def __init__(
self,
stateful=True,
resource: Resource = Resource.create_empty(),
):
self.stateful = stateful
self.resource = resource
def test_extract_resources(self):
exporter = CloudMonitoringMetricsExporter(project_id=self.project_id)
self.assertIsNone(
exporter._get_monitored_resource(Resource.create_empty())
)
resource = Resource(
labels={
"cloud.account.id": 123,
"host.id": "host",
"cloud.zone": "US",
"cloud.provider": "gcp",
"extra_info": "extra",
"gcp.resource_type": "gce_instance",
"not_gcp_resource": "value",
}
)
expected_extract = MonitoredResource(
type="gce_instance",
labels={"project_id": "123", "instance_id": "host", "zone": "US"},
)
self.assertEqual(
exporter._get_monitored_resource(resource), expected_extract
)
resource = Resource(
labels={
"cloud.account.id": "123",
"host.id": "host",
"extra_info": "extra",
"not_gcp_resource": "value",
"gcp.resource_type": "gce_instance",
"cloud.provider": "gcp",
}
)
# Should throw when passed a malformed GCP resource dict
self.assertRaises(KeyError, exporter._get_monitored_resource, resource)
resource = Resource(
labels={
"cloud.account.id": "123",
"host.id": "host",
"extra_info": "extra",
"not_gcp_resource": "value",
"gcp.resource_type": "unsupported_gcp_resource",
"cloud.provider": "gcp",
}
)
self.assertIsNone(exporter._get_monitored_resource(resource))
resource = Resource(
labels={
"cloud.account.id": "123",
"host.id": "host",
"extra_info": "extra",
"not_gcp_resource": "value",
"cloud.provider": "aws",
}
)
self.assertIsNone(exporter._get_monitored_resource(resource))
def test_get_value_observer_metric_descriptor(self):
client = mock.Mock()
exporter = CloudMonitoringMetricsExporter(project_id=self.project_id,
client=client)
exporter.project_name = self.project_name
record = ExportRecord(
MockMetric(),
(),
ValueObserverAggregator(),
Resource.create_empty(),
)
exporter._get_metric_descriptor(record)
client.create_metric_descriptor.assert_called_with(
self.project_name,
MetricDescriptor(
**{
"name": None,
"type": "custom.googleapis.com/OpenTelemetry/name",
"display_name": "name",
"description": "description",
"labels": [],
"metric_kind": "GAUGE",
"value_type": "INT64",
}),
)
def test_unique_identifier(self):
client = mock.Mock()
exporter1 = CloudMonitoringMetricsExporter(
project_id=self.project_id,
client=client,
add_unique_identifier=True,
)
exporter2 = CloudMonitoringMetricsExporter(
project_id=self.project_id,
client=client,
add_unique_identifier=True,
)
exporter1.project_name = self.project_name
exporter2.project_name = self.project_name
client.create_metric_descriptor.return_value = MetricDescriptor(
**{
"name":
None,
"type":
"custom.googleapis.com/OpenTelemetry/name",
"display_name":
"name",
"description":
"description",
"labels": [
LabelDescriptor(key=UNIQUE_IDENTIFIER_KEY,
value_type="STRING"),
],
"metric_kind":
"CUMULATIVE",
"value_type":
"DOUBLE",
})
sum_agg_one = SumAggregator()
sum_agg_one.update(1)
metric_record = ExportRecord(MockMetric(), (), sum_agg_one,
Resource.create_empty())
exporter1.export([metric_record])
exporter2.export([metric_record])
(
first_call,
second_call,
) = client.create_metric_descriptor.call_args_list
self.assertEqual(first_call[0][1].labels[0].key, UNIQUE_IDENTIFIER_KEY)
self.assertEqual(second_call[0][1].labels[0].key,
UNIQUE_IDENTIFIER_KEY)
first_call, second_call = client.create_time_series.call_args_list
self.assertNotEqual(
first_call[0][1][0].metric.labels[UNIQUE_IDENTIFIER_KEY],
second_call[0][1][0].metric.labels[UNIQUE_IDENTIFIER_KEY],
)
def __init__(
self,
instrumentation_info: "InstrumentationInfo",
stateful: bool,
resource: Resource = Resource.create_empty(),
):
self.instrumentation_info = instrumentation_info
self.metrics = set()
self.observers = set()
self.batcher = UngroupedBatcher(stateful)
self.observers_lock = threading.Lock()
self.resource = resource
def __init__(
self,
sampler: sampling.Sampler = trace_api.sampling.ALWAYS_ON,
resource: Resource = Resource.create_empty(),
shutdown_on_exit: bool = True,
):
self._active_span_processor = MultiSpanProcessor()
self.resource = resource
self.sampler = sampler
self._atexit_handler = None
if shutdown_on_exit:
self._atexit_handler = atexit.register(self.shutdown)
def __init__(
self,
name: str,
context: trace_api.SpanContext,
parent: Optional[trace_api.SpanContext] = None,
sampler: Optional[sampling.Sampler] = None,
trace_config: None = None, # TODO
resource: Resource = Resource.create_empty(),
attributes: types.Attributes = None, # TODO
events: Sequence[Event] = None, # TODO
links: Sequence[trace_api.Link] = (),
kind: trace_api.SpanKind = trace_api.SpanKind.INTERNAL,
span_processor: SpanProcessor = SpanProcessor(),
instrumentation_info: InstrumentationInfo = None,
set_status_on_exception: bool = True,
) -> None:
self.name = name
self.context = context
self.parent = parent
self.sampler = sampler
self.trace_config = trace_config
self.resource = resource
self.kind = kind
self._set_status_on_exception = set_status_on_exception
self.span_processor = span_processor
self.status = None
self._lock = threading.Lock()
self._filter_attribute_values(attributes)
if not attributes:
self.attributes = Span._empty_attributes
else:
self.attributes = BoundedDict.from_map(MAX_NUM_ATTRIBUTES,
attributes)
if events is None:
self.events = Span._empty_events
else:
self.events = BoundedList(MAX_NUM_EVENTS)
for event in events:
self._filter_attribute_values(event.attributes)
self.events.append(event)
if links is None:
self.links = Span._empty_links
else:
self.links = BoundedList.from_seq(MAX_NUM_LINKS, links)
self._end_time = None # type: Optional[int]
self._start_time = None # type: Optional[int]
self.instrumentation_info = instrumentation_info
def __init__(
self,
stateful=True,
resource: Resource = Resource.create_empty(),
shutdown_on_exit: bool = True,
):
self.stateful = stateful
self.resource = resource
self._controllers = []
self._exporters = set()
self._atexit_handler = None
if shutdown_on_exit:
self._atexit_handler = atexit.register(self.shutdown)
def __init__(
self,
sampler: sampling.Sampler = sampling.DEFAULT_ON,
resource: Resource = Resource.create_empty(),
shutdown_on_exit: bool = True,
active_span_processor: Union[SynchronousMultiSpanProcessor,
ConcurrentMultiSpanProcessor] = None,
):
self._active_span_processor = (active_span_processor
or SynchronousMultiSpanProcessor())
self.resource = resource
self.sampler = sampler
self._atexit_handler = None
if shutdown_on_exit:
self._atexit_handler = atexit.register(self.shutdown)
def test_export_value_observer(self):
client = mock.Mock()
with mock.patch(
"opentelemetry.exporter.cloud_monitoring.time_ns",
lambda: NANOS_PER_SECOND,
):
exporter = CloudMonitoringMetricsExporter(
project_id=self.project_id, client=client)
exporter.project_name = self.project_name
client.create_metric_descriptor.return_value = MetricDescriptor(
**{
"name": None,
"type": "custom.googleapis.com/OpenTelemetry/name",
"display_name": "name",
"description": "description",
"labels": [],
"metric_kind": "GAUGE",
"value_type": "INT64",
})
aggregator = ValueObserverAggregator()
aggregator.checkpoint = aggregator._TYPE(1, 2, 3, 4, 5)
aggregator.last_update_timestamp = (WRITE_INTERVAL +
1) * NANOS_PER_SECOND
exporter.export([
ExportRecord(
MockMetric(meter=mock_meter()),
(),
aggregator,
Resource.create_empty(),
)
])
series = TimeSeries()
series.metric_kind = MetricDescriptor.MetricKind.GAUGE
series.metric.type = "custom.googleapis.com/OpenTelemetry/name"
point = series.points.add()
point.value.int64_value = 5
point.interval.end_time.seconds = WRITE_INTERVAL + 1
point.interval.end_time.nanos = 0
point.interval.start_time.seconds = WRITE_INTERVAL + 1
point.interval.start_time.nanos = 0
client.create_time_series.assert_has_calls(
[mock.call(self.project_name, [series])])
def test_get_metric_descriptor(self):
client = mock.Mock()
exporter = CloudMonitoringMetricsExporter(project_id=self.project_id,
client=client)
exporter.project_name = self.project_name
self.assertIsNone(
exporter._get_metric_descriptor(
ExportRecord(
MockMetric(),
(),
UnsupportedAggregator(),
Resource.create_empty(),
)))
record = ExportRecord(
MockMetric(),
(("label1", "value1"), ),
SumAggregator(),
Resource.create_empty(),
)
metric_descriptor = exporter._get_metric_descriptor(record)
client.create_metric_descriptor.assert_called_with(
self.project_name,
MetricDescriptor(
**{
"name": None,
"type": "custom.googleapis.com/OpenTelemetry/name",
"display_name": "name",
"description": "description",
"labels":
[LabelDescriptor(key="label1", value_type="STRING")],
"metric_kind": "CUMULATIVE",
"value_type": "INT64",
}),
)
# Getting a cached metric descriptor shouldn't use another call
cached_metric_descriptor = exporter._get_metric_descriptor(record)
self.assertEqual(client.create_metric_descriptor.call_count, 1)
self.assertEqual(metric_descriptor, cached_metric_descriptor)
# Drop labels with values that aren't string, int or bool
exporter._get_metric_descriptor(
ExportRecord(
MockMetric(name="name2", value_type=float),
(
("label1", "value1"),
("label2", dict()),
("label3", 3),
("label4", False),
),
SumAggregator(),
Resource.create_empty(),
))
client.create_metric_descriptor.assert_called_with(
self.project_name,
MetricDescriptor(
**{
"name":
None,
"type":
"custom.googleapis.com/OpenTelemetry/name2",
"display_name":
"name2",
"description":
"description",
"labels": [
LabelDescriptor(key="label1", value_type="STRING"),
LabelDescriptor(key="label3", value_type="INT64"),
LabelDescriptor(key="label4", value_type="BOOL"),
],
"metric_kind":
"CUMULATIVE",
"value_type":
"DOUBLE",
}),
)
def test_extract_empty_resources(self):
self.assertEqual(_extract_resources(Resource.create_empty()), {})
def test_export(self):
client = mock.Mock()
with mock.patch(
"opentelemetry.exporter.cloud_monitoring.time_ns",
lambda: NANOS_PER_SECOND,
):
exporter = CloudMonitoringMetricsExporter(
project_id=self.project_id, client=client)
exporter.project_name = self.project_name
exporter.export([
ExportRecord(
MockMetric(),
(("label1", "value1"), ),
UnsupportedAggregator(),
Resource.create_empty(),
)
])
client.create_time_series.assert_not_called()
client.create_metric_descriptor.return_value = MetricDescriptor(
**{
"name":
None,
"type":
"custom.googleapis.com/OpenTelemetry/name",
"display_name":
"name",
"description":
"description",
"labels": [
LabelDescriptor(key="label1", value_type="STRING"),
LabelDescriptor(key="label2", value_type="INT64"),
],
"metric_kind":
"CUMULATIVE",
"value_type":
"DOUBLE",
})
resource = Resource(
attributes={
"cloud.account.id": 123,
"host.id": "host",
"cloud.zone": "US",
"cloud.provider": "gcp",
"extra_info": "extra",
"gcp.resource_type": "gce_instance",
"not_gcp_resource": "value",
})
sum_agg_one = SumAggregator()
sum_agg_one.checkpoint = 1
sum_agg_one.last_update_timestamp = (WRITE_INTERVAL +
1) * NANOS_PER_SECOND
exporter.export([
ExportRecord(
MockMetric(meter=mock_meter()),
(
("label1", "value1"),
("label2", 1),
),
sum_agg_one,
resource,
),
ExportRecord(
MockMetric(meter=mock_meter()),
(
("label1", "value2"),
("label2", 2),
),
sum_agg_one,
resource,
),
])
expected_resource = MonitoredResource(
type="gce_instance",
labels={
"project_id": "123",
"instance_id": "host",
"zone": "US"
},
)
series1 = TimeSeries(resource=expected_resource)
series1.metric_kind = MetricDescriptor.MetricKind.CUMULATIVE
series1.metric.type = "custom.googleapis.com/OpenTelemetry/name"
series1.metric.labels["label1"] = "value1"
series1.metric.labels["label2"] = "1"
point = series1.points.add()
point.value.int64_value = 1
point.interval.end_time.seconds = WRITE_INTERVAL + 1
point.interval.end_time.nanos = 0
point.interval.start_time.seconds = 1
point.interval.start_time.nanos = 0
series2 = TimeSeries(resource=expected_resource)
series2.metric_kind = MetricDescriptor.MetricKind.CUMULATIVE
series2.metric.type = "custom.googleapis.com/OpenTelemetry/name"
series2.metric.labels["label1"] = "value2"
series2.metric.labels["label2"] = "2"
point = series2.points.add()
point.value.int64_value = 1
point.interval.end_time.seconds = WRITE_INTERVAL + 1
point.interval.end_time.nanos = 0
point.interval.start_time.seconds = 1
point.interval.start_time.nanos = 0
client.create_time_series.assert_has_calls(
[mock.call(self.project_name, [series1, series2])])
# Attempting to export too soon after another export with the exact
# same labels leads to it being dropped
sum_agg_two = SumAggregator()
sum_agg_two.checkpoint = 1
sum_agg_two.last_update_timestamp = (WRITE_INTERVAL +
2) * NANOS_PER_SECOND
exporter.export([
ExportRecord(
MockMetric(),
(
("label1", "value1"),
("label2", 1),
),
sum_agg_two,
Resource.create_empty(),
),
ExportRecord(
MockMetric(),
(
("label1", "value2"),
("label2", 2),
),
sum_agg_two,
Resource.create_empty(),
),
])
self.assertEqual(client.create_time_series.call_count, 1)
# But exporting with different labels is fine
sum_agg_two.checkpoint = 2
exporter.export([
ExportRecord(
MockMetric(),
(
("label1", "changed_label"),
("label2", 2),
),
sum_agg_two,
Resource.create_empty(),
),
])
series3 = TimeSeries()
series3.metric_kind = MetricDescriptor.MetricKind.CUMULATIVE
series3.metric.type = "custom.googleapis.com/OpenTelemetry/name"
series3.metric.labels["label1"] = "changed_label"
series3.metric.labels["label2"] = "2"
point = series3.points.add()
point.value.int64_value = 2
point.interval.end_time.seconds = WRITE_INTERVAL + 2
point.interval.end_time.nanos = 0
point.interval.start_time.seconds = 1
point.interval.start_time.nanos = 0
client.create_time_series.assert_has_calls([
mock.call(self.project_name, [series1, series2]),
mock.call(self.project_name, [series3]),
])
def __init__(self, resource=Resource.create_empty(), stateful=True):
self.resource = resource
self.batcher = MockBatcher(stateful)
def __init__(
self, resource: Resource = Resource.create_empty(),
):
self.resource = resource
def test_export_histogram(self):
client = mock.Mock()
with mock.patch(
"opentelemetry.exporter.cloud_monitoring.time_ns",
lambda: NANOS_PER_SECOND,
):
exporter = CloudMonitoringMetricsExporter(
project_id=self.project_id, client=client)
exporter.project_name = self.project_name
client.create_metric_descriptor.return_value = MetricDescriptor(
**{
"name": None,
"type": "custom.googleapis.com/OpenTelemetry/name",
"display_name": "name",
"description": "description",
"labels": [],
"metric_kind": "CUMULATIVE",
"value_type": "DISTRIBUTION",
})
aggregator = HistogramAggregator(config={"bounds": [2, 4, 6]})
aggregator.checkpoint = OrderedDict([(2, 1), (4, 2), (6, 4), (">", 3)])
aggregator.last_update_timestamp = (WRITE_INTERVAL +
1) * NANOS_PER_SECOND
exporter.export([
ExportRecord(
MockMetric(meter=mock_meter()),
(),
aggregator,
Resource.create_empty(),
)
])
series = TimeSeries()
series.metric_kind = MetricDescriptor.MetricKind.CUMULATIVE
series.metric.type = "custom.googleapis.com/OpenTelemetry/name"
point = {
"interval": {
"start_time": {
"seconds": 1
},
"end_time": {
"seconds": 11
},
},
"value": {
"distribution_value": {
"count": 10,
"bucket_options": {
"explicit_buckets": {
"bounds": [2.0, 4.0, 6.0]
}
},
"bucket_counts": [1, 2, 4, 3],
}
},
}
series.points.add(**point)
client.create_time_series.assert_has_calls(
[mock.call(self.project_name, [series])])
def test_stateless_times(self):
client = mock.Mock()
with mock.patch(
"opentelemetry.exporter.cloud_monitoring.time_ns",
lambda: NANOS_PER_SECOND,
):
exporter = CloudMonitoringMetricsExporter(
project_id=self.project_id,
client=client,
)
client.create_metric_descriptor.return_value = MetricDescriptor(
**{
"name":
None,
"type":
"custom.googleapis.com/OpenTelemetry/name",
"display_name":
"name",
"description":
"description",
"labels": [
LabelDescriptor(key=UNIQUE_IDENTIFIER_KEY,
value_type="STRING"),
],
"metric_kind":
"CUMULATIVE",
"value_type":
"DOUBLE",
})
agg = SumAggregator()
agg.checkpoint = 1
agg.last_update_timestamp = (WRITE_INTERVAL + 1) * NANOS_PER_SECOND
metric_record = ExportRecord(MockMetric(stateful=False), (), agg,
Resource.create_empty())
exporter.export([metric_record])
exports_1 = client.create_time_series.call_args_list[0]
# verify the first metric started at exporter start time
self.assertEqual(
exports_1[0][1][0].points[0].interval.start_time.seconds, 1)
self.assertEqual(
exports_1[0][1][0].points[0].interval.start_time.nanos, 0)
self.assertEqual(
exports_1[0][1][0].points[0].interval.end_time.seconds,
WRITE_INTERVAL + 1,
)
agg.last_update_timestamp = (WRITE_INTERVAL * 2 + 2) * NANOS_PER_SECOND
metric_record = ExportRecord(MockMetric(stateful=False), (), agg,
Resource.create_empty())
exporter.export([metric_record])
exports_2 = client.create_time_series.call_args_list[1]
# 1ms ahead of end time of last export
self.assertEqual(
exports_2[0][1][0].points[0].interval.start_time.seconds,
WRITE_INTERVAL + 1,
)
self.assertEqual(
exports_2[0][1][0].points[0].interval.start_time.nanos, 1e6)
self.assertEqual(
exports_2[0][1][0].points[0].interval.end_time.seconds,
WRITE_INTERVAL * 2 + 2,
)
def test_checkpoint_set_empty(self):
processor = Processor(True, Resource.create_empty())
records = processor.checkpoint_set()
self.assertEqual(len(records), 0)
