49f53f35a5
Currently we run tests which uses real backend or real daemons with other unit tests. This CR is initial for sequence of functional tests implementation. It contains only moving files and modules to right directories and fixing tox.ini. This approach allows to avoid constantly rebase conflicts, because git handles file removing correct. Next step - separate classes and functions from moved files to right test types. Depends-On: Ifdb0de150b2c738117308b2aae6c0c197e162821 Change-Id: I16b84ed83ac075658626f3ec6a35a24e228b61e7 Partialy-Implement: blueprint ceilometer-functional-tests
439 lines
21 KiB
Python
439 lines
21 KiB
Python
#
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# Copyright 2015 eNovance
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#
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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 datetime
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import unittest
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import uuid
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import mock
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from oslo_serialization import jsonutils
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from oslo_utils import timeutils
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from oslotest import mockpatch
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import pytz
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import six
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from six import moves
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from ceilometer.alarm.evaluator import gnocchi
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from ceilometer.alarm.storage import models
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from ceilometer.tests import constants
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from ceilometer.tests.unit.alarm.evaluator import base
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class FakeResponse(object):
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def __init__(self, code, data):
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if code == 200:
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self.values = [d[2] for d in data]
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else:
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self.values = []
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self.text = jsonutils.dumps(data)
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self.status_code = code
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class TestGnocchiThresholdEvaluate(base.TestEvaluatorBase):
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EVALUATOR = gnocchi.GnocchiThresholdEvaluator
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def setUp(self):
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ks_client = mock.Mock(auth_token='fake_token')
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ks_client.users.find.return_value = 'gnocchi'
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self.useFixture(mockpatch.Patch(
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'keystoneclient.v2_0.client.Client',
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return_value=ks_client))
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super(TestGnocchiThresholdEvaluate, self).setUp()
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self.useFixture(mockpatch.Patch('ceilometerclient.client.get_client',
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return_value=self.api_client))
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self.requests = self.useFixture(mockpatch.Patch(
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'ceilometer.alarm.evaluator.gnocchi.requests')).mock
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def prepare_alarms(self):
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self.alarms = [
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models.Alarm(name='instance_running_hot',
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description='instance_running_hot',
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type='gnocchi_resources_threshold',
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enabled=True,
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user_id='foobar',
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project_id='snafu',
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alarm_id=str(uuid.uuid4()),
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state='insufficient data',
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state_timestamp=constants.MIN_DATETIME,
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timestamp=constants.MIN_DATETIME,
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insufficient_data_actions=[],
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ok_actions=[],
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alarm_actions=[],
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repeat_actions=False,
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time_constraints=[],
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rule=dict(
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comparison_operator='gt',
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threshold=80.0,
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evaluation_periods=5,
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aggregation_method='mean',
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granularity=60,
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metric='cpu_util',
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resource_type='instance',
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resource_id='my_instance')
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),
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models.Alarm(name='group_running_idle',
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description='group_running_idle',
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type='gnocchi_aggregation_by_metrics_threshold',
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enabled=True,
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user_id='foobar',
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project_id='snafu',
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state='insufficient data',
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state_timestamp=constants.MIN_DATETIME,
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timestamp=constants.MIN_DATETIME,
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insufficient_data_actions=[],
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ok_actions=[],
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alarm_actions=[],
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repeat_actions=False,
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alarm_id=str(uuid.uuid4()),
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time_constraints=[],
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rule=dict(
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comparison_operator='le',
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threshold=10.0,
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evaluation_periods=4,
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aggregation_method='max',
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granularity=300,
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metrics=['0bb1604d-1193-4c0a-b4b8-74b170e35e83',
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'9ddc209f-42f8-41e1-b8f1-8804f59c4053']),
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),
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models.Alarm(name='instance_not_running',
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description='instance_running_hot',
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type='gnocchi_aggregation_by_resources_threshold',
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enabled=True,
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user_id='foobar',
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project_id='snafu',
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alarm_id=str(uuid.uuid4()),
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state='insufficient data',
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state_timestamp=constants.MIN_DATETIME,
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timestamp=constants.MIN_DATETIME,
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insufficient_data_actions=[],
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ok_actions=[],
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alarm_actions=[],
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repeat_actions=False,
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time_constraints=[],
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rule=dict(
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comparison_operator='gt',
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threshold=80.0,
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evaluation_periods=6,
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aggregation_method='mean',
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granularity=50,
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metric='cpu_util',
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resource_type='instance',
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query='{"=": {"server_group": '
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'"my_autoscaling_group"}}')
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),
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]
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@staticmethod
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def _get_stats(granularity, values):
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now = timeutils.utcnow_ts()
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return FakeResponse(
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200, [[six.text_type(now - len(values) * granularity),
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granularity, value] for value in values])
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@staticmethod
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def _reason_data(disposition, count, most_recent):
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return {'type': 'threshold', 'disposition': disposition,
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'count': count, 'most_recent': most_recent}
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def _set_all_rules(self, field, value):
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for alarm in self.alarms:
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alarm.rule[field] = value
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def test_retry_transient_api_failure(self):
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means = self._get_stats(60, [self.alarms[0].rule['threshold'] - v
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for v in moves.xrange(5)])
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maxs = self._get_stats(300, [self.alarms[1].rule['threshold'] + v
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for v in moves.xrange(1, 4)])
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avgs2 = self._get_stats(50, [self.alarms[2].rule['threshold'] - v
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for v in moves.xrange(6)])
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self.requests.get.side_effect = [Exception('boom'),
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FakeResponse(500, "error"),
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means,
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maxs]
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self.requests.post.side_effect = [FakeResponse(500, "error"), avgs2]
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self._evaluate_all_alarms()
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self._assert_all_alarms('insufficient data')
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self._evaluate_all_alarms()
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self._assert_all_alarms('ok')
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def test_simple_insufficient(self):
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self._set_all_alarms('ok')
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self.requests.get.return_value = FakeResponse(200, [])
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self.requests.post.return_value = FakeResponse(200, [])
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self._evaluate_all_alarms()
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self._assert_all_alarms('insufficient data')
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expected = [mock.call(alarm.alarm_id, state='insufficient data')
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for alarm in self.alarms]
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update_calls = self.api_client.alarms.set_state.call_args_list
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self.assertEqual(expected, update_calls)
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expected = [mock.call(
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alarm,
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'ok',
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('%d datapoints are unknown'
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% alarm.rule['evaluation_periods']),
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self._reason_data('unknown',
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alarm.rule['evaluation_periods'],
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None))
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for alarm in self.alarms]
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self.assertEqual(expected, self.notifier.notify.call_args_list)
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@mock.patch.object(timeutils, 'utcnow')
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def test_simple_alarm_trip(self, utcnow):
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utcnow.return_value = datetime.datetime(2015, 1, 26, 12, 57, 0, 0)
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self._set_all_alarms('ok')
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avgs = self._get_stats(60, [self.alarms[0].rule['threshold'] + v
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for v in moves.xrange(1, 6)])
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maxs = self._get_stats(300, [self.alarms[1].rule['threshold'] - v
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for v in moves.xrange(4)])
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avgs2 = self._get_stats(50, [self.alarms[2].rule['threshold'] + v
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for v in moves.xrange(1, 7)])
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self.requests.get.side_effect = [avgs, maxs]
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self.requests.post.side_effect = [avgs2]
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self._evaluate_all_alarms()
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expected_headers = {'X-Auth-Token': 'fake_token',
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'Content-Type': 'application/json'}
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start_alarm1 = "2015-01-26T12:51:00"
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start_alarm2 = "2015-01-26T12:32:00"
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start_alarm3 = "2015-01-26T12:51:10"
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end = "2015-01-26T12:57:00"
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self.assertEqual([
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mock.call(url='http://localhost:8041/v1/resource/instance/'
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'my_instance/metric/cpu_util/measures',
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params={'aggregation': 'mean',
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'start': start_alarm1, 'end': end},
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headers=expected_headers),
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mock.call(url='http://localhost:8041/v1/aggregation/metric',
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params={'aggregation': 'max',
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'start': start_alarm2, 'end': end,
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'metric[]': [
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'0bb1604d-1193-4c0a-b4b8-74b170e35e83',
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'9ddc209f-42f8-41e1-b8f1-8804f59c4053']},
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headers=expected_headers)],
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self.requests.get.mock_calls)
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self.assertEqual([
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mock.call(url='http://localhost:8041/v1/aggregation/resource/'
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'instance/metric/cpu_util',
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params={'aggregation': 'mean',
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'start': start_alarm3, 'end': end},
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data='{"=": {"server_group": "my_autoscaling_group"}}',
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headers=expected_headers),
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],
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self.requests.post.mock_calls)
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self._assert_all_alarms('alarm')
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expected = [mock.call(alarm.alarm_id, state='alarm')
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for alarm in self.alarms]
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update_calls = self.api_client.alarms.set_state.call_args_list
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self.assertEqual(expected, update_calls)
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reasons = ['Transition to alarm due to 5 samples outside'
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' threshold, most recent: %s' % avgs.values[-1],
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'Transition to alarm due to 4 samples outside'
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' threshold, most recent: %s' % maxs.values[-1],
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'Transition to alarm due to 6 samples outside'
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' threshold, most recent: %s' % avgs2.values[-1],
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]
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reason_datas = [self._reason_data('outside', 5, avgs.values[-1]),
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self._reason_data('outside', 4, maxs.values[-1]),
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self._reason_data('outside', 6, avgs2.values[-1])]
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expected = [mock.call(alarm, 'ok', reason, reason_data)
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for alarm, reason, reason_data
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in zip(self.alarms, reasons, reason_datas)]
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self.assertEqual(expected, self.notifier.notify.call_args_list)
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def test_simple_alarm_clear(self):
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self._set_all_alarms('alarm')
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avgs = self._get_stats(60, [self.alarms[0].rule['threshold'] - v
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for v in moves.xrange(5)])
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maxs = self._get_stats(300, [self.alarms[1].rule['threshold'] + v
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for v in moves.xrange(1, 5)])
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avgs2 = self._get_stats(50, [self.alarms[2].rule['threshold'] - v
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for v in moves.xrange(6)])
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self.requests.post.side_effect = [avgs2]
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self.requests.get.side_effect = [avgs, maxs]
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self._evaluate_all_alarms()
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self._assert_all_alarms('ok')
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expected = [mock.call(alarm.alarm_id, state='ok')
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for alarm in self.alarms]
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update_calls = self.api_client.alarms.set_state.call_args_list
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self.assertEqual(expected, update_calls)
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reasons = ['Transition to ok due to 5 samples inside'
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' threshold, most recent: %s' % avgs.values[-1],
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'Transition to ok due to 4 samples inside'
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' threshold, most recent: %s' % maxs.values[-1],
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'Transition to ok due to 6 samples inside'
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' threshold, most recent: %s' % avgs2.values[-1]]
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reason_datas = [self._reason_data('inside', 5, avgs.values[-1]),
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self._reason_data('inside', 4, maxs.values[-1]),
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self._reason_data('inside', 6, avgs2.values[-1])]
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expected = [mock.call(alarm, 'alarm', reason, reason_data)
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for alarm, reason, reason_data
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in zip(self.alarms, reasons, reason_datas)]
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self.assertEqual(expected, self.notifier.notify.call_args_list)
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def test_equivocal_from_known_state(self):
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self._set_all_alarms('ok')
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avgs = self._get_stats(60, [self.alarms[0].rule['threshold'] + v
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for v in moves.xrange(5)])
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maxs = self._get_stats(300, [self.alarms[1].rule['threshold'] - v
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for v in moves.xrange(-1, 3)])
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avgs2 = self._get_stats(50, [self.alarms[2].rule['threshold'] + v
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for v in moves.xrange(6)])
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self.requests.post.side_effect = [avgs2]
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self.requests.get.side_effect = [avgs, maxs]
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self._evaluate_all_alarms()
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self._assert_all_alarms('ok')
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self.assertEqual(
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[],
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self.api_client.alarms.set_state.call_args_list)
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self.assertEqual([], self.notifier.notify.call_args_list)
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def test_equivocal_from_known_state_and_repeat_actions(self):
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self._set_all_alarms('ok')
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self.alarms[1].repeat_actions = True
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avgs = self._get_stats(60, [self.alarms[0].rule['threshold'] + v
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for v in moves.xrange(5)])
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maxs = self._get_stats(300, [self.alarms[1].rule['threshold'] - v
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for v in moves.xrange(-1, 3)])
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avgs2 = self._get_stats(50, [self.alarms[2].rule['threshold'] + v
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for v in moves.xrange(6)])
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self.requests.post.side_effect = [avgs2]
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self.requests.get.side_effect = [avgs, maxs]
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self._evaluate_all_alarms()
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self._assert_all_alarms('ok')
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self.assertEqual([], self.api_client.alarms.set_state.call_args_list)
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reason = ('Remaining as ok due to 4 samples inside'
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' threshold, most recent: 8.0')
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reason_datas = self._reason_data('inside', 4, 8.0)
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expected = [mock.call(self.alarms[1], 'ok', reason, reason_datas)]
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self.assertEqual(expected, self.notifier.notify.call_args_list)
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def test_unequivocal_from_known_state_and_repeat_actions(self):
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self._set_all_alarms('alarm')
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self.alarms[1].repeat_actions = True
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avgs = self._get_stats(60, [self.alarms[0].rule['threshold'] + v
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for v in moves.xrange(1, 6)])
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maxs = self._get_stats(300, [self.alarms[1].rule['threshold'] - v
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for v in moves.xrange(4)])
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avgs2 = self._get_stats(50, [self.alarms[2].rule['threshold'] + v
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for v in moves.xrange(6)])
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self.requests.post.side_effect = [avgs2]
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self.requests.get.side_effect = [avgs, maxs]
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self._evaluate_all_alarms()
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self._assert_all_alarms('alarm')
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self.assertEqual([], self.api_client.alarms.set_state.call_args_list)
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reason = ('Remaining as alarm due to 4 samples outside'
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' threshold, most recent: 7.0')
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reason_datas = self._reason_data('outside', 4, 7.0)
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expected = [mock.call(self.alarms[1], 'alarm',
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reason, reason_datas)]
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self.assertEqual(expected, self.notifier.notify.call_args_list)
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def test_state_change_and_repeat_actions(self):
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self._set_all_alarms('ok')
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self.alarms[0].repeat_actions = True
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self.alarms[1].repeat_actions = True
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avgs = self._get_stats(60, [self.alarms[0].rule['threshold'] + v
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for v in moves.xrange(1, 6)])
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maxs = self._get_stats(300, [self.alarms[1].rule['threshold'] - v
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for v in moves.xrange(4)])
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avgs2 = self._get_stats(50, [self.alarms[2].rule['threshold'] + v
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for v in moves.xrange(1, 7)])
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self.requests.post.side_effect = [avgs2]
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self.requests.get.side_effect = [avgs, maxs]
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self._evaluate_all_alarms()
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self._assert_all_alarms('alarm')
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expected = [mock.call(alarm.alarm_id, state='alarm')
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for alarm in self.alarms]
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update_calls = self.api_client.alarms.set_state.call_args_list
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self.assertEqual(expected, update_calls)
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reasons = ['Transition to alarm due to 5 samples outside'
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' threshold, most recent: %s' % avgs.values[-1],
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'Transition to alarm due to 4 samples outside'
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' threshold, most recent: %s' % maxs.values[-1],
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'Transition to alarm due to 6 samples outside'
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' threshold, most recent: %s' % avgs2.values[-1]]
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reason_datas = [self._reason_data('outside', 5, avgs.values[-1]),
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self._reason_data('outside', 4, maxs.values[-1]),
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self._reason_data('outside', 6, avgs2.values[-1])]
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expected = [mock.call(alarm, 'ok', reason, reason_data)
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for alarm, reason, reason_data
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in zip(self.alarms, reasons, reason_datas)]
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self.assertEqual(expected, self.notifier.notify.call_args_list)
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def test_equivocal_from_unknown(self):
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self._set_all_alarms('insufficient data')
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avgs = self._get_stats(60, [self.alarms[0].rule['threshold'] + v
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for v in moves.xrange(1, 6)])
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maxs = self._get_stats(300, [self.alarms[1].rule['threshold'] - v
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for v in moves.xrange(4)])
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avgs2 = self._get_stats(50, [self.alarms[2].rule['threshold'] + v
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for v in moves.xrange(1, 7)])
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self.requests.post.side_effect = [avgs2]
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self.requests.get.side_effect = [avgs, maxs]
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self._evaluate_all_alarms()
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self._assert_all_alarms('alarm')
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expected = [mock.call(alarm.alarm_id, state='alarm')
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for alarm in self.alarms]
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update_calls = self.api_client.alarms.set_state.call_args_list
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self.assertEqual(expected, update_calls)
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reasons = ['Transition to alarm due to 5 samples outside'
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' threshold, most recent: %s' % avgs.values[-1],
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'Transition to alarm due to 4 samples outside'
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' threshold, most recent: %s' % maxs.values[-1],
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'Transition to alarm due to 6 samples outside'
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' threshold, most recent: %s' % avgs2.values[-1]]
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reason_datas = [self._reason_data('outside', 5, avgs.values[-1]),
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self._reason_data('outside', 4, maxs.values[-1]),
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self._reason_data('outside', 6, avgs2.values[-1])]
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expected = [mock.call(alarm, 'insufficient data',
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reason, reason_data)
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for alarm, reason, reason_data
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|
in zip(self.alarms, reasons, reason_datas)]
|
|
self.assertEqual(expected, self.notifier.notify.call_args_list)
|
|
|
|
@unittest.skipIf(six.PY3,
|
|
"the ceilometer base class is not python 3 ready")
|
|
@mock.patch.object(timeutils, 'utcnow')
|
|
def test_no_state_change_outside_time_constraint(self, mock_utcnow):
|
|
self._set_all_alarms('ok')
|
|
self.alarms[0].time_constraints = [
|
|
{'name': 'test',
|
|
'description': 'test',
|
|
'start': '0 11 * * *', # daily at 11:00
|
|
'duration': 10800, # 3 hours
|
|
'timezone': 'Europe/Ljubljana'}
|
|
]
|
|
self.alarms[1].time_constraints = self.alarms[0].time_constraints
|
|
self.alarms[2].time_constraints = self.alarms[0].time_constraints
|
|
dt = datetime.datetime(2014, 1, 1, 15, 0, 0,
|
|
tzinfo=pytz.timezone('Europe/Ljubljana'))
|
|
mock_utcnow.return_value = dt.astimezone(pytz.UTC)
|
|
self.requests.get.return_value = []
|
|
self._evaluate_all_alarms()
|
|
self._assert_all_alarms('ok')
|
|
update_calls = self.api_client.alarms.set_state.call_args_list
|
|
self.assertEqual([], update_calls,
|
|
"Alarm should not change state if the current "
|
|
" time is outside its time constraint.")
|
|
self.assertEqual([], self.notifier.notify.call_args_list)
|