Change-Id: I003c9e88abb08b11c22b008936413ee51f6096b1
Closes-Bug: #1817533
(cherry picked from commit 594039f794)
187 lines
7.8 KiB
Python
187 lines
7.8 KiB
Python
# -*- encoding: utf-8 -*-
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# Copyright (c) 2017 Servionica
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#
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# Authors: Alexander Chadin <a.chadin@servionica.ru>
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
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# implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from datetime import datetime
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from datetime import timedelta
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import time
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from oslo_config import cfg
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from oslo_log import log
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from watcher.common import clients
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from watcher.common import exception
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from watcher.common import utils as common_utils
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from watcher.datasource import base
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CONF = cfg.CONF
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LOG = log.getLogger(__name__)
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class GnocchiHelper(base.DataSourceBase):
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NAME = 'gnocchi'
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METRIC_MAP = base.DataSourceBase.METRIC_MAP['gnocchi']
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def __init__(self, osc=None):
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""":param osc: an OpenStackClients instance"""
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self.osc = osc if osc else clients.OpenStackClients()
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self.gnocchi = self.osc.gnocchi()
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def query_retry(self, f, *args, **kwargs):
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for i in range(CONF.gnocchi_client.query_max_retries):
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try:
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return f(*args, **kwargs)
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except Exception as e:
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LOG.exception(e)
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time.sleep(CONF.gnocchi_client.query_timeout)
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raise exception.DataSourceNotAvailable(datasource='gnocchi')
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def check_availability(self):
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try:
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self.query_retry(self.gnocchi.status.get)
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except Exception:
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return 'not available'
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return 'available'
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def list_metrics(self):
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"""List the user's meters."""
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try:
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response = self.query_retry(f=self.gnocchi.metric.list)
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except Exception:
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return set()
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else:
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return set([metric['name'] for metric in response])
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def statistic_aggregation(self, resource_id=None, meter_name=None,
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period=300, granularity=300, dimensions=None,
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aggregation='avg', group_by='*'):
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"""Representing a statistic aggregate by operators
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:param resource_id: id of resource to list statistics for.
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:param meter_name: meter name of which we want the statistics.
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:param period: Period in seconds over which to group samples.
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:param granularity: frequency of marking metric point, in seconds.
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:param dimensions: dimensions (dict). This param isn't used in
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Gnocchi datasource.
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:param aggregation: Should be chosen in accordance with policy
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aggregations.
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:param group_by: list of columns to group the metrics to be returned.
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This param isn't used in Gnocchi datasource.
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:return: value of aggregated metric
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"""
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stop_time = datetime.utcnow()
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start_time = stop_time - timedelta(seconds=(int(period)))
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if not common_utils.is_uuid_like(resource_id):
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kwargs = dict(query={"=": {"original_resource_id": resource_id}},
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limit=1)
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resources = self.query_retry(
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f=self.gnocchi.resource.search, **kwargs)
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if not resources:
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raise exception.ResourceNotFound(name='gnocchi',
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id=resource_id)
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resource_id = resources[0]['id']
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raw_kwargs = dict(
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metric=meter_name,
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start=start_time,
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stop=stop_time,
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resource_id=resource_id,
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granularity=granularity,
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aggregation=aggregation,
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)
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kwargs = {k: v for k, v in raw_kwargs.items() if k and v}
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statistics = self.query_retry(
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f=self.gnocchi.metric.get_measures, **kwargs)
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if statistics:
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# return value of latest measure
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# measure has structure [time, granularity, value]
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return statistics[-1][2]
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def get_host_cpu_usage(self, resource_id, period, aggregate,
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granularity=300):
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meter_name = self.METRIC_MAP.get('host_cpu_usage')
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return self.statistic_aggregation(resource_id, meter_name, period,
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granularity, aggregation=aggregate)
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def get_instance_cpu_usage(self, resource_id, period, aggregate,
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granularity=300):
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meter_name = self.METRIC_MAP.get('instance_cpu_usage')
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return self.statistic_aggregation(resource_id, meter_name, period,
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granularity, aggregation=aggregate)
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def get_host_memory_usage(self, resource_id, period, aggregate,
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granularity=300):
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meter_name = self.METRIC_MAP.get('host_memory_usage')
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return self.statistic_aggregation(resource_id, meter_name, period,
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granularity, aggregation=aggregate)
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def get_instance_memory_usage(self, resource_id, period, aggregate,
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granularity=300):
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meter_name = self.METRIC_MAP.get('instance_ram_usage')
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return self.statistic_aggregation(resource_id, meter_name, period,
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granularity, aggregation=aggregate)
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def get_instance_l3_cache_usage(self, resource_id, period, aggregate,
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granularity=300):
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meter_name = self.METRIC_MAP.get('instance_l3_cache_usage')
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return self.statistic_aggregation(resource_id, meter_name, period,
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granularity, aggregation=aggregate)
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def get_instance_ram_allocated(self, resource_id, period, aggregate,
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granularity=300):
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meter_name = self.METRIC_MAP.get('instance_ram_allocated')
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return self.statistic_aggregation(resource_id, meter_name, period,
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granularity, aggregation=aggregate)
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def get_instance_root_disk_allocated(self, resource_id, period, aggregate,
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granularity=300):
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meter_name = self.METRIC_MAP.get('instance_root_disk_size')
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return self.statistic_aggregation(resource_id, meter_name, period,
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granularity, aggregation=aggregate)
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def get_host_outlet_temperature(self, resource_id, period, aggregate,
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granularity=300):
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meter_name = self.METRIC_MAP.get('host_outlet_temp')
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return self.statistic_aggregation(resource_id, meter_name, period,
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granularity, aggregation=aggregate)
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def get_host_inlet_temperature(self, resource_id, period, aggregate,
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granularity=300):
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meter_name = self.METRIC_MAP.get('host_inlet_temp')
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return self.statistic_aggregation(resource_id, meter_name, period,
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granularity, aggregation=aggregate)
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def get_host_airflow(self, resource_id, period, aggregate,
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granularity=300):
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meter_name = self.METRIC_MAP.get('host_airflow')
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return self.statistic_aggregation(resource_id, meter_name, period,
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granularity, aggregation=aggregate)
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def get_host_power(self, resource_id, period, aggregate,
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granularity=300):
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meter_name = self.METRIC_MAP.get('host_power')
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return self.statistic_aggregation(resource_id, meter_name, period,
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granularity, aggregation=aggregate)
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