def test_export(self):
channel = grpc.insecure_channel(self.address)
transport = metric_service_grpc_transport.MetricServiceGrpcTransport(
channel=channel
)
client = MagicMock(wraps=MetricServiceClient(transport=transport))
exporter = CloudMonitoringMetricsExporter(
self.project_id, client=client
)
meter_provider = metrics.MeterProvider(
resource=Resource.create(
{
"cloud.account.id": "some_account_id",
"cloud.provider": "gcp",
"cloud.zone": "us-east1-b",
"host.id": 654321,
"gcp.resource_type": "gce_instance",
}
)
)
meter = meter_provider.get_meter(__name__)
counter = meter.create_counter(
# TODO: remove "opentelemetry/" prefix which is a hack
# https://github.com/GoogleCloudPlatform/opentelemetry-operations-python/issues/84
name="opentelemetry/name",
description="desc",
unit="1",
value_type=int,
)
# interval doesn't matter, we don't start the thread and just run
# tick() instead
controller = PushController(meter, exporter, 10)
counter.add(10, {"env": "test"})
with patch(
"opentelemetry.exporter.cloud_monitoring.logger"
) as mock_logger:
controller.tick()
# run tox tests with `-- -log-cli-level=0` to see mock calls made
logger.debug(client.create_time_series.mock_calls)
mock_logger.warning.assert_not_called()
mock_logger.error.assert_not_called()
CloudMonitoringMetricsExporter,
)
from opentelemetry.sdk.metrics import Counter, MeterProvider
from opentelemetry.sdk.resources import get_aggregated_resources
from opentelemetry.tools.resource_detector import GoogleCloudResourceDetector
# MUST be run on a Google tool!
# Detect resources from the environment
resources = get_aggregated_resources(
[GoogleCloudResourceDetector(raise_on_error=True)]
)
metrics.set_meter_provider(MeterProvider(resource=resources))
meter = metrics.get_meter(__name__)
metrics.get_meter_provider().start_pipeline(
meter, CloudMonitoringMetricsExporter(), 5
)
requests_counter = meter.create_metric(
name="request_counter_with_resource",
description="number of requests",
unit="1",
value_type=int,
metric_type=Counter,
)
staging_labels = {"environment": "staging"}
for i in range(20):
requests_counter.add(25, staging_labels)
time.sleep(10)
def test_constructor_default(self):
exporter = CloudMonitoringMetricsExporter(self.project_id)
self.assertEqual(exporter.project_id, self.project_id)
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 = MetricRecord(MockMetric(stateful=False), (), agg)
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 = MetricRecord(MockMetric(stateful=False), (), agg)
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_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(
[
MetricRecord(
MockMetric(),
(("label1", "value1"),),
UnsupportedAggregator(),
)
]
)
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(
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",
}
)
sum_agg_one = SumAggregator()
sum_agg_one.checkpoint = 1
sum_agg_one.last_update_timestamp = (
WRITE_INTERVAL + 1
) * NANOS_PER_SECOND
exporter.export(
[
MetricRecord(
MockMetric(meter=MockMeter(resource=resource)),
(("label1", "value1"), ("label2", 1),),
sum_agg_one,
),
MetricRecord(
MockMetric(meter=MockMeter(resource=resource)),
(("label1", "value2"), ("label2", 2),),
sum_agg_one,
),
]
)
expected_resource = MonitoredResource(
type="gce_instance",
labels={"project_id": "123", "instance_id": "host", "zone": "US"},
)
series1 = TimeSeries(resource=expected_resource)
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.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(
[
MetricRecord(
MockMetric(),
(("label1", "value1"), ("label2", 1),),
sum_agg_two,
),
MetricRecord(
MockMetric(),
(("label1", "value2"), ("label2", 2),),
sum_agg_two,
),
]
)
self.assertEqual(client.create_time_series.call_count, 1)
# But exporting with different labels is fine
sum_agg_two.checkpoint = 2
exporter.export(
[
MetricRecord(
MockMetric(),
(("label1", "changed_label"), ("label2", 2),),
sum_agg_two,
),
]
)
series3 = TimeSeries()
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 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(
MetricRecord(MockMetric(), (), UnsupportedAggregator())
)
)
record = MetricRecord(
MockMetric(), (("label1", "value1"),), SumAggregator(),
)
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(
MetricRecord(
MockMetric(name="name2", value_type=float),
(
("label1", "value1"),
("label2", dict()),
("label3", 3),
("label4", False),
),
SumAggregator(),
)
)
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_export(self):
client = mock.Mock()
exporter = CloudMonitoringMetricsExporter(
project_id=self.project_id, client=client
)
exporter.project_name = self.project_name
exporter.export(
[
MetricRecord(
MockMetric(),
(("label1", "value1"),),
UnsupportedAggregator(),
)
]
)
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": "GAUGE",
"value_type": "DOUBLE",
}
)
counter_one = CounterAggregator()
counter_one.checkpoint = 1
counter_one.last_update_timestamp = (WRITE_INTERVAL + 1) * 1e9
exporter.export(
[
MetricRecord(
MockMetric(),
(("label1", "value1"), ("label2", 1),),
counter_one,
),
MetricRecord(
MockMetric(),
(("label1", "value2"), ("label2", 2),),
counter_one,
),
]
)
series1 = TimeSeries()
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
series2 = TimeSeries()
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
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
counter_two = CounterAggregator()
counter_two.checkpoint = 1
counter_two.last_update_timestamp = (WRITE_INTERVAL + 2) * 1e9
exporter.export(
[
MetricRecord(
MockMetric(),
(("label1", "value1"), ("label2", 1),),
counter_two,
),
MetricRecord(
MockMetric(),
(("label1", "value2"), ("label2", 2),),
counter_two,
),
]
)
self.assertEqual(client.create_time_series.call_count, 1)
# But exporting with different labels is fine
counter_two.checkpoint = 2
exporter.export(
[
MetricRecord(
MockMetric(),
(("label1", "changed_label"), ("label2", 2),),
counter_two,
),
]
)
series3 = TimeSeries()
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
client.create_time_series.assert_has_calls(
[
mock.call(self.project_name, [series1, series2]),
mock.call(self.project_name, [series3]),
]
)
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])])