Arnike/watcher
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Merge "Fix issues with aggregate and granularity attributes"

Browse Source
This commit is contained in:
Zuul
2018-02-06 06:05:50 +00:00
committed by Gerrit Code Review
parent cb8d1a98d6 d27ba8cc2a
commit 76263f149a
21 changed files with 204 additions and 534 deletions
Download Patch File Download Diff File Expand all files Collapse all files

52
watcher/decision_engine/strategy/strategies/outlet_temp_control.py
View File

@@ -28,15 +28,11 @@ Outlet (Exhaust Air) Temperature is one of the important thermal
telemetries to measure thermal/workload status of server.
"""
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
@@ -95,8 +91,6 @@ class OutletTempControl(base.ThermalOptimizationBaseStrategy):
:type osc: :py:class:`~.OpenStackClients` instance, optional
"""
super(OutletTempControl, self).__init__(config, osc)
self._ceilometer = None
self._gnocchi = None
@classmethod
def get_name(cls):
@@ -139,26 +133,6 @@ class OutletTempControl(base.ThermalOptimizationBaseStrategy):
},
}
@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
@property
def gnocchi(self):
if self._gnocchi is None:
self.gnocchi = gnoc.GnocchiHelper(osc=self.osc)
return self._gnocchi
@gnocchi.setter
def gnocchi(self, g):
self._gnocchi = g
@property
def granularity(self):
return self.input_parameters.get('granularity', 300)
@@ -208,25 +182,13 @@ class OutletTempControl(base.ThermalOptimizationBaseStrategy):
resource_id = node.uuid
outlet_temp = None
if self.config.datasource == "ceilometer":
outlet_temp = self.ceilometer.statistic_aggregation(
resource_id=resource_id,
meter_name=metric_name,
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))
outlet_temp = self.gnocchi.statistic_aggregation(
resource_id=resource_id,
metric=metric_name,
granularity=self.granularity,
start_time=start_time,
stop_time=stop_time,
aggregation='mean'
)
outlet_temp = self.datasource_backend.statistic_aggregation(
resource_id=resource_id,
meter_name=metric_name,
period=self.period,
granularity=self.granularity,
)
# some hosts may not have outlet temp meters, remove from target
if outlet_temp is None:
LOG.warning("%s: no outlet temp data", resource_id)

87
watcher/decision_engine/strategy/strategies/uniform_airflow.py
View File

@@ -42,15 +42,11 @@ airflow is higher than the specified threshold.
- It assumes that live migrations are possible.
"""
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
@@ -125,30 +121,8 @@ class UniformAirflow(base.BaseStrategy):
self.config.datasource]['host_inlet_temp']
self.meter_name_power = self.METRIC_NAMES[
self.config.datasource]['host_power']
self._ceilometer = None
self._gnocchi = None
self._period = self.PERIOD
@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
@property
def gnocchi(self):
if self._gnocchi is None:
self.gnocchi = gnoc.GnocchiHelper(osc=self.osc)
return self._gnocchi
@gnocchi.setter
def gnocchi(self, g):
self._gnocchi = g
@classmethod
def get_name(cls):
return "uniform_airflow"
@@ -247,35 +221,16 @@ class UniformAirflow(base.BaseStrategy):
source_instances = self.compute_model.get_node_instances(
source_node)
if source_instances:
if self.config.datasource == "ceilometer":
inlet_t = self.ceilometer.statistic_aggregation(
resource_id=source_node.uuid,
meter_name=self.meter_name_inlet_t,
period=self._period,
aggregate='avg')
power = self.ceilometer.statistic_aggregation(
resource_id=source_node.uuid,
meter_name=self.meter_name_power,
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))
inlet_t = self.gnocchi.statistic_aggregation(
resource_id=source_node.uuid,
metric=self.meter_name_inlet_t,
granularity=self.granularity,
start_time=start_time,
stop_time=stop_time,
aggregation='mean')
power = self.gnocchi.statistic_aggregation(
resource_id=source_node.uuid,
metric=self.meter_name_power,
granularity=self.granularity,
start_time=start_time,
stop_time=stop_time,
aggregation='mean')
inlet_t = self.datasource_backend.statistic_aggregation(
resource_id=source_node.uuid,
meter_name=self.meter_name_inlet_t,
period=self._period,
granularity=self.granularity)
power = self.datasource_backend.statistic_aggregation(
resource_id=source_node.uuid,
meter_name=self.meter_name_power,
period=self._period,
granularity=self.granularity)
if (power < self.threshold_power and
inlet_t < self.threshold_inlet_t):
# hardware issue, migrate all instances from this node
@@ -353,23 +308,11 @@ class UniformAirflow(base.BaseStrategy):
node = self.compute_model.get_node_by_uuid(
node_id)
resource_id = node.uuid
if self.config.datasource == "ceilometer":
airflow = self.ceilometer.statistic_aggregation(
resource_id=resource_id,
meter_name=self.meter_name_airflow,
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))
airflow = self.gnocchi.statistic_aggregation(
resource_id=resource_id,
metric=self.meter_name_airflow,
granularity=self.granularity,
start_time=start_time,
stop_time=stop_time,
aggregation='mean')
airflow = self.datasource_backend.statistic_aggregation(
resource_id=resource_id,
meter_name=self.meter_name_airflow,
period=self._period,
granularity=self.granularity)
# some hosts may not have airflow meter, remove from target
if airflow is None:
LOG.warning("%s: no airflow data", resource_id)

94
watcher/decision_engine/strategy/strategies/vm_workload_consolidation.py
View File

@@ -52,7 +52,6 @@ correctly on all compute nodes within the cluster.
This strategy assumes it is possible to live migrate any VM from
an active compute node to any other active compute node.
"""
import datetime
from oslo_config import cfg
from oslo_log import log
@@ -60,8 +59,6 @@ import six
from watcher._i18n import _
from watcher.common import exception
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
@@ -118,26 +115,6 @@ class VMWorkloadConsolidation(base.ServerConsolidationBaseStrategy):
def period(self):
return self.input_parameters.get('period', 3600)
@property
def ceilometer(self):
if self._ceilometer is None:
self.ceilometer = ceil.CeilometerHelper(osc=self.osc)
return self._ceilometer
@ceilometer.setter
def ceilometer(self, ceilometer):
self._ceilometer = ceilometer
@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
@property
def granularity(self):
return self.input_parameters.get('granularity', 300)
@@ -315,57 +292,28 @@ class VMWorkloadConsolidation(base.ServerConsolidationBaseStrategy):
disk_alloc_metric = self.METRIC_NAMES[
self.config.datasource]['disk_alloc_metric']
if self.config.datasource == "ceilometer":
instance_cpu_util = self.ceilometer.statistic_aggregation(
resource_id=instance.uuid, meter_name=cpu_util_metric,
period=self.period, aggregate='avg')
instance_ram_util = self.ceilometer.statistic_aggregation(
resource_id=instance.uuid, meter_name=ram_util_metric,
period=self.period, aggregate='avg')
if not instance_ram_util:
instance_ram_util = self.ceilometer.statistic_aggregation(
resource_id=instance.uuid, meter_name=ram_alloc_metric,
period=self.period, aggregate='avg')
instance_disk_util = self.ceilometer.statistic_aggregation(
resource_id=instance.uuid, meter_name=disk_alloc_metric,
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))
instance_cpu_util = self.gnocchi.statistic_aggregation(
instance_cpu_util = self.datasource_backend.statistic_aggregation(
resource_id=instance.uuid,
meter_name=cpu_util_metric,
period=self.period,
granularity=self.granularity)
instance_ram_util = self.datasource_backend.statistic_aggregation(
resource_id=instance.uuid,
meter_name=ram_util_metric,
period=self.period,
granularity=self.granularity)
if not instance_ram_util:
instance_ram_util = self.datasource_backend.statistic_aggregation(
resource_id=instance.uuid,
metric=cpu_util_metric,
granularity=self.granularity,
start_time=start_time,
stop_time=stop_time,
aggregation='mean'
)
instance_ram_util = self.gnocchi.statistic_aggregation(
resource_id=instance.uuid,
metric=ram_util_metric,
granularity=self.granularity,
start_time=start_time,
stop_time=stop_time,
aggregation='mean'
)
if not instance_ram_util:
instance_ram_util = self.gnocchi.statistic_aggregation(
resource_id=instance.uuid,
metric=ram_alloc_metric,
granularity=self.granularity,
start_time=start_time,
stop_time=stop_time,
aggregation='mean'
)
instance_disk_util = self.gnocchi.statistic_aggregation(
resource_id=instance.uuid,
metric=disk_alloc_metric,
granularity=self.granularity,
start_time=start_time,
stop_time=stop_time,
aggregation='mean'
)
meter_name=ram_alloc_metric,
period=self.period,
granularity=self.granularity)
instance_disk_util = self.datasource_backend.statistic_aggregation(
resource_id=instance.uuid,
meter_name=disk_alloc_metric,
period=self.period,
granularity=self.granularity)
if instance_cpu_util:
total_cpu_utilization = (
instance.vcpus * (instance_cpu_util / 100.0))

6
watcher/decision_engine/strategy/strategies/workload_balance.py
View File

@@ -290,8 +290,9 @@ class WorkloadBalance(base.WorkloadStabilizationBaseStrategy):
util = None
try:
util = self.datasource_backend.statistic_aggregation(
instance.uuid, self._meter, self._period, 'mean',
granularity=self.granularity)
instance.uuid, self._meter, self._period,
self._granularity, aggregation='mean',
dimensions=dict(resource_id=instance.uuid))
except Exception as exc:
LOG.exception(exc)
LOG.error("Can not get %s from %s", self._meter,
@@ -352,6 +353,7 @@ class WorkloadBalance(base.WorkloadStabilizationBaseStrategy):
self.threshold = self.input_parameters.threshold
self._period = self.input_parameters.period
self._meter = self.input_parameters.metrics
self._granularity = self.input_parameters.granularity
source_nodes, target_nodes, avg_workload, workload_cache = (
self.group_hosts_by_cpu_or_ram_util())

7
watcher/decision_engine/strategy/strategies/workload_stabilization.py
View File

@@ -198,8 +198,8 @@ class WorkloadStabilization(base.WorkloadStabilizationBaseStrategy):
instance_load = {'uuid': instance.uuid, 'vcpus': instance.vcpus}
for meter in self.metrics:
avg_meter = self.datasource_backend.statistic_aggregation(
instance.uuid, meter, self.periods['instance'], 'mean',
granularity=self.granularity)
instance.uuid, meter, self.periods['instance'],
self.granularity, aggregation='mean')
if avg_meter is None:
LOG.warning(
"No values returned by %(resource_id)s "
@@ -242,8 +242,7 @@ class WorkloadStabilization(base.WorkloadStabilizationBaseStrategy):
resource_id = node_id
avg_meter = self.datasource_backend.statistic_aggregation(
resource_id, self.instance_metrics[metric],
self.periods['node'], 'mean', granularity=self.granularity)
self.periods['node'], self.granularity, aggregation='mean')
if avg_meter is None:
LOG.warning('No values returned by node %s for %s',
node_id, meter_name)