethod
def get_config_opts(cls):
return [
cfg.ListOpt(
"datasource",
help="Data source to use in order to query the needed metrics",
item_type=cfg.types.String(choices=['gnocchi', 'ceilometer',
'monasca']),
default=['gnocchi', 'ceilometer', 'monasca'])
]
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')
curr_cache = self.datasource_backend.get_instance_l3_cache_usage(
instance.uuid, self.period, 'mean', granularity=300)
previous_cache = 2 * (
self.ceilometer.statistic_aggregation(
resource_id=instance.uuid,
meter_name=self.meter_name,
period=2*self.period, aggregate='avg')) - current_cache
self.datasource_backend.get_instance_l3_cache_usage(
instance.uuid, 2 * self.period,
'mean', granularity=300)) - curr_cache
except Exception as exc:
LOG.exception(exc)
return None
return None, None
return current_cache, previous_cache
return curr_cache, previous_cache
def find_priority_instance(self, instance):
@ -114,7 +111,7 @@ class NoisyNeighbor(base.NoisyNeighborBaseStrategy):
self.get_current_and_previous_cache(instance)
if None in (current_cache, previous_cache):
LOG.warning("Ceilometer unable to pick L3 Cache "
LOG.warning("Datasource unable to pick L3 Cache "
"values. Skipping the instance")
return None
@ -130,7 +127,7 @@ class NoisyNeighbor(base.NoisyNeighborBaseStrategy):
self.get_current_and_previous_cache(instance)
if None in (noisy_current_cache, noisy_previous_cache):
LOG.warning("Ceilometer unable to pick "
LOG.warning("Datasource unable to pick "
"L3 Cache. Skipping the instance")
return None

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@ -64,12 +64,12 @@ class FakeCeilometerMetrics(object):
result = self.get_average_usage_instance_memory_wb(resource_id)
return result
def mock_get_statistics_nn(self, resource_id, meter_name, period,
aggregate='avg'):
def mock_get_statistics_nn(self, resource_id, period,
aggregation, granularity=300):
result = 0.0
if meter_name == "cpu_l3_cache" and period == 100:
if period == 100:
result = self.get_average_l3_cache_current(resource_id)
if meter_name == "cpu_l3_cache" and period == 200:
if period == 200:
result = self.get_average_l3_cache_previous(resource_id)
return result

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@ -52,6 +52,41 @@ class FakeGnocchiMetrics(object):
result = self.get_average_power(resource_id)
return result
def mock_get_statistics_nn(self, resource_id, period,
aggregation, granularity=300):
result = 0.0
if period == 100:
result = self.get_average_l3_cache_current(resource_id)
if 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)]
def mock_get_statistics_wb(self, resource_id, metric, granularity,
start_time, stop_time, aggregation='mean'):
result = 0.0

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@ -27,14 +27,24 @@ 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 TestNoisyNeighbor(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(TestNoisyNeighbor, self).setUp()
# fake metrics
self.fake_metrics = ceilometer_metrics.FakeCeilometerMetrics()
self.f_metrics = self.fake_datasource_cls()
# fake cluster
self.fake_cluster = faker_cluster_state.FakerModelCollector()
@ -44,11 +54,11 @@ class TestNoisyNeighbor(base.TestCase):
self.m_model = p_model.start()
self.addCleanup(p_model.stop)
p_ceilometer = mock.patch.object(
strategies.NoisyNeighbor, "ceilometer",
p_datasource = mock.patch.object(
strategies.NoisyNeighbor, "datasource_backend",
new_callable=mock.PropertyMock)
self.m_ceilometer = p_ceilometer.start()
self.addCleanup(p_ceilometer.stop)
self.m_datasource = p_datasource.start()
self.addCleanup(p_datasource.stop)
p_audit_scope = mock.patch.object(
strategies.NoisyNeighbor, "audit_scope",
@ -60,8 +70,8 @@ class TestNoisyNeighbor(base.TestCase):
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.m_datasource.return_value = mock.Mock(
get_instance_l3_cache_usage=self.f_metrics.mock_get_statistics_nn)
self.strategy = strategies.NoisyNeighbor(config=mock.Mock())
self.strategy.input_parameters = utils.Struct()