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formal datasource interface implementation

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Changes to the baseclass for datasources so strategies can be made
compatible with every datasource. Baseclass methods clearly describe
expected values and types for both parameters and for method returns.
query_retry has been added as base method since every current
datasource implements it.

Ceilometer is updated to work with the new baseclass. Several methods
which are not part of the baseclass and are not used by any strategies
are removed. The signature of these methods would have to be changed
to fit with the new base class while it would limit strategies to
only work with Ceilometer.

Gnocchi is updated to work with the new baseclass.

Gnocchi and Ceilometer will perform a transformation for the
host_airflow metric as it retrieves 1/10 th of the actual CFM

Monasca is updated to work with the new baseclass.

FakeMetrics for Gnocchi, Monasca and Ceilometer are updated to work
with the new method signatures of the baseclass.

FakeClusterAndMetrics for Ceilometer and Gnocchi are updated to work
with the new method signatures of the baseclass.

The strategies workload_balance, vm_workload_consolidation,
workload_stabilization, basic_consolidation, noisy_neighbour,
outlet_temp_control and uniform_airflow are updated to work with the
new datasource baseclass.

This patch will break compatibility with plugin strategies and
datasources due to the changes in signatures.

Depends-on: I7aa52a9b82f4aa849f2378d4d1c03453e45c0c78
Change-Id: Ie30ca3dbf01062cbb20d3be5d514ec6b5155cd7c
Implements: blueprint formal-datasource-interface
This commit is contained in:
Dantali0n
2019-05-01 10:09:58 +02:00
parent f049815cf4
commit 84cb589aa9
23 changed files with 915 additions and 1253 deletions
Download Patch File Download Diff File Expand all files Collapse all files

127
watcher/tests/datasources/test_ceilometer_helper.py
View File

@@ -54,7 +54,6 @@ class TestCeilometerHelper(base.BaseTestCase):
self.assertEqual(expected, query)
def test_statistic_aggregation(self, mock_ceilometer):
cm = ceilometer_helper.CeilometerHelper()
ceilometer = mock.MagicMock()
statistic = mock.MagicMock()
expected_result = 100
@@ -63,113 +62,73 @@ class TestCeilometerHelper(base.BaseTestCase):
mock_ceilometer.return_value = ceilometer
cm = ceilometer_helper.CeilometerHelper()
val = cm.statistic_aggregation(
resource_id="INSTANCE_ID",
meter_name="cpu_util",
resource=mock.Mock(id="INSTANCE_ID"),
resource_type='instance',
meter_name="instance_cpu_usage",
period="7300",
granularity=None
)
self.assertEqual(expected_result, val)
def test_get_last_sample(self, mock_ceilometer):
ceilometer = mock.MagicMock()
statistic = mock.MagicMock()
expected_result = 100
statistic[-1]._info = {'counter_volume': expected_result}
ceilometer.samples.list.return_value = statistic
mock_ceilometer.return_value = ceilometer
cm = ceilometer_helper.CeilometerHelper()
val = cm.get_last_sample_value(
resource_id="id",
meter_name="compute.node.percent"
)
self.assertEqual(expected_result, val)
def test_get_last_sample_none(self, mock_ceilometer):
ceilometer = mock.MagicMock()
expected = []
ceilometer.samples.list.return_value = expected
mock_ceilometer.return_value = ceilometer
cm = ceilometer_helper.CeilometerHelper()
val = cm.get_last_sample_values(
resource_id="id",
meter_name="compute.node.percent"
)
self.assertEqual(expected, val)
def test_statistic_list(self, mock_ceilometer):
ceilometer = mock.MagicMock()
expected_value = []
ceilometer.statistics.list.return_value = expected_value
mock_ceilometer.return_value = ceilometer
cm = ceilometer_helper.CeilometerHelper()
val = cm.statistic_list(meter_name="cpu_util")
self.assertEqual(expected_value, val)
def test_get_host_cpu_usage(self, mock_ceilometer):
self.helper.get_host_cpu_usage('compute1', 600, 'mean')
self.mock_aggregation.assert_called_once_with(
'compute1', self.helper.METRIC_MAP['host_cpu_usage'], 600, None,
aggregation='mean')
'compute1', 'compute_node', 'host_cpu_usage', 600, 'mean', None)
def test_get_instance_cpu_usage(self, mock_ceilometer):
self.helper.get_instance_cpu_usage('compute1', 600, 'mean')
def test_get_host_ram_usage(self, mock_ceilometer):
self.helper.get_host_ram_usage('compute1', 600, 'mean')
self.mock_aggregation.assert_called_once_with(
'compute1', self.helper.METRIC_MAP['instance_cpu_usage'], 600,
None, aggregation='mean')
'compute1', 'compute_node', 'host_ram_usage', 600, 'mean', None)
def test_get_host_memory_usage(self, mock_ceilometer):
self.helper.get_host_memory_usage('compute1', 600, 'mean')
self.mock_aggregation.assert_called_once_with(
'compute1', self.helper.METRIC_MAP['host_memory_usage'], 600, None,
aggregation='mean')
def test_get_instance_memory_usage(self, mock_ceilometer):
self.helper.get_instance_ram_usage('compute1', 600, 'mean')
self.mock_aggregation.assert_called_once_with(
'compute1', self.helper.METRIC_MAP['instance_ram_usage'], 600,
None, aggregation='mean')
def test_get_instance_l3_cache_usage(self, mock_ceilometer):
self.helper.get_instance_l3_cache_usage('compute1', 600, 'mean')
self.mock_aggregation.assert_called_once_with(
'compute1', self.helper.METRIC_MAP['instance_l3_cache_usage'], 600,
None, aggregation='mean')
def test_get_instance_ram_allocated(self, mock_ceilometer):
self.helper.get_instance_ram_allocated('compute1', 600, 'mean')
self.mock_aggregation.assert_called_once_with(
'compute1', self.helper.METRIC_MAP['instance_ram_allocated'], 600,
None, aggregation='mean')
def test_get_instance_root_disk_allocated(self, mock_ceilometer):
self.helper.get_instance_root_disk_size('compute1', 600, 'mean')
self.mock_aggregation.assert_called_once_with(
'compute1', self.helper.METRIC_MAP['instance_root_disk_size'], 600,
None, aggregation='mean')
def test_get_host_outlet_temperature(self, mock_ceilometer):
def test_get_host_outlet_temp(self, mock_ceilometer):
self.helper.get_host_outlet_temp('compute1', 600, 'mean')
self.mock_aggregation.assert_called_once_with(
'compute1', self.helper.METRIC_MAP['host_outlet_temp'], 600, None,
aggregation='mean')
'compute1', 'compute_node', 'host_outlet_temp', 600, 'mean', None)
def test_get_host_inlet_temperature(self, mock_ceilometer):
def test_get_host_inlet_temp(self, mock_ceilometer):
self.helper.get_host_inlet_temp('compute1', 600, 'mean')
self.mock_aggregation.assert_called_once_with(
'compute1', self.helper.METRIC_MAP['host_inlet_temp'], 600, None,
aggregation='mean')
'compute1', 'compute_node', 'host_inlet_temp', 600, 'mean', None)
def test_get_host_airflow(self, mock_ceilometer):
self.helper.get_host_airflow('compute1', 600, 'mean')
self.mock_aggregation.assert_called_once_with(
'compute1', self.helper.METRIC_MAP['host_airflow'], 600, None,
aggregation='mean')
'compute1', 'compute_node', 'host_airflow', 600, 'mean', None)
def test_get_host_power(self, mock_ceilometer):
self.helper.get_host_power('compute1', 600, 'mean')
self.mock_aggregation.assert_called_once_with(
'compute1', self.helper.METRIC_MAP['host_power'], 600, None,
aggregation='mean')
'compute1', 'compute_node', 'host_power', 600, 'mean', None)
def test_get_instance_cpu_usage(self, mock_ceilometer):
self.helper.get_instance_cpu_usage('compute1', 600, 'mean')
self.mock_aggregation.assert_called_once_with(
'compute1', 'instance', 'instance_cpu_usage', 600, 'mean',
None)
def test_get_instance_ram_usage(self, mock_ceilometer):
self.helper.get_instance_ram_usage('compute1', 600, 'mean')
self.mock_aggregation.assert_called_once_with(
'compute1', 'instance', 'instance_ram_usage', 600, 'mean',
None)
def test_get_instance_ram_allocated(self, mock_ceilometer):
self.helper.get_instance_ram_allocated('compute1', 600, 'mean')
self.mock_aggregation.assert_called_once_with(
'compute1', 'instance', 'instance_ram_allocated', 600, 'mean',
None)
def test_get_instance_l3_cache_usage(self, mock_ceilometer):
self.helper.get_instance_l3_cache_usage('compute1', 600, 'mean')
self.mock_aggregation.assert_called_once_with(
'compute1', 'instance', 'instance_l3_cache_usage', 600, 'mean',
None)
def test_get_instance_root_disk_size(self, mock_ceilometer):
self.helper.get_instance_root_disk_size('compute1', 600, 'mean')
self.mock_aggregation.assert_called_once_with(
'compute1', 'instance', 'instance_root_disk_size', 600, 'mean',
None)
def test_check_availability(self, mock_ceilometer):
ceilometer = mock.MagicMock()

105
watcher/tests/datasources/test_gnocchi_helper.py
View File

@@ -48,85 +48,74 @@ class TestGnocchiHelper(base.BaseTestCase):
helper = gnocchi_helper.GnocchiHelper()
result = helper.statistic_aggregation(
resource_id='16a86790-327a-45f9-bc82-45839f062fdc',
meter_name='cpu_util',
resource=mock.Mock(id='16a86790-327a-45f9-bc82-45839f062fdc'),
resource_type='instance',
meter_name='instance_cpu_usage',
period=300,
granularity=360,
dimensions=None,
aggregation='mean',
group_by='*'
aggregate='mean',
)
self.assertEqual(expected_result, result)
def test_get_host_cpu_usage(self, mock_gnocchi):
self.helper.get_host_cpu_usage('compute1', 600, 'mean',
granularity=300)
self.helper.get_host_cpu_usage('compute1', 600, 'mean', 300)
self.mock_aggregation.assert_called_once_with(
'compute1', self.helper.METRIC_MAP['host_cpu_usage'], 600,
300, aggregation='mean')
'compute1', 'compute_node', 'host_cpu_usage', 600, 'mean',
300)
def test_get_instance_cpu_usage(self, mock_gnocchi):
self.helper.get_instance_cpu_usage('compute1', 600, 'mean',
granularity=300)
def test_get_host_ram_usage(self, mock_gnocchi):
self.helper.get_host_ram_usage('compute1', 600, 'mean', 300)
self.mock_aggregation.assert_called_once_with(
'compute1', self.helper.METRIC_MAP['instance_cpu_usage'], 600,
300, aggregation='mean')
def test_get_host_memory_usage(self, mock_gnocchi):
self.helper.get_host_memory_usage('compute1', 600, 'mean',
granularity=300)
self.mock_aggregation.assert_called_once_with(
'compute1', self.helper.METRIC_MAP['host_memory_usage'], 600,
300, aggregation='mean')
def test_get_instance_memory_usage(self, mock_gnocchi):
self.helper.get_instance_ram_usage('compute1', 600, 'mean',
granularity=300)
self.mock_aggregation.assert_called_once_with(
'compute1', self.helper.METRIC_MAP['instance_ram_usage'], 600,
300, aggregation='mean')
def test_get_instance_ram_allocated(self, mock_gnocchi):
self.helper.get_instance_ram_allocated('compute1', 600, 'mean',
granularity=300)
self.mock_aggregation.assert_called_once_with(
'compute1', self.helper.METRIC_MAP['instance_ram_allocated'], 600,
300, aggregation='mean')
def test_get_instance_root_disk_allocated(self, mock_gnocchi):
self.helper.get_instance_root_disk_size('compute1', 600, 'mean',
granularity=300)
self.mock_aggregation.assert_called_once_with(
'compute1', self.helper.METRIC_MAP['instance_root_disk_size'], 600,
300, aggregation='mean')
'compute1', 'compute_node', 'host_ram_usage', 600, 'mean',
300)
def test_get_host_outlet_temperature(self, mock_gnocchi):
self.helper.get_host_outlet_temp('compute1', 600, 'mean',
granularity=300)
self.helper.get_host_outlet_temp('compute1', 600, 'mean', 300)
self.mock_aggregation.assert_called_once_with(
'compute1', self.helper.METRIC_MAP['host_outlet_temp'], 600,
300, aggregation='mean')
'compute1', 'compute_node', 'host_outlet_temp', 600, 'mean',
300)
def test_get_host_inlet_temperature(self, mock_gnocchi):
self.helper.get_host_inlet_temp('compute1', 600, 'mean',
granularity=300)
self.helper.get_host_inlet_temp('compute1', 600, 'mean', 300)
self.mock_aggregation.assert_called_once_with(
'compute1', self.helper.METRIC_MAP['host_inlet_temp'], 600,
300, aggregation='mean')
'compute1', 'compute_node', 'host_inlet_temp', 600, 'mean',
300)
def test_get_host_airflow(self, mock_gnocchi):
self.helper.get_host_airflow('compute1', 600, 'mean',
granularity=300)
self.helper.get_host_airflow('compute1', 600, 'mean', 300)
self.mock_aggregation.assert_called_once_with(
'compute1', self.helper.METRIC_MAP['host_airflow'], 600,
300, aggregation='mean')
'compute1', 'compute_node', 'host_airflow', 600, 'mean',
300)
def test_get_host_power(self, mock_gnocchi):
self.helper.get_host_power('compute1', 600, 'mean',
granularity=300)
self.helper.get_host_power('compute1', 600, 'mean', 300)
self.mock_aggregation.assert_called_once_with(
'compute1', self.helper.METRIC_MAP['host_power'], 600,
300, aggregation='mean')
'compute1', 'compute_node', 'host_power', 600, 'mean',
300)
def test_get_instance_cpu_usage(self, mock_gnocchi):
self.helper.get_instance_cpu_usage('compute1', 600, 'mean', 300)
self.mock_aggregation.assert_called_once_with(
'compute1', 'instance', 'instance_cpu_usage', 600, 'mean',
300)
def test_get_instance_memory_usage(self, mock_gnocchi):
self.helper.get_instance_ram_usage('compute1', 600, 'mean', 300)
self.mock_aggregation.assert_called_once_with(
'compute1', 'instance', 'instance_ram_usage', 600, 'mean',
300)
def test_get_instance_ram_allocated(self, mock_gnocchi):
self.helper.get_instance_ram_allocated('compute1', 600, 'mean', 300)
self.mock_aggregation.assert_called_once_with(
'compute1', 'instance', 'instance_ram_allocated', 600, 'mean',
300)
def test_get_instance_root_disk_allocated(self, mock_gnocchi):
self.helper.get_instance_root_disk_size('compute1', 600, 'mean', 300)
self.mock_aggregation.assert_called_once_with(
'compute1', 'instance', 'instance_root_disk_size', 600, 'mean',
300)
def test_gnocchi_check_availability(self, mock_gnocchi):
gnocchi = mock.MagicMock()

56
watcher/tests/datasources/test_monasca_helper.py
View File

@@ -56,13 +56,12 @@ class TestMonascaHelper(base.BaseTestCase):
helper = monasca_helper.MonascaHelper()
result = helper.statistic_aggregation(
resource_id=None,
meter_name='cpu.percent',
resource=mock.Mock(id='NODE_UUID'),
resource_type='compute_node',
meter_name='host_cpu_usage',
period=7200,
granularity=300,
dimensions={'hostname': 'NODE_UUID'},
aggregation='avg',
group_by='*',
aggregate='mean',
)
self.assertEqual(0.6, result)
@@ -81,55 +80,14 @@ class TestMonascaHelper(base.BaseTestCase):
helper = monasca_helper.MonascaHelper()
self.assertEqual('not available', helper.check_availability())
def test_monasca_statistic_list(self, mock_monasca):
monasca = mock.MagicMock()
expected_result = [{
'columns': ['timestamp', 'value', 'value_meta'],
'dimensions': {
'hostname': 'rdev-indeedsrv001',
'service': 'monasca'},
'id': '0',
'measurements': [
['2016-07-29T12:54:06.000Z', 0.9, {}],
['2016-07-29T12:54:36.000Z', 0.9, {}],
['2016-07-29T12:55:06.000Z', 0.9, {}],
['2016-07-29T12:55:36.000Z', 0.8, {}]],
'name': 'cpu.percent'}]
monasca.metrics.list_measurements.return_value = expected_result
mock_monasca.return_value = monasca
helper = monasca_helper.MonascaHelper()
val = helper.statistics_list(meter_name="cpu.percent", dimensions={})
self.assertEqual(expected_result, val)
def test_monasca_statistic_list_query_retry(self, mock_monasca):
monasca = mock.MagicMock()
expected_result = [{
'columns': ['timestamp', 'value', 'value_meta'],
'dimensions': {
'hostname': 'rdev-indeedsrv001',
'service': 'monasca'},
'id': '0',
'measurements': [
['2016-07-29T12:54:06.000Z', 0.9, {}],
['2016-07-29T12:54:36.000Z', 0.9, {}],
['2016-07-29T12:55:06.000Z', 0.9, {}],
['2016-07-29T12:55:36.000Z', 0.8, {}]],
'name': 'cpu.percent'}]
monasca.metrics.list_measurements.side_effect = [expected_result]
mock_monasca.return_value = monasca
helper = monasca_helper.MonascaHelper()
val = helper.statistics_list(meter_name="cpu.percent", dimensions={})
self.assertEqual(expected_result, val)
def test_get_host_cpu_usage(self, mock_monasca):
node = "compute1_compute1"
self.mock_aggregation.return_value = 0.6
node = mock.Mock(id='compute1')
cpu_usage = self.helper.get_host_cpu_usage(node, 600, 'mean')
self.assertEqual(0.6, cpu_usage)
def test_get_instance_cpu_usage(self, mock_monasca):
self.mock_aggregation.return_value = 0.6
cpu_usage = self.helper.get_instance_cpu_usage('vm1', 600, 'mean')
node = mock.Mock(id='vm1')
cpu_usage = self.helper.get_instance_cpu_usage(node, 600, 'mean')
self.assertEqual(0.6, cpu_usage)

205
watcher/tests/decision_engine/model/ceilometer_metrics.py
View File

@@ -28,64 +28,74 @@ class FakeCeilometerMetrics(object):
def empty_one_metric(self, emptytype):
self.emptytype = emptytype
def mock_get_statistics(self, resource_id=None, meter_name=None,
period=None, granularity=None, dimensions=None,
aggregation='avg', group_by='*'):
def mock_get_statistics(self, resource=None, resource_type=None,
meter_name=None, period=None, aggregate='mean',
granularity=None):
result = 0
if meter_name == "hardware.cpu.util":
result = self.get_usage_node_cpu(resource_id)
elif meter_name == "compute.node.cpu.percent":
result = self.get_usage_node_cpu(resource_id)
elif meter_name == "hardware.memory.used":
result = self.get_usage_node_ram(resource_id)
elif meter_name == "cpu_util":
result = self.get_average_usage_instance_cpu(resource_id)
elif meter_name == "memory.resident":
result = self.get_average_usage_instance_memory(resource_id)
elif meter_name == "hardware.ipmi.node.outlet_temperature":
result = self.get_average_outlet_temperature(resource_id)
elif meter_name == "hardware.ipmi.node.airflow":
result = self.get_average_airflow(resource_id)
elif meter_name == "hardware.ipmi.node.temperature":
result = self.get_average_inlet_t(resource_id)
elif meter_name == "hardware.ipmi.node.power":
result = self.get_average_power(resource_id)
if meter_name == 'host_cpu_usage':
result = self.get_usage_compute_node_cpu(resource)
elif meter_name == 'host_ram_usage':
result = self.get_usage_compute_node_ram(resource)
elif meter_name == 'host_outlet_temp':
result = self.get_average_outlet_temp(resource)
elif meter_name == 'host_inlet_temp':
result = self.get_average_inlet_temp(resource)
elif meter_name == 'host_airflow':
result = self.get_average_airflow(resource)
elif meter_name == 'host_power':
result = self.get_average_power(resource)
elif meter_name == 'instance_cpu_usage':
result = self.get_average_usage_instance_cpu(resource)
elif meter_name == 'instance_ram_usage':
result = self.get_average_usage_instance_memory(resource)
return result
def mock_get_statistics_wb(self, resource_id, meter_name, period,
granularity, dimensions=None,
aggregation='avg', group_by='*'):
result = 0.0
if meter_name == "cpu_util":
result = self.get_average_usage_instance_cpu_wb(resource_id)
elif meter_name == "memory.resident":
result = self.get_average_usage_instance_memory_wb(resource_id)
return result
def mock_get_statistics_nn(self, resource=None, meter_name=None,
period=None, aggregate='mean', granularity=300):
"""Statistics for noisy neighbor strategy
Signature should match DataSourceBase.get_instance_l3_cache_usage
"""
def mock_get_statistics_nn(self, resource_id, period,
aggregation, granularity=300):
result = 0.0
if period == 100:
result = self.get_average_l3_cache_current(resource_id)
result = self.get_average_l3_cache_current(resource)
if period == 200:
result = self.get_average_l3_cache_previous(resource_id)
result = self.get_average_l3_cache_previous(resource)
return result
def mock_get_statistics_wb(self, resource=None, resource_type=None,
meter_name=None, period=None, aggregate='mean',
granularity=None):
"""Statistics for workload balance strategy"""
result = 0.0
if meter_name == 'instance_cpu_usage':
result = self.get_average_usage_instance_cpu_wb(resource)
elif meter_name == 'instance_ram_usage':
result = self.get_average_usage_instance_memory_wb(resource)
return result
@staticmethod
def get_average_l3_cache_current(uuid):
def get_average_l3_cache_current(resource):
"""The average l3 cache used by instance"""
uuid = resource.uuid
mock = {}
mock['73b09e16-35b7-4922-804e-e8f5d9b740fc'] = 35 * oslo_utils.units.Ki
mock['cae81432-1631-4d4e-b29c-6f3acdcde906'] = 30 * oslo_utils.units.Ki
mock['INSTANCE_3'] = 40 * oslo_utils.units.Ki
mock['INSTANCE_4'] = 35 * oslo_utils.units.Ki
if uuid not in mock.keys():
mock[uuid] = 25 * oslo_utils.units.Ki
return mock[str(uuid)]
@staticmethod
def get_average_l3_cache_previous(uuid):
def get_average_l3_cache_previous(resource):
"""The average l3 cache used by instance"""
uuid = resource.uuid
mock = {}
mock['73b09e16-35b7-4922-804e-e8f5d9b740fc'] = 34.5 * (
oslo_utils.units.Ki)
@@ -93,13 +103,14 @@ class FakeCeilometerMetrics(object):
oslo_utils.units.Ki)
mock['INSTANCE_3'] = 60 * oslo_utils.units.Ki
mock['INSTANCE_4'] = 22.5 * oslo_utils.units.Ki
if uuid not in mock.keys():
mock[uuid] = 25 * oslo_utils.units.Ki
return mock[str(uuid)]
@staticmethod
def get_average_outlet_temperature(uuid):
def get_average_outlet_temp(resource):
"""The average outlet temperature for host"""
uuid = resource.uuid
mock = {}
mock['Node_0'] = 30
# use a big value to make sure it exceeds threshold
@@ -109,7 +120,9 @@ class FakeCeilometerMetrics(object):
return float(mock[str(uuid)])
@staticmethod
def get_usage_node_ram(uuid):
def get_usage_compute_node_ram(resource):
uuid = resource.uuid
mock = {}
# Ceilometer returns hardware.memory.used samples in KB.
mock['Node_0'] = 7 * oslo_utils.units.Ki
@@ -125,8 +138,10 @@ class FakeCeilometerMetrics(object):
return float(mock[str(uuid)])
@staticmethod
def get_average_airflow(uuid):
def get_average_airflow(resource):
"""The average outlet temperature for host"""
uuid = resource.uuid
mock = {}
mock['Node_0'] = 400
# use a big value to make sure it exceeds threshold
@@ -136,8 +151,10 @@ class FakeCeilometerMetrics(object):
return mock[str(uuid)]
@staticmethod
def get_average_inlet_t(uuid):
def get_average_inlet_temp(resource):
"""The average outlet temperature for host"""
uuid = resource.uuid
mock = {}
mock['Node_0'] = 24
mock['Node_1'] = 26
@@ -146,8 +163,10 @@ class FakeCeilometerMetrics(object):
return mock[str(uuid)]
@staticmethod
def get_average_power(uuid):
def get_average_power(resource):
"""The average outlet temperature for host"""
uuid = resource.uuid
mock = {}
mock['Node_0'] = 260
mock['Node_1'] = 240
@@ -156,64 +175,48 @@ class FakeCeilometerMetrics(object):
return mock[str(uuid)]
@staticmethod
def get_usage_node_cpu(*args, **kwargs):
def get_usage_compute_node_cpu(*args, **kwargs):
"""The last VM CPU usage values to average
:param uuid:00
:return:
"""
uuid = args[0]
# query influxdb stream
# compute in stream
resource = args[0]
uuid = "%s_%s" % (resource.uuid, resource.hostname)
# Normalize
mock = {}
measurements = {}
# node 0
mock['Node_0_hostname_0'] = 7
mock['Node_1_hostname_1'] = 7
measurements['Node_0_hostname_0'] = 7
measurements['Node_1_hostname_1'] = 7
# node 1
mock['Node_2_hostname_2'] = 80
measurements['Node_2_hostname_2'] = 80
# node 2
mock['Node_3_hostname_3'] = 5
mock['Node_4_hostname_4'] = 5
mock['Node_5_hostname_5'] = 10
measurements['Node_3_hostname_3'] = 5
measurements['Node_4_hostname_4'] = 5
measurements['Node_5_hostname_5'] = 10
# node 3
mock['Node_6_hostname_6'] = 8
measurements['Node_6_hostname_6'] = 8
# This node doesn't send metrics
mock['LOST_NODE_hostname_7'] = None
mock['Node_19_hostname_19'] = 10
measurements['LOST_NODE_hostname_7'] = None
measurements['Node_19_hostname_19'] = 10
# node 4
mock['INSTANCE_7_hostname_7'] = 4
measurements['INSTANCE_7_hostname_7'] = 4
mock['Node_0'] = 7
mock['Node_1'] = 5
mock['Node_2'] = 10
mock['Node_3'] = 4
mock['Node_4'] = 2
if uuid not in mock.keys():
# mock[uuid] = random.randint(1, 4)
mock[uuid] = 8
if mock[str(uuid)] is not None:
return float(mock[str(uuid)])
else:
return mock[str(uuid)]
result = measurements[uuid]
return float(result) if result is not None else None
@staticmethod
def get_average_usage_instance_cpu_wb(uuid):
def get_average_usage_instance_cpu_wb(resource):
"""The last VM CPU usage values to average
:param uuid:00
:param resource:
:return:
"""
# query influxdb stream
# compute in stream
uuid = resource.uuid
# Normalize
mock = {}
# node 0
mock['INSTANCE_1'] = 80
@@ -221,19 +224,20 @@ class FakeCeilometerMetrics(object):
# node 1
mock['INSTANCE_3'] = 20
mock['INSTANCE_4'] = 10
return float(mock[str(uuid)])
@staticmethod
def get_average_usage_instance_memory_wb(uuid):
def get_average_usage_instance_memory_wb(resource):
uuid = resource.uuid
mock = {}
# node 0
mock['INSTANCE_1'] = 30
mock['73b09e16-35b7-4922-804e-e8f5d9b740fc'] = 12
# node 1
mock['INSTANCE_3'] = 12
mock['INSTANCE_4'] = 12
if uuid not in mock.keys():
# mock[uuid] = random.randint(1, 4)
mock[uuid] = 12
return mock[str(uuid)]
@@ -244,12 +248,10 @@ class FakeCeilometerMetrics(object):
:param uuid:00
:return:
"""
uuid = args[0]
# query influxdb stream
# compute in stream
resource = args[0]
uuid = resource.uuid
# Normalize
mock = {}
# node 0
mock['INSTANCE_0'] = 7
@@ -260,22 +262,22 @@ class FakeCeilometerMetrics(object):
mock['INSTANCE_3'] = 5
mock['INSTANCE_4'] = 5
mock['INSTANCE_5'] = 10
# node 3
mock['INSTANCE_6'] = 8
# node 4
mock['INSTANCE_7'] = 4
mock['LOST_INSTANCE'] = None
# metrics might be missing in scenarios which do not do computations
if uuid not in mock.keys():
# mock[uuid] = random.randint(1, 4)
mock[uuid] = 8
mock[uuid] = 0
return mock[str(uuid)]
@staticmethod
def get_average_usage_instance_memory(uuid):
def get_average_usage_instance_memory(resource):
uuid = resource.uuid
mock = {}
# node 0
mock['INSTANCE_0'] = 2
@@ -286,20 +288,17 @@ class FakeCeilometerMetrics(object):
mock['INSTANCE_3'] = 8
mock['INSTANCE_4'] = 5
mock['INSTANCE_5'] = 16
# node 3
mock['INSTANCE_6'] = 8
# node 4
mock['INSTANCE_7'] = 4
if uuid not in mock.keys():
# mock[uuid] = random.randint(1, 4)
mock[uuid] = 10
return mock[str(uuid)]
@staticmethod
def get_average_usage_instance_disk(uuid):
def get_average_usage_instance_disk(resource):
uuid = resource.uuid
mock = {}
# node 0
mock['INSTANCE_0'] = 2
@@ -310,15 +309,9 @@ class FakeCeilometerMetrics(object):
mock['INSTANCE_3'] = 10
mock['INSTANCE_4'] = 15
mock['INSTANCE_5'] = 20
# node 3
mock['INSTANCE_6'] = 8
# node 4
mock['INSTANCE_7'] = 4
if uuid not in mock.keys():
# mock[uuid] = random.randint(1, 4)
mock[uuid] = 4
return mock[str(uuid)]

100
watcher/tests/decision_engine/model/faker_cluster_and_metrics.py
View File

@@ -84,23 +84,24 @@ class FakeCeilometerMetrics(object):
def __init__(self, model):
self.model = model
def mock_get_statistics(self, resource_id=None, meter_name=None,
period=300, granularity=300, dimensions=None,
aggregation='avg', group_by='*'):
if meter_name == "compute.node.cpu.percent":
return self.get_node_cpu_util(resource_id, period,
aggregation, granularity)
elif meter_name == "cpu_util":
return self.get_instance_cpu_util(resource_id, period,
aggregation, granularity)
elif meter_name == "memory.resident":
return self.get_instance_ram_util(resource_id, period,
aggregation, granularity)
elif meter_name == "disk.root.size":
return self.get_instance_disk_root_size(resource_id, period,
aggregation, granularity)
def mock_get_statistics(self, resource=None, resource_type=None,
meter_name=None, period=300, aggregate='mean',
granularity=300):
if meter_name == 'host_cpu_usage':
return self.get_compute_node_cpu_util(
resource, period, aggregate, granularity)
elif meter_name == 'instance_cpu_usage':
return self.get_instance_cpu_util(
resource, period, aggregate, granularity)
elif meter_name == 'instance_ram_usage':
return self.get_instance_ram_util(
resource, period, aggregate, granularity)
elif meter_name == 'instance_root_disk_size':
return self.get_instance_disk_root_size(
resource, period, aggregate, granularity)
def get_node_cpu_util(self, r_id, period, aggregation, granularity):
def get_compute_node_cpu_util(self, resource, period,
aggregate, granularity):
"""Calculates node utilization dynamicaly.
node CPU utilization should consider
@@ -109,7 +110,7 @@ class FakeCeilometerMetrics(object):
Returns relative node CPU utilization <0, 100>.
:param r_id: resource id
"""
node_uuid = '%s_%s' % (r_id.split('_')[0], r_id.split('_')[1])
node_uuid = '%s_%s' % (resource.uuid, resource.hostname)
node = self.model.get_node_by_uuid(node_uuid)
instances = self.model.get_node_instances(node)
util_sum = 0.0
@@ -122,7 +123,8 @@ class FakeCeilometerMetrics(object):
return util_sum * 100.0
@staticmethod
def get_instance_cpu_util(r_id, period, aggregation, granularity):
def get_instance_cpu_util(resource, period, aggregate,
granularity):
instance_cpu_util = dict()
instance_cpu_util['INSTANCE_0'] = 10
instance_cpu_util['INSTANCE_1'] = 30
@@ -134,10 +136,11 @@ class FakeCeilometerMetrics(object):
instance_cpu_util['INSTANCE_7'] = 100
instance_cpu_util['INSTANCE_8'] = 100
instance_cpu_util['INSTANCE_9'] = 100
return instance_cpu_util[str(r_id)]
return instance_cpu_util[str(resource.uuid)]
@staticmethod
def get_instance_ram_util(r_id, period, aggregation, granularity):
def get_instance_ram_util(resource, period, aggregate,
granularity):
instance_ram_util = dict()
instance_ram_util['INSTANCE_0'] = 1
instance_ram_util['INSTANCE_1'] = 2
@@ -149,10 +152,11 @@ class FakeCeilometerMetrics(object):
instance_ram_util['INSTANCE_7'] = 2
instance_ram_util['INSTANCE_8'] = 4
instance_ram_util['INSTANCE_9'] = 8
return instance_ram_util[str(r_id)]
return instance_ram_util[str(resource.uuid)]
@staticmethod
def get_instance_disk_root_size(r_id, period, aggregation, granularity):
def get_instance_disk_root_size(resource, period, aggregate,
granularity):
instance_disk_util = dict()
instance_disk_util['INSTANCE_0'] = 10
instance_disk_util['INSTANCE_1'] = 15
@@ -164,30 +168,31 @@ class FakeCeilometerMetrics(object):
instance_disk_util['INSTANCE_7'] = 25
instance_disk_util['INSTANCE_8'] = 25
instance_disk_util['INSTANCE_9'] = 25
return instance_disk_util[str(r_id)]
return instance_disk_util[str(resource.uuid)]
class FakeGnocchiMetrics(object):
def __init__(self, model):
self.model = model
def mock_get_statistics(self, resource_id=None, meter_name=None,
period=300, granularity=300, dimensions=None,
aggregation='avg', group_by='*'):
if meter_name == "compute.node.cpu.percent":
return self.get_node_cpu_util(resource_id, period,
aggregation, granularity)
elif meter_name == "cpu_util":
return self.get_instance_cpu_util(resource_id, period,
aggregation, granularity)
elif meter_name == "memory.resident":
return self.get_instance_ram_util(resource_id, period,
aggregation, granularity)
elif meter_name == "disk.root.size":
return self.get_instance_disk_root_size(resource_id, period,
aggregation, granularity)
def mock_get_statistics(self, resource=None, resource_type=None,
meter_name=None, period=300, aggregate='mean',
granularity=300):
if meter_name == 'host_cpu_usage':
return self.get_compute_node_cpu_util(
resource, period, aggregate, granularity)
elif meter_name == 'instance_cpu_usage':
return self.get_instance_cpu_util(
resource, period, aggregate, granularity)
elif meter_name == 'instance_ram_usage':
return self.get_instance_ram_util(
resource, period, aggregate, granularity)
elif meter_name == 'instance_root_disk_size':
return self.get_instance_disk_root_size(
resource, period, aggregate, granularity)
def get_node_cpu_util(self, r_id, period, aggregation, granularity):
def get_compute_node_cpu_util(self, resource, period, aggregate,
granularity):
"""Calculates node utilization dynamicaly.
node CPU utilization should consider
@@ -197,7 +202,7 @@ class FakeGnocchiMetrics(object):
:param r_id: resource id
"""
node_uuid = '%s_%s' % (r_id.split('_')[0], r_id.split('_')[1])
node_uuid = "%s_%s" % (resource.uuid, resource.hostname)
node = self.model.get_node_by_uuid(node_uuid)
instances = self.model.get_node_instances(node)
util_sum = 0.0
@@ -210,7 +215,8 @@ class FakeGnocchiMetrics(object):
return util_sum * 100.0
@staticmethod
def get_instance_cpu_util(r_id, period, aggregation, granularity):
def get_instance_cpu_util(resource, period, aggregate,
granularity):
instance_cpu_util = dict()
instance_cpu_util['INSTANCE_0'] = 10
instance_cpu_util['INSTANCE_1'] = 30
@@ -222,10 +228,11 @@ class FakeGnocchiMetrics(object):
instance_cpu_util['INSTANCE_7'] = 100
instance_cpu_util['INSTANCE_8'] = 100
instance_cpu_util['INSTANCE_9'] = 100
return instance_cpu_util[str(r_id)]
return instance_cpu_util[str(resource.uuid)]
@staticmethod
def get_instance_ram_util(r_id, period, aggregation, granularity):
def get_instance_ram_util(resource, period, aggregate,
granularity):
instance_ram_util = dict()
instance_ram_util['INSTANCE_0'] = 1
instance_ram_util['INSTANCE_1'] = 2
@@ -237,10 +244,11 @@ class FakeGnocchiMetrics(object):
instance_ram_util['INSTANCE_7'] = 2
instance_ram_util['INSTANCE_8'] = 4
instance_ram_util['INSTANCE_9'] = 8
return instance_ram_util[str(r_id)]
return instance_ram_util[str(resource.uuid)]
@staticmethod
def get_instance_disk_root_size(r_id, period, aggregation, granularity):
def get_instance_disk_root_size(resource, period, aggregate,
granularity):
instance_disk_util = dict()
instance_disk_util['INSTANCE_0'] = 10
instance_disk_util['INSTANCE_1'] = 15
@@ -252,4 +260,4 @@ class FakeGnocchiMetrics(object):
instance_disk_util['INSTANCE_7'] = 25
instance_disk_util['INSTANCE_8'] = 25
instance_disk_util['INSTANCE_9'] = 25
return instance_disk_util[str(r_id)]
return instance_disk_util[str(resource.uuid)]

224
watcher/tests/decision_engine/model/gnocchi_metrics.py
View File

@@ -23,54 +23,74 @@ class FakeGnocchiMetrics(object):
def empty_one_metric(self, emptytype):
self.emptytype = emptytype
def mock_get_statistics(self, resource_id=None, meter_name=None,
period=None, granularity=None, dimensions=None,
aggregation='avg', group_by='*'):
def mock_get_statistics(self, resource=None, resource_type=None,
meter_name=None, period=None, aggregate='mean',
granularity=None):
result = 0
if meter_name == "hardware.cpu.util":
result = self.get_usage_node_cpu(resource_id)
elif meter_name == "compute.node.cpu.percent":
result = self.get_usage_node_cpu(resource_id)
elif meter_name == "hardware.memory.used":
result = self.get_usage_node_ram(resource_id)
elif meter_name == "cpu_util":
result = self.get_average_usage_instance_cpu(resource_id)
elif meter_name == "memory.resident":
result = self.get_average_usage_instance_memory(resource_id)
elif meter_name == "hardware.ipmi.node.outlet_temperature":
result = self.get_average_outlet_temperature(resource_id)
elif meter_name == "hardware.ipmi.node.airflow":
result = self.get_average_airflow(resource_id)
elif meter_name == "hardware.ipmi.node.temperature":
result = self.get_average_inlet_t(resource_id)
elif meter_name == "hardware.ipmi.node.power":
result = self.get_average_power(resource_id)
if meter_name == 'host_cpu_usage':
result = self.get_usage_compute_node_cpu(resource)
elif meter_name == 'host_ram_usage':
result = self.get_usage_compute_node_ram(resource)
elif meter_name == 'host_outlet_temp':
result = self.get_average_outlet_temperature(resource)
elif meter_name == 'host_inlet_temp':
result = self.get_average_inlet_temp(resource)
elif meter_name == 'host_airflow':
result = self.get_average_airflow(resource)
elif meter_name == 'host_power':
result = self.get_average_power(resource)
elif meter_name == 'instance_cpu_usage':
result = self.get_average_usage_instance_cpu(resource)
elif meter_name == 'instance_ram_usage':
result = self.get_average_usage_instance_memory(resource)
return result
def mock_get_statistics_nn(self, resource_id, period,
aggregation, granularity=300):
def mock_get_statistics_nn(self, resource=None, meter_name=None,
period=None, aggregate='mean', granularity=300):
"""Statistics for noisy neighbor strategy
Signature should match DataSourceBase.get_instance_l3_cache_usage
"""
result = 0.0
if period == 100:
result = self.get_average_l3_cache_current(resource_id)
result = self.get_average_l3_cache_current(resource)
if period == 200:
result = self.get_average_l3_cache_previous(resource_id)
result = self.get_average_l3_cache_previous(resource)
return result
def mock_get_statistics_wb(self, resource=None, resource_type=None,
meter_name=None, period=None, aggregate='mean',
granularity=300):
"""Statistics for workload balance strategy"""
result = 0.0
if meter_name == 'instance_cpu_usage':
result = self.get_average_usage_instance_cpu_wb(resource)
elif meter_name == 'instance_ram_usage':
result = self.get_average_usage_instance_memory_wb(resource)
return result
@staticmethod
def get_average_l3_cache_current(uuid):
def get_average_l3_cache_current(resource):
"""The average l3 cache used by instance"""
uuid = resource.uuid
mock = {}
mock['73b09e16-35b7-4922-804e-e8f5d9b740fc'] = 35 * oslo_utils.units.Ki
mock['cae81432-1631-4d4e-b29c-6f3acdcde906'] = 30 * oslo_utils.units.Ki
mock['INSTANCE_3'] = 40 * oslo_utils.units.Ki
mock['INSTANCE_4'] = 35 * oslo_utils.units.Ki
if uuid not in mock.keys():
mock[uuid] = 25 * oslo_utils.units.Ki
return mock[str(uuid)]
@staticmethod
def get_average_l3_cache_previous(uuid):
def get_average_l3_cache_previous(resource):
"""The average l3 cache used by instance"""
uuid = resource.uuid
mock = {}
mock['73b09e16-35b7-4922-804e-e8f5d9b740fc'] = 34.5 * (
oslo_utils.units.Ki)
@@ -78,33 +98,26 @@ class FakeGnocchiMetrics(object):
oslo_utils.units.Ki)
mock['INSTANCE_3'] = 60 * oslo_utils.units.Ki
mock['INSTANCE_4'] = 22.5 * oslo_utils.units.Ki
if uuid not in mock.keys():
mock[uuid] = 25 * oslo_utils.units.Ki
return mock[str(uuid)]
def mock_get_statistics_wb(self, resource_id, meter_name, period,
granularity, dimensions=None,
aggregation='avg', group_by='*'):
result = 0.0
if meter_name == "cpu_util":
result = self.get_average_usage_instance_cpu_wb(resource_id)
elif meter_name == "memory.resident":
result = self.get_average_usage_instance_memory_wb(resource_id)
return result
@staticmethod
def get_average_outlet_temperature(uuid):
def get_average_outlet_temperature(resource):
"""The average outlet temperature for host"""
uuid = resource.uuid
mock = {}
mock['Node_0'] = 30
# use a big value to make sure it exceeds threshold
mock['Node_1'] = 100
if uuid not in mock.keys():
mock[uuid] = 100
return mock[str(uuid)]
@staticmethod
def get_usage_node_ram(uuid):
def get_usage_compute_node_ram(resource):
uuid = resource.uuid
mock = {}
# Gnocchi returns hardware.memory.used samples in KB.
mock['Node_0'] = 7 * oslo_utils.units.Ki
@@ -113,83 +126,81 @@ class FakeGnocchiMetrics(object):
mock['Node_3'] = 8 * oslo_utils.units.Ki
mock['Node_4'] = 4 * oslo_utils.units.Ki
if uuid not in mock.keys():
mock[uuid] = 8
return float(mock[str(uuid)])
@staticmethod
def get_average_airflow(uuid):
def get_average_airflow(resource):
"""The average outlet temperature for host"""
uuid = resource.uuid
mock = {}
mock['Node_0'] = 400
# use a big value to make sure it exceeds threshold
mock['Node_1'] = 100
if uuid not in mock.keys():
mock[uuid] = 200
return mock[str(uuid)]
@staticmethod
def get_average_inlet_t(uuid):
def get_average_inlet_temp(resource):
"""The average outlet temperature for host"""
uuid = resource.uuid
mock = {}
mock['Node_0'] = 24
mock['Node_1'] = 26
if uuid not in mock.keys():
mock[uuid] = 28
return mock[str(uuid)]
@staticmethod
def get_average_power(uuid):
def get_average_power(resource):
"""The average outlet temperature for host"""
uuid = resource.uuid
mock = {}
mock['Node_0'] = 260
mock['Node_1'] = 240
if uuid not in mock.keys():
mock[uuid] = 200
return mock[str(uuid)]
@staticmethod
def get_usage_node_cpu(*args, **kwargs):
def get_usage_compute_node_cpu(*args, **kwargs):
"""The last VM CPU usage values to average
:param uuid: instance UUID
:return: float value
"""
uuid = args[0]
resource = args[0]
uuid = "%s_%s" % (resource.uuid, resource.hostname)
# Normalize
mock = {}
measurements = {}
# node 0
mock['Node_0_hostname_0'] = 7
mock['Node_1_hostname_1'] = 7
measurements['Node_0_hostname_0'] = 7
measurements['Node_1_hostname_1'] = 7
# node 1
mock['Node_2_hostname_2'] = 80
measurements['Node_2_hostname_2'] = 80
# node 2
mock['Node_3_hostname_3'] = 5
mock['Node_4_hostname_4'] = 5
mock['Node_5_hostname_5'] = 10
measurements['Node_3_hostname_3'] = 5
measurements['Node_4_hostname_4'] = 5
measurements['Node_5_hostname_5'] = 10
# node 3
mock['Node_6_hostname_6'] = 8
measurements['Node_6_hostname_6'] = 8
# This node doesn't send metrics
mock['LOST_NODE_hostname_7'] = None
mock['Node_19_hostname_19'] = 10
measurements['LOST_NODE_hostname_7'] = None
measurements['Node_19_hostname_19'] = 10
# node 4
mock['INSTANCE_7_hostname_7'] = 4
measurements['INSTANCE_7_hostname_7'] = 4
mock['Node_0'] = 7
mock['Node_1'] = 5
mock['Node_2'] = 10
mock['Node_3'] = 4
mock['Node_4'] = 2
# metrics might be missing in scenarios which do not do computations
if uuid not in measurements.keys():
measurements[uuid] = 0
if uuid not in mock.keys():
mock[uuid] = 8
if mock[str(uuid)] is not None:
return float(mock[str(uuid)])
else:
return mock[str(uuid)]
result = measurements[uuid]
return float(result) if result is not None else None
@staticmethod
def get_average_usage_instance_cpu(*args, **kwargs):
@@ -198,8 +209,10 @@ class FakeGnocchiMetrics(object):
:param uuid: instance UUID
:return: int value
"""
uuid = args[0]
# Normalize
resource = args[0]
uuid = resource.uuid
mock = {}
# node 0
mock['INSTANCE_0'] = 7
@@ -210,22 +223,24 @@ class FakeGnocchiMetrics(object):
mock['INSTANCE_3'] = 5
mock['INSTANCE_4'] = 5
mock['INSTANCE_5'] = 10
# node 3
mock['INSTANCE_6'] = 8
# node 4
mock['INSTANCE_7'] = 4
mock['LOST_INSTANCE'] = None
# metrics might be missing in scenarios which do not do computations
if uuid not in mock.keys():
mock[uuid] = 8
mock[uuid] = 0
return mock[str(uuid)]
@staticmethod
def get_average_usage_instance_memory(uuid):
def get_average_usage_instance_memory(resource):
uuid = resource.uuid
mock = {}
# node 0
mock['INSTANCE_0'] = 2
mock['INSTANCE_1'] = 5
@@ -235,20 +250,18 @@ class FakeGnocchiMetrics(object):
mock['INSTANCE_3'] = 8
mock['INSTANCE_4'] = 5
mock['INSTANCE_5'] = 16
# node 3
mock['INSTANCE_6'] = 8
# node 4
mock['INSTANCE_7'] = 4
if uuid not in mock.keys():
mock[uuid] = 10
return mock[str(uuid)]
@staticmethod
def get_average_usage_instance_disk(uuid):
def get_average_usage_instance_disk(resource):
uuid = resource.uuid
mock = {}
# node 0
mock['INSTANCE_0'] = 2
mock['INSTANCE_1'] = 2
@@ -258,49 +271,42 @@ class FakeGnocchiMetrics(object):
mock['INSTANCE_3'] = 10
mock['INSTANCE_4'] = 15
mock['INSTANCE_5'] = 20
# node 3
mock['INSTANCE_6'] = 8
# node 4
mock['INSTANCE_7'] = 4
if uuid not in mock.keys():
mock[uuid] = 4
return mock[str(uuid)]
@staticmethod
def get_average_usage_instance_cpu_wb(uuid):
def get_average_usage_instance_cpu_wb(resource):
"""The last VM CPU usage values to average
:param uuid: instance UUID
:return: float value
"""
# query influxdb stream
# compute in stream
# Normalize
uuid = resource.uuid
mock = {}
# node 0
mock['INSTANCE_1'] = 80
mock['73b09e16-35b7-4922-804e-e8f5d9b740fc'] = 50
# node 1
mock['INSTANCE_3'] = 20
mock['INSTANCE_4'] = 10
return float(mock[str(uuid)])
@staticmethod
def get_average_usage_instance_memory_wb(uuid):
def get_average_usage_instance_memory_wb(resource):
uuid = resource.uuid
mock = {}
# node 0
mock['INSTANCE_1'] = 30
mock['73b09e16-35b7-4922-804e-e8f5d9b740fc'] = 12
# node 1
mock['INSTANCE_3'] = 12
mock['INSTANCE_4'] = 12
if uuid not in mock.keys():
# mock[uuid] = random.randint(1, 4)
mock[uuid] = 12
return mock[str(uuid)]

202
watcher/tests/decision_engine/model/monasca_metrics.py
View File

@@ -16,8 +16,6 @@
# See the License for the specific language governing permissions and
# limitations under the License.
import oslo_utils
class FakeMonascaMetrics(object):
def __init__(self):
@@ -26,117 +24,37 @@ class FakeMonascaMetrics(object):
def empty_one_metric(self, emptytype):
self.emptytype = emptytype
def mock_get_statistics(self, resource_id=None, meter_name=None,
period=None, granularity=None, dimensions=None,
aggregation='avg', group_by='*'):
resource_id = dimensions.get(
"resource_id") or dimensions.get("hostname")
def mock_get_statistics(self, resource=None, resource_type=None,
meter_name=None, period=None, aggregate='mean',
granularity=None):
result = 0.0
if meter_name == "cpu.percent":
result = self.get_usage_node_cpu(resource_id)
elif meter_name == "vm.cpu.utilization_perc":
result = self.get_average_usage_instance_cpu(resource_id)
# elif meter_name == "hardware.memory.used":
# result = self.get_usage_node_ram(resource_id)
# elif meter_name == "memory.resident":
# result = self.get_average_usage_instance_memory(resource_id)
# elif meter_name == "hardware.ipmi.node.outlet_temperature":
# result = self.get_average_outlet_temperature(resource_id)
# elif meter_name == "hardware.ipmi.node.airflow":
# result = self.get_average_airflow(resource_id)
# elif meter_name == "hardware.ipmi.node.temperature":
# result = self.get_average_inlet_t(resource_id)
# elif meter_name == "hardware.ipmi.node.power":
# result = self.get_average_power(resource_id)
if meter_name == 'host_cpu_usage':
result = self.get_usage_compute_node_cpu(resource)
elif meter_name == 'instance_cpu_usage':
result = self.get_average_usage_instance_cpu(resource)
return result
def mock_get_statistics_wb(self, meter_name, dimensions, period,
aggregate='avg'):
resource_id = dimensions.get(
"resource_id") or dimensions.get("hostname")
def mock_get_statistics_wb(self, resource=None, resource_type=None,
meter_name=None, period=None, aggregate='mean',
granularity=None):
"""Statistics for workload balance strategy"""
result = 0.0
if meter_name == "vm.cpu.utilization_perc":
result = self.get_average_usage_instance_cpu_wb(resource_id)
if meter_name == 'instance_cpu_usage':
result = self.get_average_usage_instance_cpu_wb(resource)
return result
@staticmethod
def get_average_outlet_temperature(uuid):
"""The average outlet temperature for host"""
measurements = {}
measurements['Node_0'] = 30
# use a big value to make sure it exceeds threshold
measurements['Node_1'] = 100
if uuid not in measurements.keys():
measurements[uuid] = 100
return [{'columns': ['avg'],
'statistics': [[float(measurements[str(uuid)])]]}]
@staticmethod
def get_usage_node_ram(uuid):
measurements = {}
# Monasca returns hardware.memory.used samples in KB.
measurements['Node_0'] = 7 * oslo_utils.units.Ki
measurements['Node_1'] = 5 * oslo_utils.units.Ki
measurements['Node_2'] = 29 * oslo_utils.units.Ki
measurements['Node_3'] = 8 * oslo_utils.units.Ki
measurements['Node_4'] = 4 * oslo_utils.units.Ki
if uuid not in measurements.keys():
# measurements[uuid] = random.randint(1, 4)
measurements[uuid] = 8
return float(measurements[str(uuid)])
@staticmethod
def get_average_airflow(uuid):
"""The average outlet temperature for host"""
measurements = {}
measurements['Node_0'] = 400
# use a big value to make sure it exceeds threshold
measurements['Node_1'] = 100
if uuid not in measurements.keys():
measurements[uuid] = 200
return [{'columns': ['avg'],
'statistics': [[float(measurements[str(uuid)])]]}]
@staticmethod
def get_average_inlet_t(uuid):
"""The average outlet temperature for host"""
measurements = {}
measurements['Node_0'] = 24
measurements['Node_1'] = 26
if uuid not in measurements.keys():
measurements[uuid] = 28
return [{'columns': ['avg'],
'statistics': [[float(measurements[str(uuid)])]]}]
@staticmethod
def get_average_power(uuid):
"""The average outlet temperature for host"""
measurements = {}
measurements['Node_0'] = 260
measurements['Node_1'] = 240
if uuid not in measurements.keys():
measurements[uuid] = 200
return [{'columns': ['avg'],
'statistics': [[float(measurements[str(uuid)])]]}]
@staticmethod
def get_usage_node_cpu(*args, **kwargs):
uuid = args[0]
if type(uuid) is dict:
uuid = uuid.get("resource_id") or uuid.get("hostname")
uuid = uuid.rsplit('_', 2)[0]
def get_usage_compute_node_cpu(*args, **kwargs):
"""The last VM CPU usage values to average
:param uuid:00
:return:
"""
# query influxdb stream
# compute in stream
resource = args[0]
uuid = resource.uuid
# Normalize
measurements = {}
# node 0
measurements['Node_0'] = 7
@@ -147,7 +65,6 @@ class FakeMonascaMetrics(object):
measurements['Node_3'] = 5
measurements['Node_4'] = 5
measurements['Node_5'] = 10
# node 3
measurements['Node_6'] = 8
measurements['Node_19'] = 10
@@ -168,45 +85,18 @@ class FakeMonascaMetrics(object):
value = float(sum(values)) / len(values)
cpu_usage = value
return cpu_usage
# return float(measurements[str(uuid)])
@staticmethod
def get_average_usage_instance_cpu_wb(uuid):
"""The last VM CPU usage values to average
:param uuid:00
:return:
"""
# query influxdb stream
# compute in stream
# Normalize
measurements = {}
# node 0
measurements['INSTANCE_1'] = 80
measurements['73b09e16-35b7-4922-804e-e8f5d9b740fc'] = 50
# node 1
measurements['INSTANCE_3'] = 20
measurements['INSTANCE_4'] = 10
return [{'columns': ['avg'],
'statistics': [[float(measurements[str(uuid)])]]}]
@staticmethod
def get_average_usage_instance_cpu(*args, **kwargs):
uuid = args[0]
if type(uuid) is dict:
uuid = uuid.get("resource_id") or uuid.get("hostname")
"""The last VM CPU usage values to average
:param uuid:00
:return:
"""
# query influxdb stream
# compute in stream
resource = args[0]
uuid = resource.uuid
# Normalize
measurements = {}
# node 0
measurements['INSTANCE_0'] = 7
@@ -217,12 +107,11 @@ class FakeMonascaMetrics(object):
measurements['INSTANCE_3'] = 5
measurements['INSTANCE_4'] = 5
measurements['INSTANCE_5'] = 10
# node 3
measurements['INSTANCE_6'] = 8
# node 4
measurements['INSTANCE_7'] = 4
if uuid not in measurements.keys():
# measurements[uuid] = random.randint(1, 4)
measurements[uuid] = 8
@@ -237,54 +126,3 @@ class FakeMonascaMetrics(object):
value = float(sum(values)) / len(values)
cpu_usage = value
return cpu_usage
@staticmethod
def get_average_usage_instance_memory(uuid):
measurements = {}
# node 0
measurements['INSTANCE_0'] = 2
measurements['INSTANCE_1'] = 5
# node 1
measurements['INSTANCE_2'] = 5
# node 2
measurements['INSTANCE_3'] = 8
measurements['INSTANCE_4'] = 5
measurements['INSTANCE_5'] = 16
# node 3
measurements['INSTANCE_6'] = 8
# node 4
measurements['INSTANCE_7'] = 4
if uuid not in measurements.keys():
# measurements[uuid] = random.randint(1, 4)
measurements[uuid] = 10
return [{'columns': ['avg'],
'statistics': [[float(measurements[str(uuid)])]]}]
@staticmethod
def get_average_usage_instance_disk(uuid):
measurements = {}
# node 0
measurements['INSTANCE_0'] = 2
measurements['INSTANCE_1'] = 2
# node 1
measurements['INSTANCE_2'] = 2
# node 2
measurements['INSTANCE_3'] = 10
measurements['INSTANCE_4'] = 15
measurements['INSTANCE_5'] = 20
# node 3
measurements['INSTANCE_6'] = 8
# node 4
measurements['INSTANCE_7'] = 4
if uuid not in measurements.keys():
# measurements[uuid] = random.randint(1, 4)
measurements[uuid] = 4
return [{'columns': ['avg'],
'statistics': [[float(measurements[str(uuid)])]]}]

71
watcher/tests/decision_engine/strategy/strategies/test_basic_consolidation.py
View File

@@ -62,7 +62,7 @@ class TestBasicConsolidation(TestBaseStrategy):
self.addCleanup(p_datasource.stop)
self.m_datasource.return_value = mock.Mock(
get_host_cpu_usage=self.fake_metrics.get_usage_node_cpu,
get_host_cpu_usage=self.fake_metrics.get_usage_compute_node_cpu,
get_instance_cpu_usage=self.fake_metrics.
get_average_usage_instance_cpu
)
@@ -75,7 +75,7 @@ class TestBasicConsolidation(TestBaseStrategy):
size_cluster_assert = 5
self.assertEqual(size_cluster_assert, size_cluster)
def test_basic_consolidation_score_node(self):
def test_basic_consolidation_score_comute_node(self):
model = self.fake_c_cluster.generate_scenario_1()
self.m_c_model.return_value = model
node_1_score = 0.023333333333333317
@@ -96,7 +96,6 @@ class TestBasicConsolidation(TestBaseStrategy):
self.assertEqual(
instance_0_score,
self.strategy.calculate_score_instance(instance_0))
instance_1 = model.get_instance_by_uuid("INSTANCE_1")
instance_1_score = 0.023333333333333317
self.assertEqual(
@@ -236,69 +235,3 @@ class TestBasicConsolidation(TestBaseStrategy):
loaded_action = loader.load(action['action_type'])
loaded_action.input_parameters = action['input_parameters']
loaded_action.validate_parameters()
"""def test_periods(self):
model = self.fake_c_cluster.generate_scenario_1()
self.m_c_model.return_value = model
node_1 = model.get_node_by_uuid("Node_1")
p_ceilometer = mock.patch.object(
strategies.BasicConsolidation, "ceilometer")
m_ceilometer = p_ceilometer.start()
self.addCleanup(p_ceilometer.stop)
p_monasca = mock.patch.object(strategies.BasicConsolidation, "monasca")
m_monasca = p_monasca.start()
self.addCleanup(p_monasca.stop)
p_gnocchi = mock.patch.object(strategies.BasicConsolidation, "gnocchi")
m_gnocchi = p_gnocchi.start()
self.addCleanup(p_gnocchi.stop)
datetime_patcher = mock.patch.object(
datetime, 'datetime',
mock.Mock(wraps=datetime.datetime)
)
mocked_datetime = datetime_patcher.start()
mocked_datetime.utcnow.return_value = datetime.datetime(
2017, 3, 19, 18, 53, 11, 657417)
self.addCleanup(datetime_patcher.stop)
m_monasca.return_value = mock.Mock(
statistic_aggregation=self.fake_metrics.mock_get_statistics)
m_ceilometer.return_value = mock.Mock(
statistic_aggregation=self.fake_metrics.mock_get_statistics)
m_gnocchi.return_value = mock.Mock(
statistic_aggregation=self.fake_metrics.mock_get_statistics)
self.strategy.calculate_score_node(node_1)
resource_id = "%s_%s" % (node_1.uuid, node_1.hostname)
if self.strategy.config.datasource == "ceilometer":
m_ceilometer.statistic_aggregation.assert_called_with(
aggregate='avg', meter_name='compute.node.cpu.percent',
period=7200, resource_id=resource_id)
elif self.strategy.config.datasource == "monasca":
m_monasca.statistic_aggregation.assert_called_with(
aggregate='avg', meter_name='cpu.percent',
period=7200, dimensions={'hostname': 'Node_1'})
elif self.strategy.config.datasource == "gnocchi":
stop_time = datetime.datetime.utcnow()
start_time = stop_time - datetime.timedelta(
seconds=int('7200'))
m_gnocchi.statistic_aggregation.assert_called_with(
resource_id=resource_id, metric='compute.node.cpu.percent',
granularity=300, start_time=start_time, stop_time=stop_time,
aggregation='mean')
self.strategy.input_parameters.update({"period": 600})
self.strategy.calculate_score_node(node_1)
if self.strategy.config.datasource == "ceilometer":
m_ceilometer.statistic_aggregation.assert_called_with(
aggregate='avg', meter_name='compute.node.cpu.percent',
period=600, resource_id=resource_id)
elif self.strategy.config.datasource == "monasca":
m_monasca.statistic_aggregation.assert_called_with(
aggregate='avg', meter_name='cpu.percent',
period=600, dimensions={'hostname': 'Node_1'})
elif self.strategy.config.datasource == "gnocchi":
stop_time = datetime.datetime.utcnow()
start_time = stop_time - datetime.timedelta(
seconds=int('600'))
m_gnocchi.statistic_aggregation.assert_called_with(
resource_id=resource_id, metric='compute.node.cpu.percent',
granularity=300, start_time=start_time, stop_time=stop_time,
aggregation='mean')"""

6
watcher/tests/decision_engine/strategy/strategies/test_outlet_temp_control.py
View File

@@ -73,8 +73,8 @@ class TestOutletTempControl(TestBaseStrategy):
model = self.fake_c_cluster.generate_scenario_3_with_2_nodes()
self.m_c_model.return_value = model
n1, n2 = self.strategy.group_hosts_by_outlet_temp()
self.assertEqual('Node_1', n1[0]['node'].uuid)
self.assertEqual('Node_0', n2[0]['node'].uuid)
self.assertEqual('Node_1', n1[0]['compute_node'].uuid)
self.assertEqual('Node_0', n2[0]['compute_node'].uuid)
def test_choose_instance_to_migrate(self):
model = self.fake_c_cluster.generate_scenario_3_with_2_nodes()
@@ -92,7 +92,7 @@ class TestOutletTempControl(TestBaseStrategy):
instance_to_mig = self.strategy.choose_instance_to_migrate(n1)
dest_hosts = self.strategy.filter_dest_servers(n2, instance_to_mig[1])
self.assertEqual(1, len(dest_hosts))
self.assertEqual('Node_0', dest_hosts[0]['node'].uuid)
self.assertEqual('Node_0', dest_hosts[0]['compute_node'].uuid)
def test_execute_no_workload(self):
model = self.fake_c_cluster.\

16
watcher/tests/decision_engine/strategy/strategies/test_workload_balance.py
View File

@@ -55,13 +55,13 @@ class TestWorkloadBalance(TestBaseStrategy):
self.strategy = strategies.WorkloadBalance(
config=mock.Mock(datasource=self.datasource))
self.strategy.input_parameters = utils.Struct()
self.strategy.input_parameters.update({'metrics': 'cpu_util',
self.strategy.input_parameters.update({'metrics': 'instance_cpu_usage',
'threshold': 25.0,
'period': 300,
'granularity': 300})
self.strategy.threshold = 25.0
self.strategy._period = 300
self.strategy._meter = "cpu_util"
self.strategy._meter = 'instance_cpu_usage'
self.strategy._granularity = 300
def test_calc_used_resource(self):
@@ -78,18 +78,18 @@ class TestWorkloadBalance(TestBaseStrategy):
self.m_c_model.return_value = model
self.strategy.threshold = 30
n1, n2, avg, w_map = self.strategy.group_hosts_by_cpu_or_ram_util()
self.assertEqual(n1[0]['node'].uuid, 'Node_0')
self.assertEqual(n2[0]['node'].uuid, 'Node_1')
self.assertEqual(n1[0]['compute_node'].uuid, 'Node_0')
self.assertEqual(n2[0]['compute_node'].uuid, 'Node_1')
self.assertEqual(avg, 8.0)
def test_group_hosts_by_ram_util(self):
model = self.fake_c_cluster.generate_scenario_6_with_2_nodes()
self.m_c_model.return_value = model
self.strategy._meter = "memory.resident"
self.strategy._meter = 'instance_ram_usage'
self.strategy.threshold = 30
n1, n2, avg, w_map = self.strategy.group_hosts_by_cpu_or_ram_util()
self.assertEqual(n1[0]['node'].uuid, 'Node_0')
self.assertEqual(n2[0]['node'].uuid, 'Node_1')
self.assertEqual(n1[0]['compute_node'].uuid, 'Node_0')
self.assertEqual(n2[0]['compute_node'].uuid, 'Node_1')
self.assertEqual(avg, 33.0)
def test_choose_instance_to_migrate(self):
@@ -123,7 +123,7 @@ class TestWorkloadBalance(TestBaseStrategy):
dest_hosts = self.strategy.filter_destination_hosts(
n2, instance_to_mig[1], avg, w_map)
self.assertEqual(len(dest_hosts), 1)
self.assertEqual(dest_hosts[0]['node'].uuid, 'Node_1')
self.assertEqual(dest_hosts[0]['compute_node'].uuid, 'Node_1')
def test_execute_no_workload(self):
model = self.fake_c_cluster.\

90
watcher/tests/decision_engine/strategy/strategies/test_workload_stabilization.py
View File

@@ -46,11 +46,16 @@ class TestWorkloadStabilization(TestBaseStrategy):
self.fake_metrics = self.fake_datasource_cls()
self.hosts_load_assert = {
'Node_0': {'cpu_util': 0.07, 'memory.resident': 7.0, 'vcpus': 40},
'Node_1': {'cpu_util': 0.07, 'memory.resident': 5, 'vcpus': 40},
'Node_2': {'cpu_util': 0.8, 'memory.resident': 29, 'vcpus': 40},
'Node_3': {'cpu_util': 0.05, 'memory.resident': 8, 'vcpus': 40},
'Node_4': {'cpu_util': 0.05, 'memory.resident': 4, 'vcpus': 40}}
'Node_0': {'instance_cpu_usage': 0.07,
'instance_ram_usage': 7.0, 'vcpus': 40},
'Node_1': {'instance_cpu_usage': 0.07,
'instance_ram_usage': 5, 'vcpus': 40},
'Node_2': {'instance_cpu_usage': 0.8,
'instance_ram_usage': 29, 'vcpus': 40},
'Node_3': {'instance_cpu_usage': 0.05,
'instance_ram_usage': 8, 'vcpus': 40},
'Node_4': {'instance_cpu_usage': 0.05,
'instance_ram_usage': 4, 'vcpus': 40}}
p_osc = mock.patch.object(
clients, "OpenStackClients")
@@ -70,28 +75,32 @@ class TestWorkloadStabilization(TestBaseStrategy):
config=mock.Mock(datasource=self.datasource))
self.strategy.input_parameters = utils.Struct()
self.strategy.input_parameters.update(
{'metrics': ["cpu_util", "memory.resident"],
'thresholds': {"cpu_util": 0.2, "memory.resident": 0.2},
'weights': {"cpu_util_weight": 1.0,
"memory.resident_weight": 1.0},
{'metrics': ["instance_cpu_usage", "instance_ram_usage"],
'thresholds': {"instance_cpu_usage": 0.2,
"instance_ram_usage": 0.2},
'weights': {"instance_cpu_usage_weight": 1.0,
"instance_ram_usage_weight": 1.0},
'instance_metrics':
{"cpu_util": "compute.node.cpu.percent",
"memory.resident": "hardware.memory.used"},
{"instance_cpu_usage": "host_cpu_usage",
"instance_ram_usage": "host_ram_usage"},
'host_choice': 'retry',
'retry_count': 1,
'periods': {"instance": 720, "node": 600},
'aggregation_method': {"instance": "mean", "node": "mean"}})
self.strategy.metrics = ["cpu_util", "memory.resident"]
self.strategy.thresholds = {"cpu_util": 0.2, "memory.resident": 0.2}
self.strategy.weights = {"cpu_util_weight": 1.0,
"memory.resident_weight": 1.0}
'periods': {"instance": 720, "compute_node": 600},
'aggregation_method': {"instance": "mean",
"compute_node": "mean"}})
self.strategy.metrics = ["instance_cpu_usage", "instance_ram_usage"]
self.strategy.thresholds = {"instance_cpu_usage": 0.2,
"instance_ram_usage": 0.2}
self.strategy.weights = {"instance_cpu_usage_weight": 1.0,
"instance_ram_usage_weight": 1.0}
self.strategy.instance_metrics = {
"cpu_util": "compute.node.cpu.percent",
"memory.resident": "hardware.memory.used"}
"instance_cpu_usage": "host_cpu_usage",
"instance_ram_usage": "host_ram_usage"}
self.strategy.host_choice = 'retry'
self.strategy.retry_count = 1
self.strategy.periods = {"instance": 720, "node": 600}
self.strategy.aggregation_method = {"instance": "mean", "node": "mean"}
self.strategy.periods = {"instance": 720, "compute_node": 600}
self.strategy.aggregation_method = {"instance": "mean",
"compute_node": "mean"}
def test_get_instance_load(self):
model = self.fake_c_cluster.generate_scenario_1()
@@ -99,7 +108,7 @@ class TestWorkloadStabilization(TestBaseStrategy):
instance0 = model.get_instance_by_uuid("INSTANCE_0")
instance_0_dict = {
'uuid': 'INSTANCE_0', 'vcpus': 10,
'cpu_util': 0.07, 'memory.resident': 2}
'instance_cpu_usage': 0.07, 'instance_ram_usage': 2}
self.assertEqual(
instance_0_dict, self.strategy.get_instance_load(instance0))
@@ -112,14 +121,16 @@ class TestWorkloadStabilization(TestBaseStrategy):
def test_normalize_hosts_load(self):
self.m_c_model.return_value = self.fake_c_cluster.generate_scenario_1()
fake_hosts = {'Node_0': {'cpu_util': 0.07, 'memory.resident': 7},
'Node_1': {'cpu_util': 0.05, 'memory.resident': 5}}
fake_hosts = {'Node_0': {'instance_cpu_usage': 0.07,
'instance_ram_usage': 7},
'Node_1': {'instance_cpu_usage': 0.05,
'instance_ram_usage': 5}}
normalized_hosts = {'Node_0':
{'cpu_util': 0.07,
'memory.resident': 0.05303030303030303},
{'instance_cpu_usage': 0.07,
'instance_ram_usage': 0.05303030303030303},
'Node_1':
{'cpu_util': 0.05,
'memory.resident': 0.03787878787878788}}
{'instance_cpu_usage': 0.05,
'instance_ram_usage': 0.03787878787878788}}
self.assertEqual(
normalized_hosts,
self.strategy.normalize_hosts_load(fake_hosts))
@@ -147,11 +158,11 @@ class TestWorkloadStabilization(TestBaseStrategy):
test_ram_sd = 9.3
self.assertEqual(
round(self.strategy.get_sd(
self.hosts_load_assert, 'cpu_util'), 3),
self.hosts_load_assert, 'instance_cpu_usage'), 3),
test_cpu_sd)
self.assertEqual(
round(self.strategy.get_sd(
self.hosts_load_assert, 'memory.resident'), 1),
self.hosts_load_assert, 'instance_ram_usage'), 1),
test_ram_sd)
def test_calculate_weighted_sd(self):
@@ -167,8 +178,9 @@ class TestWorkloadStabilization(TestBaseStrategy):
result = self.strategy.calculate_migration_case(
self.hosts_load_assert, instance,
src_node, dst_node)[-1][dst_node.uuid]
result['cpu_util'] = round(result['cpu_util'], 3)
self.assertEqual(result, {'cpu_util': 0.095, 'memory.resident': 21.0,
result['instance_cpu_usage'] = round(result['instance_cpu_usage'], 3)
self.assertEqual(result, {'instance_cpu_usage': 0.095,
'instance_ram_usage': 21.0,
'vcpus': 40})
def test_simulate_migrations(self):
@@ -191,13 +203,15 @@ class TestWorkloadStabilization(TestBaseStrategy):
def test_check_threshold(self):
self.m_c_model.return_value = self.fake_c_cluster.generate_scenario_1()
self.strategy.thresholds = {'cpu_util': 0.001, 'memory.resident': 0.2}
self.strategy.thresholds = {'instance_cpu_usage': 0.001,
'instance_ram_usage': 0.2}
self.strategy.simulate_migrations = mock.Mock(return_value=True)
self.assertTrue(self.strategy.check_threshold())
def test_execute_one_migration(self):
self.m_c_model.return_value = self.fake_c_cluster.generate_scenario_1()
self.strategy.thresholds = {'cpu_util': 0.001, 'memory.resident': 0.2}
self.strategy.thresholds = {'instance_cpu_usage': 0.001,
'instance_ram_usage': 0.2}
self.strategy.simulate_migrations = mock.Mock(
return_value=[
{'instance': 'INSTANCE_4', 's_host': 'Node_2',
@@ -210,8 +224,8 @@ class TestWorkloadStabilization(TestBaseStrategy):
def test_execute_multiply_migrations(self):
self.m_c_model.return_value = self.fake_c_cluster.generate_scenario_1()
self.strategy.thresholds = {'cpu_util': 0.00001,
'memory.resident': 0.0001}
self.strategy.thresholds = {'instance_cpu_usage': 0.00001,
'instance_ram_usage': 0.0001}
self.strategy.simulate_migrations = mock.Mock(
return_value=[
{'instance': 'INSTANCE_4', 's_host': 'Node_2',
@@ -225,8 +239,8 @@ class TestWorkloadStabilization(TestBaseStrategy):
def test_execute_nothing_to_migrate(self):
self.m_c_model.return_value = self.fake_c_cluster.generate_scenario_1()
self.strategy.thresholds = {'cpu_util': 0.042,
'memory.resident': 0.0001}
self.strategy.thresholds = {'instance_cpu_usage': 0.042,
'instance_ram_usage': 0.0001}
self.strategy.simulate_migrations = mock.Mock(return_value=False)
self.strategy.instance_migrations_count = 0
with mock.patch.object(self.strategy, 'migrate') as mock_migrate: