Adapt basic_consolidation strategy to multiple datasource backend
Change-Id: Ie30308fd08ed1fd103b70f58f1d17b3749a6fe04
This commit is contained in:
Alexander Chadin
@@ -35,16 +35,11 @@ migration is possible on your OpenStack cluster.
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"""
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import datetime
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from oslo_config import cfg
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from oslo_log import log
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from watcher._i18n import _
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from watcher.common import exception
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from watcher.datasource import ceilometer as ceil
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from watcher.datasource import gnocchi as gnoc
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from watcher.datasource import monasca as mon
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from watcher.decision_engine.model import element
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from watcher.decision_engine.strategy.strategies import base
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@@ -91,10 +86,6 @@ class BasicConsolidation(base.ServerConsolidationBaseStrategy):
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# set default value for the efficacy
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self.efficacy = 100
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self._ceilometer = None
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self._monasca = None
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self._gnocchi = None
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# TODO(jed): improve threshold overbooking?
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self.threshold_mem = 1
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self.threshold_disk = 1
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@@ -155,11 +146,12 @@ class BasicConsolidation(base.ServerConsolidationBaseStrategy):
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@classmethod
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def get_config_opts(cls):
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return [
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cfg.StrOpt(
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cfg.ListOpt(
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"datasource",
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help="Data source to use in order to query the needed metrics",
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default="gnocchi",
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choices=["ceilometer", "monasca", "gnocchi"]),
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item_type=cfg.types.String(choices=['gnocchi', 'ceilometer',
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'monasca']),
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default=['gnocchi', 'ceilometer', 'monasca']),
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cfg.BoolOpt(
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"check_optimize_metadata",
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help="Check optimize metadata field in instance before "
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@@ -167,36 +159,6 @@ class BasicConsolidation(base.ServerConsolidationBaseStrategy):
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default=False),
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]
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@property
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def ceilometer(self):
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if self._ceilometer is None:
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self.ceilometer = ceil.CeilometerHelper(osc=self.osc)
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return self._ceilometer
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@ceilometer.setter
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def ceilometer(self, ceilometer):
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self._ceilometer = ceilometer
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@property
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def monasca(self):
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if self._monasca is None:
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self.monasca = mon.MonascaHelper(osc=self.osc)
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return self._monasca
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@monasca.setter
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def monasca(self, monasca):
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self._monasca = monasca
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@property
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def gnocchi(self):
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if self._gnocchi is None:
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self.gnocchi = gnoc.GnocchiHelper(osc=self.osc)
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return self._gnocchi
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@gnocchi.setter
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def gnocchi(self, gnocchi):
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self._gnocchi = gnocchi
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def get_available_compute_nodes(self):
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default_node_scope = [element.ServiceState.ENABLED.value,
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element.ServiceState.DISABLED.value]
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@@ -290,87 +252,13 @@ class BasicConsolidation(base.ServerConsolidationBaseStrategy):
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return (score_cores + score_disk + score_memory) / 3
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def get_node_cpu_usage(self, node):
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metric_name = self.METRIC_NAMES[
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self.config.datasource]['host_cpu_usage']
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if self.config.datasource == "ceilometer":
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resource_id = "%s_%s" % (node.uuid, node.hostname)
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return self.ceilometer.statistic_aggregation(
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resource_id=resource_id,
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meter_name=metric_name,
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period=self.period,
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aggregate='avg',
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)
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elif self.config.datasource == "gnocchi":
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resource_id = "%s_%s" % (node.uuid, node.hostname)
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stop_time = datetime.datetime.utcnow()
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start_time = stop_time - datetime.timedelta(
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seconds=int(self.period))
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return self.gnocchi.statistic_aggregation(
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resource_id=resource_id,
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metric=metric_name,
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granularity=self.granularity,
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start_time=start_time,
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stop_time=stop_time,
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aggregation='mean'
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)
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elif self.config.datasource == "monasca":
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statistics = self.monasca.statistic_aggregation(
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meter_name=metric_name,
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dimensions=dict(hostname=node.uuid),
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period=self.period,
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aggregate='avg'
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)
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cpu_usage = None
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for stat in statistics:
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avg_col_idx = stat['columns'].index('avg')
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values = [r[avg_col_idx] for r in stat['statistics']]
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value = float(sum(values)) / len(values)
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cpu_usage = value
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return cpu_usage
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raise exception.UnsupportedDataSource(
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strategy=self.name, datasource=self.config.datasource)
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resource_id = "%s_%s" % (node.uuid, node.hostname)
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return self.datasource_backend.get_host_cpu_usage(
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resource_id, self.period, 'mean', granularity=300)
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def get_instance_cpu_usage(self, instance):
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metric_name = self.METRIC_NAMES[
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self.config.datasource]['instance_cpu_usage']
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if self.config.datasource == "ceilometer":
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return self.ceilometer.statistic_aggregation(
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resource_id=instance.uuid,
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meter_name=metric_name,
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period=self.period,
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aggregate='avg'
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)
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elif self.config.datasource == "gnocchi":
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stop_time = datetime.datetime.utcnow()
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start_time = stop_time - datetime.timedelta(
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seconds=int(self.period))
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return self.gnocchi.statistic_aggregation(
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resource_id=instance.uuid,
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metric=metric_name,
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granularity=self.granularity,
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start_time=start_time,
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stop_time=stop_time,
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aggregation='mean',
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)
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elif self.config.datasource == "monasca":
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statistics = self.monasca.statistic_aggregation(
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meter_name=metric_name,
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dimensions=dict(resource_id=instance.uuid),
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period=self.period,
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aggregate='avg'
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)
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cpu_usage = None
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for stat in statistics:
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avg_col_idx = stat['columns'].index('avg')
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values = [r[avg_col_idx] for r in stat['statistics']]
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value = float(sum(values)) / len(values)
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cpu_usage = value
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return cpu_usage
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raise exception.UnsupportedDataSource(
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strategy=self.name, datasource=self.config.datasource)
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return self.datasource_backend.get_instance_cpu_usage(
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instance.uuid, self.period, 'mean', granularity=300)
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def calculate_score_node(self, node):
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"""Calculate the score that represent the utilization level
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