def test_export_metrics(self):
lv = label_value.LabelValue('val')
val = value.ValueLong(value=123)
dt = datetime(2019, 3, 20, 21, 34, 0, 537954)
pp = point.Point(value=val, timestamp=dt)
ts = [
time_series.TimeSeries(label_values=[lv],
points=[pp],
start_timestamp=utils.to_iso_str(dt))
]
desc = metric_descriptor.MetricDescriptor(
name='name',
description='description',
unit='unit',
type_=metric_descriptor.MetricDescriptorType.GAUGE_INT64,
label_keys=[label_key.LabelKey('key', 'description')])
mm = metric.Metric(descriptor=desc, time_series=ts)
exporter = stackdriver.StackdriverStatsExporter(client=mock.Mock())
exporter.export_metrics([mm])
self.assertEqual(exporter.client.create_time_series.call_count, 1)
sd_args = exporter.client.create_time_series.call_args[0][1]
self.assertEqual(len(sd_args), 1)
[sd_arg] = exporter.client.create_time_series.call_args[0][1]
self.assertEqual(sd_arg.points[0].value.int64_value, 123)
def test_create_batched_time_series(self, monitor_resource_mock):
client = mock.Mock()
v_data = view_data_module.ViewData(view=VIDEO_SIZE_VIEW,
start_time=TEST_TIME_STR,
end_time=TEST_TIME_STR)
v_data.record(context=tag_map_module.TagMap(), value=2, timestamp=None)
view_data = [v_data]
option = stackdriver.Options(project_id="project-test")
exporter = stackdriver.StackdriverStatsExporter(options=option,
client=client)
view_data = [metric_utils.view_data_to_metric(view_data[0], TEST_TIME)]
time_series_batches = exporter.create_batched_time_series(view_data, 1)
self.assertEqual(len(time_series_batches), 1)
[time_series_batch] = time_series_batches
self.assertEqual(len(time_series_batch), 1)
[time_series] = time_series_batch
self.assertEqual(
time_series.metric.type,
'custom.googleapis.com/opencensus/' + VIDEO_SIZE_VIEW_NAME)
self.check_labels(time_series.metric.labels, {},
include_opencensus=True)
def test_handle_upload_no_data(self):
client = mock.Mock()
option = stackdriver.Options(project_id="project-test")
exporter = stackdriver.StackdriverStatsExporter(options=option,
client=client)
exporter.handle_upload(None)
self.assertFalse(client.create_time_series.called)
def test_create_metric_descriptor(self):
client = mock.Mock()
option = stackdriver.Options(project_id="project-test",
metric_prefix="teste")
exporter = stackdriver.StackdriverStatsExporter(options=option,
client=client)
desc = exporter.create_metric_descriptor(VIDEO_SIZE_VIEW)
self.assertIsNotNone(desc)
def test_constructor_param(self):
project_id = 1
default_labels = {'key1': 'value1'}
exporter = stackdriver.StackdriverStatsExporter(
options=stackdriver.Options(
project_id=project_id,
default_monitoring_labels=default_labels))
self.assertEqual(exporter.options.project_id, project_id)
def test_on_register_view(self):
client = mock.Mock()
view_none = None
option = stackdriver.Options(project_id="project-test")
exporter = stackdriver.StackdriverStatsExporter(options=option,
client=client)
exporter.on_register_view(VIDEO_SIZE_VIEW)
exporter.on_register_view(view_none)
self.assertTrue(client.create_metric_descriptor.called)
def test_export_no_data(self):
client = mock.Mock()
transport = mock.Mock()
option = stackdriver.Options(project_id="project-test")
exporter = stackdriver.StackdriverStatsExporter(options=option,
client=client,
transport=transport)
exporter.export(None)
self.assertFalse(exporter.transport.export.called)
def test_create_timeseries_float_tagvalue(self, monitor_resource_mock):
client = mock.Mock()
option = stackdriver.Options(project_id="project-test",
resource="global")
exporter = stackdriver.StackdriverStatsExporter(options=option,
client=client)
stats = stats_module.stats
view_manager = stats.view_manager
stats_recorder = stats.stats_recorder
if len(view_manager.measure_to_view_map.exporters) > 0:
view_manager.unregister_exporter(
view_manager.measure_to_view_map.exporters[0])
view_manager.register_exporter(exporter)
agg_3 = aggregation_module.SumAggregation(sum=2.2)
view_name3 = "view-name3"
new_view3 = view_module.View(view_name3,
"processed video size over time",
[FRONTEND_KEY_FLOAT],
VIDEO_SIZE_MEASURE_FLOAT, agg_3)
view_manager.register_view(new_view3)
tag_value_float = tag_value_module.TagValue("1200")
tag_map = tag_map_module.TagMap()
tag_map.insert(FRONTEND_KEY_FLOAT, tag_value_float)
measure_map = stats_recorder.new_measurement_map()
measure_map.measure_float_put(VIDEO_SIZE_MEASURE_FLOAT, 25 * MiB)
measure_map.record(tag_map)
v_data = measure_map.measure_to_view_map.get_view(view_name3, None)
v_data = metric_utils.view_data_to_metric(v_data, TEST_TIME)
time_series_list = exporter.create_time_series_list(v_data)
self.assertEqual(len(time_series_list), 1)
[time_series] = time_series_list
self.assertEqual(time_series.metric.type,
"custom.googleapis.com/opencensus/view-name3")
self.check_labels(time_series.metric.labels,
{FRONTEND_KEY_FLOAT_CLEAN: "1200"},
include_opencensus=True)
self.assertIsNotNone(time_series.resource)
self.assertEqual(len(time_series.points), 1)
expected_value = monitoring_v3.types.TypedValue()
expected_value.double_value = 2.2 + 25 * MiB
self.assertEqual(time_series.points[0].value, expected_value)
def test_handle_upload_with_data(self, monitor_resource_mock):
client = mock.Mock()
v_data = view_data_module.ViewData(view=VIDEO_SIZE_VIEW,
start_time=TEST_TIME,
end_time=TEST_TIME)
v_data.record(context=tag_map_module.TagMap(), value=2, timestamp=None)
view_data = [v_data]
option = stackdriver.Options(project_id="project-test")
exporter = stackdriver.StackdriverStatsExporter(options=option,
client=client)
exporter.handle_upload(view_data)
self.assertTrue(client.create_time_series.called)
def test_create_batched_time_series_with_many(self, monitor_resource_mock):
client = mock.Mock()
# First view with 3
view_name1 = "view-name1"
view1 = view_module.View(view_name1, "test description", ['test'],
VIDEO_SIZE_MEASURE,
aggregation_module.LastValueAggregation())
v_data1 = view_data_module.ViewData(view=view1,
start_time=TEST_TIME_STR,
end_time=TEST_TIME_STR)
v_data1.record(context=tag_map_module.TagMap({'test': '1'}),
value=7,
timestamp=None)
v_data1.record(context=tag_map_module.TagMap({'test': '2'}),
value=5,
timestamp=None)
v_data1.record(context=tag_map_module.TagMap({'test': '3'}),
value=3,
timestamp=None)
# Second view with 2
view_name2 = "view-name2"
view2 = view_module.View(view_name2, "test description", ['test'],
VIDEO_SIZE_MEASURE,
aggregation_module.LastValueAggregation())
v_data2 = view_data_module.ViewData(view=view2,
start_time=TEST_TIME_STR,
end_time=TEST_TIME_STR)
v_data2.record(context=tag_map_module.TagMap({'test': '1'}),
value=7,
timestamp=None)
v_data2.record(context=tag_map_module.TagMap({'test': '2'}),
value=5,
timestamp=None)
view_data = [v_data1, v_data2]
view_data = [
metric_utils.view_data_to_metric(vd, TEST_TIME) for vd in view_data
]
option = stackdriver.Options(project_id="project-test")
exporter = stackdriver.StackdriverStatsExporter(options=option,
client=client)
time_series_batches = exporter.create_batched_time_series(view_data, 2)
self.assertEqual(len(time_series_batches), 3)
[tsb1, tsb2, tsb3] = time_series_batches
self.assertEqual(len(tsb1), 2)
self.assertEqual(len(tsb2), 2)
self.assertEqual(len(tsb3), 1)
def test_stats_record_sync(self):
# We are using sufix in order to prevent cached objects
sufix = str(os.getgid())
tag_key = "SampleKeySyncTest%s" % sufix
measure_name = "SampleMeasureNameSyncTest%s" % sufix
measure_description = "SampleDescriptionSyncTest%s" % sufix
view_name = "SampleViewNameSyncTest%s" % sufix
view_description = "SampleViewDescriptionSyncTest%s" % sufix
FRONTEND_KEY = tag_key_module.TagKey(tag_key)
VIDEO_SIZE_MEASURE = measure_module.MeasureInt(measure_name,
measure_description,
"By")
VIDEO_SIZE_VIEW_NAME = view_name
VIDEO_SIZE_DISTRIBUTION = aggregation_module.DistributionAggregation(
[0.0, 16.0 * MiB, 256.0 * MiB])
VIDEO_SIZE_VIEW = view_module.View(VIDEO_SIZE_VIEW_NAME,
view_description, [FRONTEND_KEY],
VIDEO_SIZE_MEASURE,
VIDEO_SIZE_DISTRIBUTION)
stats = stats_module.stats
view_manager = stats.view_manager
stats_recorder = stats.stats_recorder
client = monitoring_v3.MetricServiceClient()
exporter = stackdriver.StackdriverStatsExporter(
options=stackdriver.Options(project_id=PROJECT), client=client)
view_manager.register_exporter(exporter)
# Register view.
view_manager.register_view(VIDEO_SIZE_VIEW)
# Sleep for [0, 10] milliseconds to fake work.
time.sleep(random.randint(1, 10) / 1000.0)
# Process video.
# Record the processed video size.
tag_value = tag_value_module.TagValue("1200")
tag_map = tag_map_module.TagMap()
tag_map.insert(FRONTEND_KEY, tag_value)
measure_map = stats_recorder.new_measurement_map()
measure_map.measure_int_put(VIDEO_SIZE_MEASURE, 25 * MiB)
measure_map.record(tag_map)
exporter.export_metrics(stats_module.stats.get_metrics())
# Sleep for [0, 10] milliseconds to fake wait.
time.sleep(random.randint(1, 10) / 1000.0)
self.check_sd_md(exporter, view_description)
def test_create_timeseries_multiple_tags(self):
"""Check that exporter creates timeseries for multiple tag values.
create_time_series_list should return a time series for each set of
values in the tag value aggregation map.
"""
agg = aggregation_module.CountAggregation(
aggregation_type=aggregation_module.Type.COUNT)
view = view_module.View(
name="example.org/test_view",
description="example.org/test_view",
columns=[
tag_key_module.TagKey('color'),
tag_key_module.TagKey('shape')
],
measure=mock.Mock(),
aggregation=agg,
)
v_data = view_data_module.ViewData(
view=view,
start_time=TEST_TIME_STR,
end_time=TEST_TIME_STR,
)
rs_count = aggregation_data_module.CountAggregationData(10)
bc_count = aggregation_data_module.CountAggregationData(20)
v_data._tag_value_aggregation_data_map = {
('red', 'square'): rs_count,
('blue', 'circle'): bc_count,
}
v_data = metric_utils.view_data_to_metric(v_data, TEST_TIME)
exporter = stackdriver.StackdriverStatsExporter()
time_series_list = exporter.create_time_series_list(v_data)
self.assertEqual(len(time_series_list), 2)
self.assertEqual(len(time_series_list[0].points), 1)
self.assertEqual(len(time_series_list[1].points), 1)
ts_by_color = {
ts.metric.labels.get('color'): ts
for ts in time_series_list
}
rs_ts = ts_by_color['red']
bc_ts = ts_by_color['blue']
self.assertEqual(rs_ts.metric.labels.get('shape'), 'square')
self.assertEqual(bc_ts.metric.labels.get('shape'), 'circle')
self.assertEqual(rs_ts.points[0].value.int64_value, 10)
self.assertEqual(bc_ts.points[0].value.int64_value, 20)
def test_export_with_data(self):
client = mock.Mock()
transport = mock.Mock()
v_data = view_data_module.ViewData(view=VIDEO_SIZE_VIEW,
start_time=TEST_TIME,
end_time=TEST_TIME)
view_data = [v_data]
option = stackdriver.Options(project_id="project-test")
exporter = stackdriver.StackdriverStatsExporter(options=option,
client=client,
transport=transport)
exporter.export(view_data)
self.assertTrue(exporter.transport.export.called)
def test_create_metric_descriptor_count(self):
client = mock.Mock()
option = stackdriver.Options(project_id="project-test",
metric_prefix="teste")
view_name_count = "view-count"
agg_count = aggregation_module.CountAggregation(count=2)
view_count = view_module.View(view_name_count,
"processed video size over time",
[FRONTEND_KEY], VIDEO_SIZE_MEASURE,
agg_count)
exporter = stackdriver.StackdriverStatsExporter(options=option,
client=client)
desc = exporter.create_metric_descriptor(view_count)
self.assertIsNotNone(desc)
def test_create_metric_descriptor_sum_float(self):
client = mock.Mock()
option = stackdriver.Options(project_id="project-test",
metric_prefix="teste")
view_name_sum_float = "view-sum-float"
agg_sum = aggregation_module.SumAggregation(sum=2)
view_sum_float = view_module.View(view_name_sum_float,
"processed video size over time",
[FRONTEND_KEY_FLOAT],
VIDEO_SIZE_MEASURE_FLOAT, agg_sum)
exporter = stackdriver.StackdriverStatsExporter(options=option,
client=client)
desc = exporter.create_metric_descriptor(view_sum_float)
self.assertIsNotNone(desc)
def test_create_metric_descriptor_base(self):
client = mock.Mock()
option = stackdriver.Options(project_id="project-test",
metric_prefix="teste")
view_name_base = "view-base"
agg_base = aggregation_module.BaseAggregation()
view_base = view_module.View(view_name_base,
"processed video size over time",
[FRONTEND_KEY], VIDEO_SIZE_MEASURE,
agg_base)
exporter = stackdriver.StackdriverStatsExporter(options=option,
client=client)
self.assertRaises(Exception, exporter.create_metric_descriptor,
view_base)
def test_create_metric_descriptor_last_value_float(self):
client = mock.Mock()
option = stackdriver.Options(project_id="project-test",
metric_prefix="teste")
view_name_base = "view-base"
agg_base = aggregation_module.LastValueAggregation()
view_base = view_module.View(view_name_base,
"processed video size over time",
[FRONTEND_KEY], VIDEO_SIZE_MEASURE_FLOAT,
agg_base)
exporter = stackdriver.StackdriverStatsExporter(options=option,
client=client)
desc = exporter.create_metric_descriptor(view_base)
self.assertIsNotNone(desc)
def test_get_metric_descriptor_bad_type(self):
exporter = stackdriver.StackdriverStatsExporter(
options=stackdriver.Options(project_id='project_id'),
client=mock.Mock())
bad_type_oc_md = metric_descriptor.MetricDescriptor(
name='name',
description='description',
unit='unit',
# Need a valid type to create the descriptor
type_=metric_descriptor.MetricDescriptorType.GAUGE_INT64,
label_keys=[label_key.LabelKey('key', 'description')])
bad_type_oc_md._type = 100
with self.assertRaises(TypeError):
exporter.get_metric_descriptor(bad_type_oc_md)
def test_create_timeseries_from_distribution(self):
"""Check for explicit 0-bound bucket for SD export."""
agg = aggregation_module.DistributionAggregation(
aggregation_type=aggregation_module.Type.DISTRIBUTION)
view = view_module.View(
name="example.org/test_view",
description="example.org/test_view",
columns=['tag_key'],
measure=mock.Mock(),
aggregation=agg,
)
v_data = view_data_module.ViewData(
view=view,
start_time=TEST_TIME_STR,
end_time=TEST_TIME_STR,
)
# Aggregation over (10 * range(10)) for buckets [2, 4, 6, 8]
dad = aggregation_data_module.DistributionAggregationData(
mean_data=4.5,
count_data=100,
sum_of_sqd_deviations=825,
counts_per_bucket=[20, 20, 20, 20, 20],
bounds=[2, 4, 6, 8],
exemplars={mock.Mock()
for ii in range(5)})
v_data._tag_value_aggregation_data_map = {('tag_value', ): dad}
v_data = metric_utils.view_data_to_metric(v_data, TEST_TIME)
exporter = stackdriver.StackdriverStatsExporter()
time_series_list = exporter.create_time_series_list(v_data)
self.assertEqual(len(time_series_list), 1)
[time_series] = time_series_list
self.check_labels(time_series.metric.labels, {'tag_key': 'tag_value'},
include_opencensus=True)
self.assertEqual(len(time_series.points), 1)
[point] = time_series.points
dv = point.value.distribution_value
self.assertEqual(100, dv.count)
self.assertEqual(825.0, dv.sum_of_squared_deviation)
self.assertEqual([0, 20, 20, 20, 20, 20], dv.bucket_counts)
self.assertEqual([0, 2, 4, 6, 8],
dv.bucket_options.explicit_buckets.bounds)
def test_create_timeseries_something(self):
"""Check that exporter creates timeseries for multiple tag values.
create_time_series_list should return a time series for each set of
values in the tag value aggregation map.
"""
v_data = mock.Mock(spec=view_data_module.ViewData)
v_data.view.name = "example.org/test_view"
v_data.view.columns = [
tag_key_module.TagKey('color'),
tag_key_module.TagKey('shape')
]
v_data.view.aggregation.aggregation_type = \
aggregation_module.Type.COUNT
v_data.start_time = TEST_TIME
v_data.end_time = TEST_TIME
rs_count = aggregation_data_module.CountAggregationData(10)
bc_count = aggregation_data_module.CountAggregationData(20)
v_data.tag_value_aggregation_data_map = {
('red', 'square'): rs_count,
('blue', 'circle'): bc_count,
}
exporter = stackdriver.StackdriverStatsExporter(
options=mock.Mock(),
client=mock.Mock(),
)
time_series_list = exporter.create_time_series_list(v_data, "", "")
self.assertEqual(len(time_series_list), 2)
self.assertEqual(len(time_series_list[0].points), 1)
self.assertEqual(len(time_series_list[1].points), 1)
ts_by_color = {
ts.metric.labels.get('color'): ts
for ts in time_series_list
}
rs_ts = ts_by_color['red']
bc_ts = ts_by_color['blue']
self.assertEqual(rs_ts.metric.labels.get('shape'), 'square')
self.assertEqual(bc_ts.metric.labels.get('shape'), 'circle')
self.assertEqual(rs_ts.points[0].value.int64_value, 10)
self.assertEqual(bc_ts.points[0].value.int64_value, 20)
def test_get_metric_descriptor_custom_prefix(self):
exporter = stackdriver.StackdriverStatsExporter(
options=stackdriver.Options(default_monitoring_labels={'dk': 'dd'},
metric_prefix='metric_prefix',
project_id='project_id'),
client=mock.Mock())
oc_md = metric_descriptor.MetricDescriptor(
name='name',
description='description',
unit='unit',
type_=metric_descriptor.MetricDescriptorType.GAUGE_INT64,
label_keys=[label_key.LabelKey('ck', 'cd')])
sd_md = exporter.get_metric_descriptor(oc_md)
self.assertIn('metric_prefix', sd_md.type)
self.assertIn('metric_prefix', sd_md.name)
def setup_create_timeseries_test(self):
client = mock.Mock()
execution_context.clear()
option = stackdriver.Options(project_id="project-test",
resource="global")
exporter = stackdriver.StackdriverStatsExporter(options=option,
client=client)
stats = stats_module.Stats()
view_manager = stats.view_manager
stats_recorder = stats.stats_recorder
if len(view_manager.measure_to_view_map.exporters) > 0:
view_manager.unregister_exporter(
view_manager.measure_to_view_map.exporters[0])
view_manager.register_exporter(exporter)
return view_manager, stats_recorder, exporter
def test_register_metric_descriptor(self):
exporter = stackdriver.StackdriverStatsExporter(
options=stackdriver.Options(metric_prefix='metric_prefix',
project_id='project_id'),
client=mock.Mock())
oc_md = metric_descriptor.MetricDescriptor(
name='name',
description='description',
unit='unit',
type_=metric_descriptor.MetricDescriptorType.GAUGE_INT64,
label_keys=[label_key.LabelKey('key', 'description')])
exporter.register_metric_descriptor(oc_md)
self.assertEqual(exporter.client.create_metric_descriptor.call_count,
1)
exporter.register_metric_descriptor(oc_md)
self.assertEqual(exporter.client.create_metric_descriptor.call_count,
1)
def test_create_timeseries_from_distribution(self):
"""Check for explicit 0-bound bucket for SD export."""
v_data = mock.Mock(spec=view_data_module.ViewData)
v_data.view.name = "example.org/test_view"
v_data.view.columns = ['tag_key']
v_data.view.aggregation.aggregation_type = \
aggregation_module.Type.DISTRIBUTION
v_data.start_time = TEST_TIME
v_data.end_time = TEST_TIME
# Aggregation over (10 * range(10)) for buckets [2, 4, 6, 8]
dad = aggregation_data_module.DistributionAggregationData(
mean_data=4.5,
count_data=100,
sum_of_sqd_deviations=825,
counts_per_bucket=[20, 20, 20, 20, 20],
bounds=[2, 4, 6, 8],
exemplars={mock.Mock()
for ii in range(5)})
v_data.tag_value_aggregation_data_map = {('tag_value', ): dad}
exporter = stackdriver.StackdriverStatsExporter(
options=mock.Mock(),
client=mock.Mock(),
)
time_series_list = exporter.create_time_series_list(v_data, "", "")
self.assertEqual(len(time_series_list), 1)
[time_series] = time_series_list
self.assertCorrectLabels(time_series.metric.labels,
{'tag_key': 'tag_value'},
include_opencensus=True)
self.assertEqual(len(time_series.points), 1)
[point] = time_series.points
dv = point.value.distribution_value
self.assertEqual(100, dv.count)
self.assertEqual(4.5, dv.mean)
self.assertEqual(825.0, dv.sum_of_squared_deviation)
self.assertEqual([0, 20, 20, 20, 20, 20], dv.bucket_counts)
self.assertEqual([0, 2, 4, 6, 8],
dv.bucket_options.explicit_buckets.bounds)
def test_create_timeseries_invalid_aggregation(self):
v_data = mock.Mock(spec=view_data_module.ViewData)
v_data.view.name = "example.org/base_view"
v_data.view.columns = [tag_key_module.TagKey('base_key')]
v_data.view.aggregation.aggregation_type = \
aggregation_module.Type.NONE
v_data.start_time = TEST_TIME
v_data.end_time = TEST_TIME
base_data = aggregation_data_module.BaseAggregationData(10)
v_data.tag_value_aggregation_data_map = {
(None, ): base_data,
}
exporter = stackdriver.StackdriverStatsExporter(
options=mock.Mock(),
client=mock.Mock(),
)
self.assertRaises(TypeError, exporter.create_time_series_list, v_data,
"", "")
def test_get_metric_descriptor(self):
exporter = stackdriver.StackdriverStatsExporter(
options=stackdriver.Options(default_monitoring_labels={'dk': 'dd'},
project_id='project_id'),
client=mock.Mock())
oc_md = metric_descriptor.MetricDescriptor(
name='name',
description='description',
unit='unit',
type_=metric_descriptor.MetricDescriptorType.GAUGE_INT64,
label_keys=[label_key.LabelKey('ck', 'cd')])
sd_md = exporter.get_metric_descriptor(oc_md)
self.assertEqual(sd_md.metric_kind,
monitoring_v3.enums.MetricDescriptor.MetricKind.GAUGE)
self.assertEqual(sd_md.value_type,
monitoring_v3.enums.MetricDescriptor.ValueType.INT64)
self.assertIsInstance(sd_md, monitoring_v3.types.MetricDescriptor)
exporter.client.create_metric_descriptor.assert_not_called()
def test_stats_record_sync(self):
# We are using sufix in order to prevent cached objects
sufix = str(os.getgid())
tag_key = "SampleKeySyncTest%s" % sufix
measure_name = "SampleMeasureNameSyncTest%s" % sufix
measure_description = "SampleDescriptionSyncTest%s" % sufix
view_name = "SampleViewNameSyncTest%s" % sufix
view_description = "SampleViewDescriptionSyncTest%s" % sufix
FRONTEND_KEY = tag_key_module.TagKey(tag_key)
VIDEO_SIZE_MEASURE = measure_module.MeasureInt(measure_name,
measure_description,
"By")
VIDEO_SIZE_VIEW_NAME = view_name
VIDEO_SIZE_DISTRIBUTION = aggregation_module.DistributionAggregation(
[0.0, 16.0 * MiB, 256.0 * MiB])
VIDEO_SIZE_VIEW = view_module.View(VIDEO_SIZE_VIEW_NAME,
view_description, [FRONTEND_KEY],
VIDEO_SIZE_MEASURE,
VIDEO_SIZE_DISTRIBUTION)
stats = stats_module.Stats()
view_manager = stats.view_manager
stats_recorder = stats.stats_recorder
client = monitoring_v3.MetricServiceClient()
exporter = stackdriver.StackdriverStatsExporter(
options=stackdriver.Options(project_id=PROJECT),
client=client,
transport=sync.SyncTransport)
view_manager.register_exporter(exporter)
# Register view.
view_manager.register_view(VIDEO_SIZE_VIEW)
# Sleep for [0, 10] milliseconds to fake work.
time.sleep(random.randint(1, 10) / 1000.0)
# Process video.
# Record the processed video size.
tag_value = tag_value_module.TagValue("1200")
tag_map = tag_map_module.TagMap()
tag_map.insert(FRONTEND_KEY, tag_value)
measure_map = stats_recorder.new_measurement_map()
measure_map.measure_int_put(VIDEO_SIZE_MEASURE, 25 * MiB)
measure_map.record(tag_map)
# Sleep for [0, 10] milliseconds to fake wait.
time.sleep(random.randint(1, 10) / 1000.0)
@retry(wait_fixed=RETRY_WAIT_PERIOD,
stop_max_attempt_number=RETRY_MAX_ATTEMPT)
def get_metric_descriptors(self, exporter, view_description):
name = exporter.client.project_path(PROJECT)
list_metrics_descriptors = exporter.client.list_metric_descriptors(
name)
element = next((element for element in list_metrics_descriptors
if element.description == view_description), None)
self.assertIsNotNone(element)
self.assertEqual(element.description, view_description)
self.assertEqual(element.unit, "By")
get_metric_descriptors(self, exporter, view_description)
def test_constructor(self):
exporter = stackdriver.StackdriverStatsExporter()
self.assertIsNone(exporter.client)
def test_create_timeseries_with_resource(self, monitor_resource_mock):
client = mock.Mock()
execution_context.clear()
option = stackdriver.Options(project_id="project-test", resource="")
exporter = stackdriver.StackdriverStatsExporter(options=option,
client=client)
stats = stats_module.stats
view_manager = stats.view_manager
stats_recorder = stats.stats_recorder
if len(view_manager.measure_to_view_map.exporters) > 0:
view_manager.unregister_exporter(
view_manager.measure_to_view_map.exporters[0])
view_manager.register_exporter(exporter)
view_manager.register_view(VIDEO_SIZE_VIEW)
tag_value = tag_value_module.TagValue("1200")
tag_map = tag_map_module.TagMap()
tag_map.insert(FRONTEND_KEY, tag_value)
measure_map = stats_recorder.new_measurement_map()
measure_map.measure_int_put(VIDEO_SIZE_MEASURE, 25 * MiB)
measure_map.record(tag_map)
v_data = measure_map.measure_to_view_map.get_view(
VIDEO_SIZE_VIEW_NAME, None)
v_data = metric_utils.view_data_to_metric(v_data, TEST_TIME)
# check for gce_instance monitored resource
mocked_labels = {
'instance_id': 'my-instance',
'project_id': 'my-project',
'zone': 'us-east1',
'pod_id': 'localhost',
'namespace_id': 'namespace'
}
mock_resource = mock.Mock()
mock_resource.get_type.return_value = 'gce_instance'
mock_resource.get_labels.return_value = mocked_labels
monitor_resource_mock.return_value = mock_resource
time_series_list = exporter.create_time_series_list(v_data)
self.assertEqual(len(time_series_list), 1)
time_series = time_series_list[0]
self.assertEqual(time_series.resource.type, "gce_instance")
self.check_labels(
time_series.resource.labels, {
'instance_id': 'my-instance',
'project_id': 'my-project',
'zone': 'us-east1',
})
self.assertEqual(
time_series.metric.type,
"custom.googleapis.com/opencensus/my.org/views/video_size_test2")
self.assertIsNotNone(time_series)
time_series_list = exporter.create_time_series_list(v_data)
self.assertEqual(len(time_series_list), 1)
time_series = time_series_list[0]
self.assertEqual(
time_series.metric.type,
"custom.googleapis.com/opencensus/my.org/views/video_size_test2")
# check for gke_container monitored resource
mocked_labels = {
'instance_id': 'my-instance',
'project_id': 'my-project',
'zone': 'us-east1',
'pod_id': 'localhost',
'cluster_name': 'cluster',
'namespace_id': 'namespace'
}
mock_resource = mock.Mock()
mock_resource.get_type.return_value = 'gke_container'
mock_resource.get_labels.return_value = mocked_labels
monitor_resource_mock.return_value = mock_resource
time_series_list = exporter.create_time_series_list(v_data)
self.assertEqual(len(time_series_list), 1)
time_series = time_series_list[0]
self.assertEqual(time_series.resource.type, "k8s_container")
self.check_labels(
time_series.resource.labels, {
'project_id': 'my-project',
'location': 'us-east1',
'cluster_name': 'cluster',
'pod_name': 'localhost',
'namespace_name': 'namespace',
})
self.assertEqual(
time_series.metric.type,
"custom.googleapis.com/opencensus/my.org/views/video_size_test2")
self.assertIsNotNone(time_series)
# check for aws_ec2_instance monitored resource
mocked_labels = {
'instance_id': 'my-instance',
'aws_account': 'my-project',
'region': 'us-east1',
}
mock_resource = mock.Mock()
mock_resource.get_type.return_value = 'aws_ec2_instance'
mock_resource.get_labels.return_value = mocked_labels
monitor_resource_mock.return_value = mock_resource
time_series_list = exporter.create_time_series_list(v_data)
self.assertEqual(len(time_series_list), 1)
time_series = time_series_list[0]
self.assertEqual(time_series.resource.type, "aws_ec2_instance")
self.check_labels(
time_series.resource.labels, {
'instance_id': 'my-instance',
'aws_account': 'my-project',
'region': 'aws:us-east1',
})
self.assertEqual(
time_series.metric.type,
"custom.googleapis.com/opencensus/my.org/views/video_size_test2")
self.assertIsNotNone(time_series)
# check for out of box monitored resource
mock_resource = mock.Mock()
mock_resource.get_type.return_value = ''
mock_resource.get_labels.return_value = mock.Mock()
monitor_resource_mock.return_value = mock_resource
time_series_list = exporter.create_time_series_list(v_data)
self.assertEqual(len(time_series_list), 1)
time_series = time_series_list[0]
self.assertEqual(time_series.resource.type, 'global')
self.check_labels(time_series.resource.labels, {})
self.assertEqual(
time_series.metric.type,
"custom.googleapis.com/opencensus/my.org/views/video_size_test2")
self.assertIsNotNone(time_series)
def test_set_default_labels(self):
labels = {'key': 'value'}
exporter = stackdriver.StackdriverStatsExporter()
exporter.set_default_labels(labels)
self.assertEqual(exporter.default_labels, labels)
