121 lines
4.6 KiB
Python
121 lines
4.6 KiB
Python
#
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# Licensed under the Apache License, Version 2.0 (the "License"); you may
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# not use this file except in compliance with the License. You may obtain
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# 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, WITHOUT
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# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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# License for the specific language governing permissions and limitations
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# under the License.
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import wsme
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from wsme import types as wtypes
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from aodh.api.controllers.v2 import base
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from aodh.api.controllers.v2 import utils as v2_utils
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from aodh.i18n import _
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from aodh import storage
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class AlarmThresholdRule(base.AlarmRule):
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"""Alarm Threshold Rule
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Describe when to trigger the alarm based on computed statistics
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"""
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meter_name = wsme.wsattr(wtypes.text, mandatory=True)
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"The name of the meter"
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# FIXME(sileht): default doesn't work
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# workaround: default is set in validate method
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query = wsme.wsattr([base.Query], default=[])
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"""The query to find the data for computing statistics.
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Ownership settings are automatically included based on the Alarm owner.
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"""
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period = wsme.wsattr(wtypes.IntegerType(minimum=1), default=60)
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"The time range in seconds over which query"
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comparison_operator = base.AdvEnum('comparison_operator', str,
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'lt', 'le', 'eq', 'ne', 'ge', 'gt',
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default='eq')
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"The comparison against the alarm threshold"
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threshold = wsme.wsattr(float, mandatory=True)
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"The threshold of the alarm"
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statistic = base.AdvEnum('statistic', str, 'max', 'min', 'avg', 'sum',
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'count', default='avg')
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"The statistic to compare to the threshold"
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evaluation_periods = wsme.wsattr(wtypes.IntegerType(minimum=1), default=1)
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"The number of historical periods to evaluate the threshold"
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exclude_outliers = wsme.wsattr(bool, default=False)
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"Whether datapoints with anomalously low sample counts are excluded"
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def __init__(self, query=None, **kwargs):
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if query:
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query = [base.Query(**q) for q in query]
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super(AlarmThresholdRule, self).__init__(query=query, **kwargs)
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@staticmethod
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def validate(threshold_rule):
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# note(sileht): wsme default doesn't work in some case
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# workaround for https://bugs.launchpad.net/wsme/+bug/1227039
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if not threshold_rule.query:
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threshold_rule.query = []
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# Timestamp is not allowed for AlarmThresholdRule query, as the alarm
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# evaluator will construct timestamp bounds for the sequence of
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# statistics queries as the sliding evaluation window advances
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# over time.
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v2_utils.validate_query(threshold_rule.query,
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storage.SampleFilter.__init__,
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allow_timestamps=False)
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return threshold_rule
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@staticmethod
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def validate_alarm(alarm):
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# ensure an implicit constraint on project_id is added to
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# the query if not already present
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alarm.threshold_rule.query = v2_utils.sanitize_query(
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alarm.threshold_rule.query,
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storage.SampleFilter.__init__,
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on_behalf_of=alarm.project_id
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)
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@property
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def default_description(self):
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return (_('Alarm when %(meter_name)s is %(comparison_operator)s a '
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'%(statistic)s of %(threshold)s over %(period)s seconds') %
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dict(comparison_operator=self.comparison_operator,
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statistic=self.statistic,
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threshold=self.threshold,
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meter_name=self.meter_name,
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period=self.period))
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def as_dict(self):
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rule = self.as_dict_from_keys(['period', 'comparison_operator',
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'threshold', 'statistic',
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'evaluation_periods', 'meter_name',
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'exclude_outliers'])
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rule['query'] = [q.as_dict() for q in self.query]
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return rule
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@classmethod
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def sample(cls):
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return cls(meter_name='cpu_util',
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period=60,
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evaluation_periods=1,
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threshold=300.0,
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statistic='avg',
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comparison_operator='gt',
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query=[{'field': 'resource_id',
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'value': '2a4d689b-f0b8-49c1-9eef-87cae58d80db',
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'op': 'eq',
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'type': 'string'}])
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