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_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_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]),
])