def test_stats_record_async(self):
# We are using sufix in order to prevent cached objects
sufix = str(os.getpid())
tag_key = "SampleKeyAsyncTest%s" % sufix
measure_name = "SampleMeasureNameAsyncTest%s" % sufix
measure_description = "SampleDescriptionAsyncTest%s" % sufix
view_name = "SampleViewNameAsyncTest%s" % sufix
view_description = "SampleViewDescriptionAsyncTest%s" % sufix
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)
@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 stats():
global _stats
if not _stats:
new_stats = stats_module.Stats()
if environment.in_gae() and not environment.in_test():
exporter = stackdriver.new_stats_exporter(
stackdriver.Options(project_id=metadata.project_id(), ))
new_stats.view_manager.register_exporter(exporter)
_stats = new_stats
return _stats
def test_not_blank_project(self):
patch_client = mock.patch(
('opencensus.stats.exporters.stackdriver_exporter'
'.monitoring_v3.MetricServiceClient'), _Client)
with patch_client:
exporter_created = stackdriver.new_stats_exporter(
stackdriver.Options(project_id=1))
self.assertIsInstance(exporter_created,
stackdriver.StackdriverStatsExporter)
def test_singleton_with_params(self):
default_labels = {'key1': 'value1'}
patch_client = mock.patch(
('opencensus.stats.exporters.stackdriver_exporter'
'.monitoring_v3.MetricServiceClient'), _Client)
with patch_client:
exporter_created = stackdriver.new_stats_exporter(
stackdriver.Options(project_id=1,
default_monitoring_labels=default_labels))
self.assertEqual(exporter_created.default_labels, default_labels)
def _enable_exporter():
"""Create and register the stackdriver exporter.
For any data to be exported to stackdriver, an exporter needs to be created
and registered with the view manager. Collected data will be reported via
all the registered exporters. By not creating and registering an exporter,
all collected data will stay local and will not appear on stackdriver.
"""
project_id = _get_project_id()
exporter = stackdriver_exporter.new_stats_exporter(
stackdriver_exporter.Options(project_id=project_id))
STATS.view_manager.register_exporter(exporter)
def _new_exporter():
"""
Initializes a metrics exporter.
Tries to initialize a Stackdriver exporter, falls back to StdoutExporter.
"""
try:
_, project_id = google.auth.default()
return stackdriver_exporter.new_stats_exporter(
stackdriver_exporter.Options(project_id=project_id, resource='global'))
except google.auth.exceptions.DefaultCredentialsError:
_logger.exception("Using stdout exporter")
return StdoutExporter()
def test_client_info_user_agent(self):
"""Check that the monitoring client sets a user agent.
The user agent should include the library version. Note that this
assumes MetricServiceClient calls ClientInfo.to_user_agent to attach
the user agent as metadata to metric service API calls.
"""
patch_client = mock.patch(
'opencensus.stats.exporters.stackdriver_exporter.monitoring_v3'
'.MetricServiceClient', _Client)
with patch_client:
exporter = stackdriver.new_stats_exporter(
stackdriver.Options(project_id=1))
self.assertIn(stackdriver.get_user_agent_slug(),
exporter.client.client_info.to_user_agent())
def main():
# Enable metrics
exporter = stackdriver_exporter.new_stats_exporter(
stackdriver_exporter.Options(project_id=project_id))
view_manager.register_exporter(exporter)
view_manager.register_view(latency_view)
mmap = stats_recorder.new_measurement_map()
tmap = tag_map_module.TagMap()
for i in range(100):
ms = random.random() * 5 * 1000
print("Latency {0}:{1}".format(i, ms))
mmap.measure_float_put(m_latency_ms, ms)
mmap.record(tmap)
time.sleep(1)
print("Done recording metrics")
FRONTEND_KEY = tag_key_module.TagKey("my.org/keys/frontend")
VIDEO_SIZE_MEASURE = measure_module.MeasureInt(
"my.org/measure/video_size_test2", "size of processed videos", "By")
VIDEO_SIZE_VIEW_NAME = "my.org/views/video_size_test2"
VIDEO_SIZE_DISTRIBUTION = aggregation_module.DistributionAggregation(
[0.0, 16.0 * MiB, 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 = stackdriver.new_stats_exporter(
stackdriver.Options(project_id="opencenus-node"))
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(str(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)
def test_not_blank_project(self):
exporter_created = stackdriver.new_stats_exporter(stackdriver.Options(project_id=1))
self.assertIsInstance(exporter_created, stackdriver.StackdriverStatsExporter)
def test_singleton_with_params(self):
default_labels = {'key1':'value1'}
exporter_created = stackdriver.new_stats_exporter(stackdriver.Options(project_id=1,default_monitoring_labels=default_labels))
self.assertEqual(exporter_created.default_labels, default_labels)
[0.0, 16.0 * MiB, 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
try:
_, project_id = google.auth.default()
except google.auth.exceptions.DefaultCredentialsError:
raise ValueError("Couldn't find Google Cloud credentials, set the "
"project ID with 'gcloud set project'")
exporter = stackdriver.new_stats_exporter(
stackdriver.Options(project_id=project_id))
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(str(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)
