def test_detector_should_return_0_for_calculate_the_number_of_standard_deviations_of_metric_of_a_new_metric():
# adding this two events will generate a standard deviation of: cpu: 0.5, mem: 5
detector = Detector()
event = {
'target' : 'edge_01',
'bucket' : 'edge',
'metrics' : {'cpu': 4.0, 'mem': 30},
'timestamp': 8192819082,
}
assert 0 == detector.calculate_the_number_of_standard_deviations(event, "cpu")
assert 0 == detector.calculate_the_number_of_standard_deviations(event, "mem")
def test_detector_should_be_able_to_calculate_the_number_of_standard_deviations_of_metric():
# adding this two events will generate a standard deviation of: cpu: 0.5, mem: 5
models.add_event('edge', 'edge_01', {u'cpu': u'2', u'mem': u'10'}, time.time())
models.add_event('edge', 'edge_02', {u'cpu': u'3', u'mem': u'20'}, time.time())
detector = Detector()
event = {
'target' : 'edge_01',
'bucket' : 'edge',
'metrics' : {'cpu': 4.0, 'mem': 30},
'timestamp': 8192819082,
}
assert 3 == detector.calculate_the_number_of_standard_deviations(event, "cpu")
assert 3 == detector.calculate_the_number_of_standard_deviations(event, "mem")
