def get_matching_watches():
if watch_name:
yield watchrule.WatchRule.load(cnxt, watch_name)
else:
for wr in db_api.watch_rule_get_all(cnxt):
if watchrule.rule_can_use_sample(wr, stats_data):
yield watchrule.WatchRule.load(cnxt, watch=wr)
def test_create_watch_data_match(self):
rule = {
u'EvaluationPeriods': u'1',
u'AlarmDescription': u'test alarm',
u'Period': u'300',
u'ComparisonOperator': u'GreaterThanThreshold',
u'Statistic': u'SampleCount',
u'Threshold': u'2',
u'Dimensions': [{
u'Name': 'AutoScalingGroupName',
u'Value': 'group_x'
}],
u'MetricName': u'CreateDataMetric'
}
self.wr = watchrule.WatchRule(context=self.ctx,
watch_name='create_data_test',
stack_id=self.stack_id,
rule=rule)
self.wr.store()
data = {
u'CreateDataMetric': {
"Unit": "Counter",
"Value": "1",
"Dimensions": [{
u'AutoScalingGroupName': u'group_x'
}]
}
}
self.assertTrue(watchrule.rule_can_use_sample(self.wr, data))
def get_matching_watches():
if watch_name:
yield watchrule.WatchRule.load(cnxt, watch_name)
else:
for wr in db_api.watch_rule_get_all(cnxt):
if watchrule.rule_can_use_sample(wr, stats_data):
yield watchrule.WatchRule.load(cnxt, watch=wr)
def test_create_watch_data_not_match_dimensions(self):
rule = {u'EvaluationPeriods': u'1',
u'AlarmDescription': u'test alarm',
u'Period': u'300',
u'ComparisonOperator': u'GreaterThanThreshold',
u'Statistic': u'SampleCount',
u'Threshold': u'2',
u'Dimensions': [{u'Name': 'AutoScalingGroupName',
u'Value': 'group_x'}],
u'MetricName': u'CreateDataMetric'}
self.wr = watchrule.WatchRule(context=self.ctx,
watch_name='create_data_test',
stack_id=self.stack_id, rule=rule)
self.wr.store()
data = {u'CreateDataMetric': {"Unit": "Counter",
"Value": "1",
"Dimensions": [
{u'AutoScalingGroupName':
u'not_this'}]},
u'CreateDataMetric': {"Unit": "Counter",
"Value": "1",
"Dimensions": [
{u'wrong_key':
u'group_x'}]}}
self.assertFalse(watchrule.rule_can_use_sample(self.wr, data))
def test_create_watch_data_not_match_dimensions(self):
rule = {
u"EvaluationPeriods": u"1",
u"AlarmDescription": u"test alarm",
u"Period": u"300",
u"ComparisonOperator": u"GreaterThanThreshold",
u"Statistic": u"SampleCount",
u"Threshold": u"2",
u"Dimensions": [{u"Name": "AutoScalingGroupName", u"Value": "group_x"}],
u"MetricName": u"CreateDataMetric",
}
self.wr = watchrule.WatchRule(
context=self.ctx, watch_name="create_data_test", stack_id=self.stack_id, rule=rule
)
self.wr.store()
data = {
u"CreateDataMetric": {
"Unit": "Counter",
"Value": "1",
"Dimensions": [{u"AutoScalingGroupName": u"not_this"}],
},
u"CreateDataMetric": {"Unit": "Counter", "Value": "1", "Dimensions": [{u"wrong_key": u"group_x"}]},
}
self.assertFalse(watchrule.rule_can_use_sample(self.wr, data))