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)
time_series_list = exporter.create_time_series_list(
v_data, "global", "")
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.assertCorrectLabels(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_stats_record_sync(self):
# We are using suffix in order to prevent cached objects
suffix = str(os.getgid())
tag_key = "SampleKeySyncTest%s" % suffix
measure_name = "SampleMeasureNameSyncTest%s" % suffix
measure_description = "SampleDescriptionSyncTest%s" % suffix
view_name = "SampleViewNameSyncTest%s" % suffix
view_description = "SampleViewDescriptionSyncTest%s" % suffix
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_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_record_with_multi_keys(self):
measure = mock.Mock()
sum_aggregation = aggregation_module.SumAggregation()
view = view_module.View("test_view", "description", ['key1', 'key2'],
measure, sum_aggregation)
start_time = datetime.utcnow()
end_time = datetime.utcnow()
view_data = view_data_module.ViewData(view=view,
start_time=start_time,
end_time=end_time)
context = mock.Mock()
context.map = {'key1': 'val1', 'key2': 'val2'}
time = datetime.utcnow().isoformat() + 'Z'
value = 1
self.assertEqual({}, view_data.tag_value_aggregation_data_map)
view_data.record(context=context, value=value, timestamp=time)
tag_values = view_data.get_tag_values(tags=context.map,
columns=view.columns)
tuple_vals = tuple(tag_values)
self.assertEqual(['val1', 'val2'], tag_values)
self.assertIsNotNone(view_data.tag_value_aggregation_data_map)
self.assertTrue(tuple_vals in view_data.tag_value_aggregation_data_map)
self.assertIsNotNone(
view_data.tag_value_aggregation_data_map[tuple_vals])
sum_data = view_data.tag_value_aggregation_data_map.get(tuple_vals)
self.assertEqual(1, sum_data.sum_data)
context_2 = mock.Mock()
context_2.map = {'key1': 'val3', 'key2': 'val2'}
time_2 = datetime.utcnow().isoformat() + 'Z'
value_2 = 2
view_data.record(context=context_2, value=value_2, timestamp=time_2)
tag_values_2 = view_data.get_tag_values(tags=context_2.map,
columns=view.columns)
tuple_vals_2 = tuple(tag_values_2)
self.assertEqual(['val3', 'val2'], tag_values_2)
self.assertTrue(
tuple_vals_2 in view_data.tag_value_aggregation_data_map)
sum_data_2 = view_data.tag_value_aggregation_data_map.get(tuple_vals_2)
self.assertEqual(2, sum_data_2.sum_data)
time_3 = datetime.utcnow().isoformat() + 'Z'
value_3 = 3
# Use the same context {'key1': 'val1', 'key2': 'val2'}.
# Record to entry [(val1, val2), sum=1].
view_data.record(context=context, value=value_3, timestamp=time_3)
self.assertEqual(4, sum_data.sum_data)
# The other entry should remain unchanged.
self.assertEqual(2, sum_data_2.sum_data)
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_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 create_measurement_view(self, measurement_name):
"creates a measurement and a view"
tg_key = tag_key_module.TagKey("TEST_ID")
measurement = measure_module.MeasureInt(
f"gw_m_{measurement_name}_response",
"response time of the home page", "s")
view_name = f"views_{measurement_name}_response"
aggregation = aggregation_module.LastValueAggregation()
view = view_module.View(view_name,
f"glasswall {measurement_name} response time",
[tg_key], measurement, aggregation)
# Register view.
self.view_manager.register_view(view)
return measurement
def test_constructor(self):
name = "testName"
description = "testMeasure"
columns = ["testTagKey1", "testTagKey2"]
measure = mock.Mock()
aggregation = mock.Mock()
view = view_module.View(name=name, description=description, columns=columns, measure=measure, aggregation=aggregation)
self.assertEqual("testName", view.name)
self.assertEqual("testMeasure", view.description)
self.assertEqual(["testTagKey1", "testTagKey2"], view.columns)
self.assertEqual(measure, view.measure)
self.assertEqual(aggregation, view.aggregation)
def configure():
"""Globally enables metrics collection."""
global _METRICS_ENABLED
if _METRICS_ENABLED:
return
_METRICS_ENABLED = True
STATS.view_manager.register_exporter(_new_exporter())
latency_view = view.View(
"fireci/latency", "Latency of fireci execution stages", _TAGS, _m_latency,
aggregation.LastValueAggregation())
success_view = view.View(
"fireci/success", "Success indication of fireci execution stages", _TAGS,
_m_success, aggregation.LastValueAggregation())
STATS.view_manager.register_view(latency_view)
STATS.view_manager.register_view(success_view)
context = tags.TagMap()
for tag in _TAGS:
if tag.upper() in os.environ:
context.insert(tag, tags.TagValue(os.environ[tag.upper()]))
execution_context.set_current_tag_map(context)
def test_stats_record_async(self):
# We are using suffix in order to prevent cached objects
suffix = str(os.getpid())
tag_key = "SampleKeyAsyncTest%s" % suffix
measure_name = "SampleMeasureNameAsyncTest%s" % suffix
measure_description = "SampleDescriptionAsyncTest%s" % suffix
view_name = "SampleViewNameAsyncTest%s" % suffix
view_description = "SampleViewDescriptionAsyncTest%s" % suffix
FRONTEND_KEY_ASYNC = tag_key_module.TagKey(tag_key)
VIDEO_SIZE_MEASURE_ASYNC = measure_module.MeasureInt(
measure_name, measure_description, "By")
VIDEO_SIZE_VIEW_NAME_ASYNC = view_name
VIDEO_SIZE_DISTRIBUTION_ASYNC =\
aggregation_module.DistributionAggregation(
[0.0, 16.0 * MiB, 256.0 * MiB]
)
VIDEO_SIZE_VIEW_ASYNC = view_module.View(
VIDEO_SIZE_VIEW_NAME_ASYNC, view_description, [FRONTEND_KEY_ASYNC],
VIDEO_SIZE_MEASURE_ASYNC, VIDEO_SIZE_DISTRIBUTION_ASYNC)
stats = stats_module.stats
view_manager = stats.view_manager
stats_recorder = stats.stats_recorder
exporter = stackdriver.new_stats_exporter(
stackdriver.Options(project_id=PROJECT))
view_manager.register_exporter(exporter)
# Register view.
view_manager.register_view(VIDEO_SIZE_VIEW_ASYNC)
# 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_ASYNC, tag_value)
measure_map = stats_recorder.new_measurement_map()
measure_map.measure_int_put(VIDEO_SIZE_MEASURE_ASYNC, 25 * MiB)
measure_map.record(tag_map)
# Give the exporter thread enough time to export exactly once
time.sleep(transport.DEFAULT_INTERVAL * 1.5)
self.check_sd_md(exporter, view_description)
def test_record_with_attachment(self):
boundaries = [1, 2, 3]
distribution = {1: "test"}
distribution_aggregation = aggregation_module.DistributionAggregation(
boundaries=boundaries, distribution=distribution)
name = "testName"
description = "testMeasure"
unit = "testUnit"
measure = measure_module.MeasureInt(name=name,
description=description,
unit=unit)
description = "testMeasure"
columns = ["key1", "key2"]
view = view_module.View(name=name,
description=description,
columns=columns,
measure=measure,
aggregation=distribution_aggregation)
start_time = datetime.utcnow()
attachments = {"One": "one", "Two": "two"}
end_time = datetime.utcnow()
view_data = view_data_module.ViewData(view=view,
start_time=start_time,
end_time=end_time)
context = mock.Mock
context.map = {'key1': 'val1', 'key2': 'val2'}
time = datetime.utcnow().isoformat() + 'Z'
value = 1
view_data.record(context=context,
value=value,
timestamp=time,
attachments=attachments)
tag_values = view_data.get_tag_values(tags=context.map,
columns=view.columns)
tuple_vals = tuple(tag_values)
self.assertEqual(['val1', 'val2'], tag_values)
self.assertIsNotNone(view_data.tag_value_aggregation_data_map)
self.assertTrue(tuple_vals in view_data.tag_value_aggregation_data_map)
self.assertIsNotNone(
view_data.tag_value_aggregation_data_map[tuple_vals])
self.assertEqual(
attachments, view_data.tag_value_aggregation_data_map[tuple_vals].
exemplars[1].attachments)
def __init__(self, export_metrics=False):
self.nb_check_requests = measure_module.MeasureInt(
"nb_check_requests",
"number of dates check requests for all weeks", "nb")
self.nb_check_requests_view = view_module.View(
"nb_check_requests view",
"number of dates check requests for all weeks", [],
self.nb_check_requests, aggregation_module.CountAggregation())
view_manager.register_view(self.nb_check_requests_view)
self.mmap = stats_recorder.new_measurement_map()
self.tmap = tag_map_module.TagMap()
if export_metrics:
exporter = metrics_exporter.new_metrics_exporter(
connection_string=azure_insights.connection_string)
view_manager.register_exporter(exporter)
def setup_open_census():
stats_stats = stats.Stats()
app.view_manager = stats_stats.view_manager
app.stats_recorder = stats_stats.stats_recorder
response_time_view = view.View("response_time",
"The time it took to respond",
[key_method, key_status, key_error],
m_response_ms,
aggregation.LastValueAggregation())
app.exporter = prometheus.new_stats_exporter(
prometheus.Options(namespace="flask_app", port=8000))
app.view_manager.register_exporter(app.exporter)
app.view_manager.register_view(response_time_view)
def test_collector_to_metric_invalid_dist(self):
agg = mock.Mock()
view = view_module.View(VIDEO_SIZE_VIEW_NAME,
"processed video size over time",
[FRONTEND_KEY], VIDEO_SIZE_MEASURE, agg)
registry = mock.Mock()
options = prometheus.Options("test1", 8001, "localhost", registry)
collector = prometheus.Collector(options=options)
collector.register_view(view)
desc = collector.registered_views[list(REGISTERED_VIEW)[0]]
with self.assertRaisesRegexp(
ValueError,
'unsupported aggregation type <class \'mock.mock.Mock\'>'):
collector.to_metric(desc=desc, tag_values=[None], agg_data=agg)
def test_create_metric_descriptor_sum_int(self):
client = mock.Mock()
start_time = datetime.utcnow()
end_time = datetime.utcnow()
option = stackdriver.Options(project_id="project-test", metric_prefix="teste")
view_name_sum_int= "view-sum-int"
agg_sum = aggregation_module.SumAggregation(sum=2)
view_sum_int = view_module.View(view_name_sum_int,
"processed video size over time",
[FRONTEND_KEY],
VIDEO_SIZE_MEASURE,
agg_sum)
exporter = stackdriver.StackdriverStatsExporter(options=option, client=client)
desc = exporter.create_metric_descriptor(view_sum_int)
self.assertNotEqual(desc, None)
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_last_value_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_1 = aggregation_module.LastValueAggregation(value=2)
view_name1 = "view-name1"
new_view1 = view_module.View(view_name1,
"processed video size over time",
[FRONTEND_KEY_FLOAT],
VIDEO_SIZE_MEASURE_FLOAT, agg_1)
view_manager.register_view(new_view1)
tag_value_int = tag_value_module.TagValue("Abc")
tag_map = tag_map_module.TagMap()
tag_map.insert(FRONTEND_KEY_INT, tag_value_int)
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(view_name1, None)
time_series = exporter.create_time_series_list(v_data, "global",
"kubernetes.io/myorg")
self.assertEquals(time_series.metric.type,
"kubernetes.io/myorg/view-name1")
self.assertIsNotNone(time_series)
def test_collector_to_metric_last_value(self):
agg = aggregation_module.LastValueAggregation(256)
view = view_module.View(VIDEO_SIZE_VIEW_NAME,
"processed video size over time",
[FRONTEND_KEY], VIDEO_SIZE_MEASURE, agg)
registry = mock.Mock()
view_data = mock.Mock()
options = prometheus.Options("test1", 8001, "localhost", registry)
collector = prometheus.Collector(options=options, view_data=view_data)
collector.register_view(view)
desc = collector.registered_views[list(REGISTERED_VIEW)[0]]
metric = collector.to_metric(desc=desc, view=view)
self.assertEqual(desc['name'], metric.name)
self.assertEqual(desc['documentation'], metric.documentation)
self.assertEqual('gauge', metric.type)
self.assertEqual(1, len(metric.samples))
def test_view_to_metric_descriptor(self):
mock_measure = mock.Mock(spec=measure.MeasureFloat)
mock_agg = mock.Mock(spec=aggregation.SumAggregation)
mock_agg.aggregation_type = aggregation.Type.SUM
test_view = view.View("name", "description", ["tk1", "tk2"],
mock_measure, mock_agg)
md = metric_utils.view_to_metric_descriptor(test_view)
self.assertTrue(isinstance(md, metric_descriptor.MetricDescriptor))
self.assertEqual(md.name, test_view.name)
self.assertEqual(md.description, test_view.description)
self.assertEqual(md.unit, test_view.measure.unit)
self.assertEqual(
md.type, metric_descriptor.MetricDescriptorType.CUMULATIVE_DOUBLE)
self.assertTrue(
all(lk.key == col
for lk, col in zip(md.label_keys, test_view.columns)))
def test_export_double_point_value(self):
view = view_module.View('', '', [FRONTEND_KEY], VIDEO_SIZE_MEASURE,
aggregation_module.SumAggregation())
v_data = view_data_module.ViewData(view=view,
start_time=TEST_TIME_STR,
end_time=TEST_TIME_STR)
v_data.record(context=tag_map_module.TagMap(),
value=2.5,
timestamp=None)
view_data = [v_data]
view_data = [metric_utils.view_data_to_metric(view_data[0], TEST_TIME)]
handler = mock.Mock(spec=ocagent.ExportRpcHandler)
ocagent.StatsExporter(handler).export_metrics(view_data)
self.assertEqual(
handler.send.call_args[0]
[0].metrics[0].timeseries[0].points[0].double_value, 2.5)
def test_collector_collect_with_none_label_value(self):
agg = aggregation_module.LastValueAggregation(256)
view = view_module.View("new_view", "processed video size over time",
[FRONTEND_KEY], VIDEO_SIZE_MEASURE, agg)
registry = mock.Mock()
options = prometheus.Options("test3", 8001, "localhost", registry)
collector = prometheus.Collector(options=options)
collector.register_view(view)
desc = collector.registered_views['test3_new_view']
metric = collector.to_metric(
desc=desc, tag_values=[None], agg_data=agg.aggregation_data)
self.assertEqual(1, len(metric.samples))
sample = metric.samples[0]
# Sample is a namedtuple
# ('Sample', ['name', 'labels', 'value', 'timestamp', 'exemplar'])
label_map = sample[1]
self.assertEqual({"myorg_keys_frontend": ""}, label_map)
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_2 = aggregation_module.SumAggregation(sum=2.2)
view_name2 = "view-name2"
new_view2 = view_module.View(view_name2,
"processed video size over time",
[FRONTEND_KEY_FLOAT],
VIDEO_SIZE_MEASURE_FLOAT, agg_2)
view_manager.register_view(new_view2)
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_name2, None)
time_series = exporter.create_time_series_list(v_data, "global", "")
self.assertEquals(time_series.metric.type,
"custom.googleapis.com/opencensus/view-name2")
self.assertIsNotNone(time_series)
def test_create_timeseries_disjoint_tags(self, monitoring_resoure_mock):
view_manager, stats_recorder, exporter = \
self.setup_create_timeseries_test()
# Register view with two tags
view_name = "view-name"
view = view_module.View(view_name, "test description",
[FRONTEND_KEY, FRONTEND_KEY_FLOAT],
VIDEO_SIZE_MEASURE,
aggregation_module.SumAggregation())
view_manager.register_view(view)
# Add point with one tag in common and one different tag
measure_map = stats_recorder.new_measurement_map()
tag_map = tag_map_module.TagMap()
tag_map.insert(FRONTEND_KEY, tag_value_module.TagValue("1200"))
tag_map.insert(FRONTEND_KEY_STR, tag_value_module.TagValue("1800"))
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(view_name, 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
# Verify first time series
self.assertEqual(time_series.resource.type, "global")
self.assertEqual(time_series.metric.type,
"custom.googleapis.com/opencensus/" + view_name)
self.check_labels(time_series.metric.labels,
{FRONTEND_KEY_CLEAN: "1200"},
include_opencensus=True)
self.assertIsNotNone(time_series.resource)
self.assertEqual(len(time_series.points), 1)
expected_value = monitoring_v3.types.TypedValue()
# TODO: #565
expected_value.double_value = 25.0 * MiB
self.assertEqual(time_series.points[0].value, expected_value)
def test_prometheus_stats(self):
MiB = 1 << 20
FRONTEND_KEY = tag_key_module.TagKey("my.org/keys/frontend")
VIDEO_SIZE_MEASURE = measure_module.MeasureInt(
"my.org/measures/video_size", "size of processed videos", "By")
VIDEO_SIZE_VIEW_NAME = "my.org/views/video_size"
VIDEO_SIZE_DISTRIBUTION = aggregation_module.CountAggregation(256.0 *
MiB)
VIDEO_SIZE_VIEW = view_module.View(VIDEO_SIZE_VIEW_NAME,
"processed video size over time",
[FRONTEND_KEY], VIDEO_SIZE_MEASURE,
VIDEO_SIZE_DISTRIBUTION)
stats = stats_module.Stats()
view_manager = stats.view_manager
stats_recorder = stats.stats_recorder
exporter = prometheus.new_stats_exporter(
prometheus.Options(namespace="opencensus", port=9303))
view_manager.register_exporter(exporter)
view_manager.register_view(VIDEO_SIZE_VIEW)
time.sleep(random.randint(1, 10) / 1000.0)
tag_value = tag_value_module.TagValue(str(random.randint(1, 10000)))
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)
if sys.version_info > (3, 0):
import urllib.request
contents = urllib.request.urlopen(
"http://localhost:9303/metrics").read()
else:
import urllib2
contents = urllib2.urlopen("http://localhost:9303/metrics").read()
self.assertIn(b'# TYPE opencensus_my.org/views/video_size counter',
contents)
self.assertIn(b'opencensus_my.org/views/video_size 268435456.0',
contents)
def test_collector_to_metric_sum(self):
agg = aggregation_module.SumAggregation(256.0)
view = view_module.View(VIDEO_SIZE_VIEW_NAME,
"processed video size over time",
[FRONTEND_KEY], VIDEO_SIZE_MEASURE, agg)
registry = mock.Mock()
options = prometheus.Options("test1", 8001, "localhost", registry)
collector = prometheus.Collector(options=options)
collector.register_view(view)
desc = collector.registered_views[list(REGISTERED_VIEW)[0]]
metric = collector.to_metric(
desc=desc,
tag_values=[None],
agg_data=agg.new_aggregation_data(VIDEO_SIZE_MEASURE))
self.assertEqual(desc['name'], metric.name)
self.assertEqual(desc['documentation'], metric.documentation)
self.assertEqual('unknown', metric.type)
self.assertEqual(1, len(metric.samples))
def test_collector_collect(self):
agg = aggregation_module.LastValueAggregation(256)
view = view_module.View("new_view", "processed video size over time",
[FRONTEND_KEY], VIDEO_SIZE_MEASURE, agg)
registry = mock.Mock()
options = prometheus.Options("test2", 8001, "localhost", registry)
collector = prometheus.Collector(options=options)
collector.register_view(view)
desc = collector.registered_views['test2_new_view']
metric = collector.to_metric(
desc=desc,
tag_values=[tag_value_module.TagValue("value")],
agg_data=agg.aggregation_data)
self.assertEqual(desc['name'], metric.name)
self.assertEqual(desc['documentation'], metric.documentation)
self.assertEqual('gauge', metric.type)
expected_samples = [
Sample(metric.name, {"myorg_keys_frontend": "value"}, 256)]
self.assertEqual(expected_samples, metric.samples)
def test_record_with_none_context(self):
measure = mock.Mock(spec=measure_module.MeasureInt)
sum_aggregation = aggregation_module.SumAggregation()
view = view_module.View("test_view", "description", ['key1', 'key2'],
measure, sum_aggregation)
start_time = datetime.utcnow()
end_time = datetime.utcnow()
view_data = view_data_module.ViewData(view=view,
start_time=start_time,
end_time=end_time)
time = utils.to_iso_str()
value = 4
view_data.record(context=None,
value=value,
timestamp=time,
attachments=None)
tag_values = view_data.get_tag_values(tags={}, columns=view.columns)
tuple_vals = tuple(tag_values)
self.assertEqual([None, None], tag_values)
self.assertTrue(tuple_vals in view_data.tag_value_aggregation_data_map)
sum_data = view_data.tag_value_aggregation_data_map.get(tuple_vals)
self.assertEqual(4, sum_data.sum_data)
def test_create_timeseries_last_value_float_tagvalue(
self, monitor_resource_mock):
view_manager, stats_recorder, exporter = \
self.setup_create_timeseries_test()
agg_2 = aggregation_module.LastValueAggregation(value=2.2 * MiB)
view_name2 = "view-name2"
new_view2 = view_module.View(view_name2,
"processed video size over time",
[FRONTEND_KEY_FLOAT],
VIDEO_SIZE_MEASURE_FLOAT, agg_2)
view_manager.register_view(new_view2)
tag_value_float = tag_value_module.TagValue("Abc")
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, 25.7 * MiB)
measure_map.record(tag_map)
v_data = measure_map.measure_to_view_map.get_view(view_name2, None)
time_series_list = exporter.create_time_series_list(
v_data, "global", "kubernetes.io/myorg")
self.assertEqual(len(time_series_list), 1)
time_series = time_series_list[0]
self.assertEqual(time_series.metric.type,
"kubernetes.io/myorg/view-name2")
self.assertCorrectLabels(time_series.metric.labels,
{FRONTEND_KEY_FLOAT_CLEAN: "Abc"},
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 = 25.7 * MiB
self.assertEqual(time_series.points[0].value, expected_value)
