Removed GaugeAverage since it is unlikely to be needed
and easy to reimplement later. added tests for GaugeMax and CumulativeRange CumulativeTotal was renamed to CumulativeRange
This commit is contained in:
adriant
parent
2b4a3d080c
commit
8686f28659
@ -121,6 +121,6 @@ class Volume(BaseModelConstruct):
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class Network(BaseModelConstruct):
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relevant_meters = ["network.outgoing.bytes", "network.incoming.bytes"]
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transformer = transformers.CumulativeTotal()
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transformer = transformers.CumulativeRange()
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type = "network_interface"
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@ -3,6 +3,10 @@ import constants
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import helpers
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class TransformerValidationError(BaseException):
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pass
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class Transformer(object):
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meter_type = None
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@ -16,13 +20,15 @@ class Transformer(object):
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if self.meter_type is None:
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for meter in self.required_meters:
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if meter not in meters:
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raise AttributeError("Required meters: " +
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str(self.required_meters))
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raise TransformerValidationError(
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"Required meters: " +
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str(self.required_meters))
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else:
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for meter in meters.values():
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if meter.type != self.meter_type:
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raise AttributeError("Meters must all be of type: " +
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self.meter_type)
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raise TransformerValidationError(
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"Meters must all be of type: " +
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self.meter_type)
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def _transform_usage(self, meters):
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raise NotImplementedError
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@ -101,19 +107,19 @@ class GaugeMax(Transformer):
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def _transform_usage(self, meters):
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usage_dict = {}
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for meter in meters.values():
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for name, meter in meters.iteritems():
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usage = meter.usage()
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max_vol = max([v["counter_volume"] for v in usage])
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usage_dict[meter.name] = max_vol
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usage_dict[name] = max_vol
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return usage_dict
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class CumulativeTotal(Transformer):
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class CumulativeRange(Transformer):
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meter_type = 'cumulative'
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def _transform_usage(self, meters):
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usage_dict = {}
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for meter in meters.values():
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for name, meter in meters.iteritems():
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measurements = meter.usage()
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measurements = sorted(measurements, key=lambda x: x["timestamp"])
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count = 0
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@ -131,5 +137,5 @@ class CumulativeTotal(Transformer):
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if count > 1:
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total_usage = usage - measurements[0]["counter_volume"]
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usage_dict[meter.name] = total_usage
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usage_dict[name] = total_usage
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return usage_dict
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@ -1,22 +1,32 @@
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import artifice.transformers
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import artifice.constants
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from artifice.transformers import TransformerValidationError
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import artifice.constants as constants
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import unittest
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import mock
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class testdata:
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t0 = '2014-01-01T00:00:00'
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t1 = '2014-01-01T01:00:00'
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flavor = 'm1.tiny'
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t0_10 = '2014-01-01T00:10:00'
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t0_20 = '2014-01-01T00:30:00'
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t0_30 = '2014-01-01T00:30:00'
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t0_40 = '2014-01-01T00:40:00'
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t0_50 = '2014-01-01T00:50:00'
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t1 = '2014-01-01T01:00:00'
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flavor = 'm1.tiny'
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flavor2 = 'm1.large'
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class TestMeter(object):
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def __init__(self, data):
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def __init__(self, data, mtype=None):
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self.data = data
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self.type = mtype
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def usage(self):
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return self.data
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class UptimeTransformerTests(unittest.TestCase):
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def test_required_metrics_not_present(self):
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"""
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@ -24,8 +34,8 @@ class UptimeTransformerTests(unittest.TestCase):
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is not present.
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"""
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xform = artifice.transformers.Uptime()
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with self.assertRaises(AttributeError) as e:
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with self.assertRaises(TransformerValidationError) as e:
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xform.transform_usage({})
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self.assertTrue(e.exception.message.startswith('Required meters:'))
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@ -59,8 +69,8 @@ class UptimeTransformerTests(unittest.TestCase):
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{'timestamp': testdata.t1, 'counter_volume': testdata.flavor},
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]),
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'state': TestMeter([
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{'timestamp': testdata.t0, 'counter_volume': artifice.constants.active},
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{'timestamp': testdata.t1, 'counter_volume': artifice.constants.active}
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{'timestamp': testdata.t0, 'counter_volume': constants.active},
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{'timestamp': testdata.t1, 'counter_volume': constants.active}
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]),
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}
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@ -73,7 +83,6 @@ class UptimeTransformerTests(unittest.TestCase):
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Test that a machine offline for a 1h period with constant flavor
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works and gives zero uptime.
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"""
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xform = artifice.transformers.Uptime()
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meters = {
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'flavor': TestMeter([
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@ -81,8 +90,8 @@ class UptimeTransformerTests(unittest.TestCase):
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{'timestamp': testdata.t1, 'counter_volume': testdata.flavor},
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]),
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'state': TestMeter([
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{'timestamp': testdata.t0, 'counter_volume': artifice.constants.stopped},
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{'timestamp': testdata.t1, 'counter_volume': artifice.constants.stopped}
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{'timestamp': testdata.t0, 'counter_volume': constants.stopped},
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{'timestamp': testdata.t1, 'counter_volume': constants.stopped}
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]),
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}
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@ -90,7 +99,6 @@ class UptimeTransformerTests(unittest.TestCase):
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# there should be no usage, the machine was off.
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self.assertEqual({}, result)
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def test_shutdown_during_period(self):
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"""
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Test that a machine run for 0.5 then shutdown gives 0.5h uptime.
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@ -102,9 +110,9 @@ class UptimeTransformerTests(unittest.TestCase):
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{'timestamp': testdata.t1, 'counter_volume': testdata.flavor},
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]),
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'state': TestMeter([
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{'timestamp': testdata.t0, 'counter_volume': artifice.constants.active},
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{'timestamp': testdata.t0_30, 'counter_volume': artifice.constants.stopped},
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{'timestamp': testdata.t1, 'counter_volume': artifice.constants.stopped}
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{'timestamp': testdata.t0, 'counter_volume': constants.active},
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{'timestamp': testdata.t0_30, 'counter_volume': constants.stopped},
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{'timestamp': testdata.t1, 'counter_volume': constants.stopped}
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]),
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}
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@ -114,8 +122,8 @@ class UptimeTransformerTests(unittest.TestCase):
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def test_online_flavor_change(self):
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"""
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Test that a machine run for 0.5h as m1.tiny, resized to m1.large, and run
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for a further 0.5 yields 0.5h of uptime in each class.
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Test that a machine run for 0.5h as m1.tiny, resized to m1.large,
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and run for a further 0.5 yields 0.5h of uptime in each class.
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"""
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meters = {
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'flavor': TestMeter([
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@ -124,12 +132,141 @@ class UptimeTransformerTests(unittest.TestCase):
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{'timestamp': testdata.t1, 'counter_volume': testdata.flavor2},
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]),
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'state': TestMeter([
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{'timestamp': testdata.t0, 'counter_volume': artifice.constants.active},
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{'timestamp': testdata.t0_30, 'counter_volume': artifice.constants.active},
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{'timestamp': testdata.t1, 'counter_volume': artifice.constants.active}
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{'timestamp': testdata.t0, 'counter_volume': constants.active},
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{'timestamp': testdata.t0_30, 'counter_volume': constants.active},
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{'timestamp': testdata.t1, 'counter_volume': constants.active}
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]),
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}
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result = self._run_transform(meters)
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# there should be half an hour of usage in each of m1.tiny and m1.large
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self.assertEqual({'m1.tiny': 1800, 'm1.large': 1800}, result)
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class GaugeMaxTransformerTests(unittest.TestCase):
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def test_wrong_metrics_type(self):
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"""
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Test that the correct exception is thrown if any given meters
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are of the wrong type.
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"""
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xform = artifice.transformers.GaugeMax()
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meter = mock.MagicMock()
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meter.type = "cumulative"
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with self.assertRaises(TransformerValidationError) as e:
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xform.transform_usage({'some_meter': meter})
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self.assertTrue(
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e.exception.message.startswith('Meters must all be of type: '))
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def test_all_different_values(self):
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"""
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Tests that the transformer correctly grabs the highest value,
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when all values are different.
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"""
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meters = {
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'size': TestMeter([
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{'timestamp': testdata.t0, 'counter_volume': 12},
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{'timestamp': testdata.t0_10, 'counter_volume': 3},
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{'timestamp': testdata.t0_20, 'counter_volume': 7},
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{'timestamp': testdata.t0_30, 'counter_volume': 3},
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{'timestamp': testdata.t0_40, 'counter_volume': 25},
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{'timestamp': testdata.t0_50, 'counter_volume': 2},
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{'timestamp': testdata.t1, 'counter_volume': 6},
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], "gauge")
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}
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xform = artifice.transformers.GaugeMax()
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usage = xform.transform_usage(meters)
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self.assertEqual({'size': 25}, usage)
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def test_all_same_values(self):
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"""
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Tests that that transformer correctly grabs any value,
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when all values are the same.
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"""
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meters = {
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'size': TestMeter([
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{'timestamp': testdata.t0, 'counter_volume': 25},
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{'timestamp': testdata.t0_30, 'counter_volume': 25},
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{'timestamp': testdata.t1, 'counter_volume': 25},
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], "gauge")
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}
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xform = artifice.transformers.GaugeMax()
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usage = xform.transform_usage(meters)
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self.assertEqual({'size': 25}, usage)
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class CumulativeRangeTransformerTests(unittest.TestCase):
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def test_no_reset(self):
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"""
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Tests that the correct usage is being returned for the range,
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when no reset occurs.
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"""
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meters = {
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'time': TestMeter([
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{'timestamp': testdata.t0, 'counter_volume': 1},
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{'timestamp': testdata.t0_10, 'counter_volume': 2},
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{'timestamp': testdata.t0_20, 'counter_volume': 3},
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{'timestamp': testdata.t0_30, 'counter_volume': 4},
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{'timestamp': testdata.t0_40, 'counter_volume': 5},
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{'timestamp': testdata.t0_50, 'counter_volume': 6},
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{'timestamp': testdata.t1, 'counter_volume': 7},
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], "cumulative")
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}
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xform = artifice.transformers.CumulativeRange()
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usage = xform.transform_usage(meters)
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self.assertEqual({'time': 6}, usage)
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def test_clear_reset(self):
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"""
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Tests that the correct usage is being returned for the range,
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when a reset occurs.
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"""
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meters = {
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'time': TestMeter([
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{'timestamp': testdata.t0, 'counter_volume': 10},
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{'timestamp': testdata.t0_10, 'counter_volume': 20},
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{'timestamp': testdata.t0_20, 'counter_volume': 40},
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{'timestamp': testdata.t0_30, 'counter_volume': 0},
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{'timestamp': testdata.t0_40, 'counter_volume': 20},
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{'timestamp': testdata.t0_50, 'counter_volume': 30},
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{'timestamp': testdata.t1, 'counter_volume': 40},
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], "cumulative")
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}
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xform = artifice.transformers.CumulativeRange()
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usage = xform.transform_usage(meters)
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self.assertEqual({'time': 70}, usage)
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def test_close_reset(self):
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"""
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Tests that the correct usage is being returned for the range,
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when a very close reset occurs.
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"""
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meters = {
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'time': TestMeter([
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{'timestamp': testdata.t0, 'counter_volume': 10},
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{'timestamp': testdata.t0_10, 'counter_volume': 20},
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{'timestamp': testdata.t0_20, 'counter_volume': 40},
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{'timestamp': testdata.t0_30, 'counter_volume': 39},
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{'timestamp': testdata.t0_40, 'counter_volume': 50},
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{'timestamp': testdata.t0_50, 'counter_volume': 60},
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{'timestamp': testdata.t1, 'counter_volume': 70},
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], "cumulative")
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}
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xform = artifice.transformers.CumulativeRange()
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usage = xform.transform_usage(meters)
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self.assertEqual({'time': 100}, usage)
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