def populate_metrics(self, monitor_list):
metric_object = objects.MonitorMetric()
metric_object.name = 'cpu.frequency'
metric_object.value = 100
metric_object.timestamp = self.NOW_TS
metric_object.source = self.source
monitor_list.objects.append(metric_object)
def test_monitor_metric_list_to_list(self):
obj = objects.MonitorMetric(name='cpu.frequency',
value=1000,
timestamp=_ts_now,
source='nova.virt.libvirt.driver')
list_obj = objects.MonitorMetricList(objects=[obj])
self.assertEqual(_monitor_metric_list_spec, list_obj.to_list())
def test_monitor_metric_perc_to_dict(self):
"""Test to ensure division by 100.0 occurs on percentage value."""
obj = objects.MonitorMetric(name='cpu.percent',
value=17,
timestamp=_ts_now,
source='nova.virt.libvirt.driver')
self.assertEqual(_monitor_metric_perc_spec, obj.to_dict())
def test_metrics_filter_pass(self):
_ts_now = datetime.datetime(2015, 11, 11, 11, 0, 0)
obj1 = objects.MonitorMetric(name='cpu.frequency',
value=1000,
timestamp=_ts_now,
source='nova.virt.libvirt.driver')
obj2 = objects.MonitorMetric(name='numa.membw.current',
numa_membw_values={"0": 10, "1": 43},
timestamp=_ts_now,
source='nova.virt.libvirt.driver')
metrics_list = objects.MonitorMetricList(objects=[obj1, obj2])
self.flags(weight_setting=[
'cpu.frequency=1', 'numa.membw.current=2'], group='metrics')
filt_cls = metrics_filter.MetricsFilter()
host = fakes.FakeHostState('host1', 'node1',
attribute_dict={'metrics': metrics_list})
self.assertTrue(filt_cls.host_passes(host, None))
def populate_metrics(self, metric_list):
self._update_data()
for name in self.get_metric_names():
metric_object = objects.MonitorMetric()
metric_object.name = name
metric_object.value = self._data[name]
metric_object.timestamp = self._data["timestamp"]
metric_object.source = self.source
metric_list.objects.append(metric_object)
def test_monitor_NUMA_metric_to_dict(self):
obj = objects.MonitorMetric(name='numa.membw.current',
numa_membw_values={
"0": 10,
"1": 43
},
timestamp=_ts_now,
source='nova.virt.libvirt.driver')
self.assertEqual(_monitor_numa_metric_spec, obj.to_dict())
def test_obj_make_compatible(self):
monitormetric_obj = objects.MonitorMetric(
name=fields.MonitorMetricType.NUMA_MEM_BW_CURRENT,
numa_membw_values={"0": 10, "1": 43},
timestamp=_ts_now.isoformat(),
source='nova.virt.libvirt.driver')
primitive = monitormetric_obj.obj_to_primitive()
self.assertIn('numa_membw_values', primitive['nova_object.data'])
monitormetric_obj.obj_make_compatible(primitive['nova_object.data'],
'1.0')
self.assertNotIn('numa_membw_values', primitive['nova_object.data'])
def test_metrics_filter_missing_metrics(self):
_ts_now = datetime.datetime(2015, 11, 11, 11, 0, 0)
obj1 = objects.MonitorMetric(name='cpu.frequency',
value=1000,
timestamp=_ts_now,
source='nova.virt.libvirt.driver')
metrics_list = objects.MonitorMetricList(objects=[obj1])
self.flags(weight_setting=['foo=1', 'bar=2'], group='metrics')
filt_cls = metrics_filter.MetricsFilter()
host = fakes.FakeHostState('host1', 'node1',
attribute_dict={'metrics': metrics_list})
self.assertFalse(filt_cls.host_passes(host, None))
def add_metrics_to_list(self, metrics_list):
"""Adds metric objects to a supplied list object.
:param metric_list: nova.objects.MonitorMetricList that the monitor
plugin should append nova.objects.MonitorMetric
objects to.
"""
metric_data = self.get_metrics()
metrics = []
for (name, value, timestamp) in metric_data:
metric = objects.MonitorMetric(name=name,
value=value,
timestamp=timestamp,
source=self.source)
metrics.append(metric)
metrics_list.objects.extend(metrics)
