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improve agent metrics integration test and cleanup fixtures

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- simplified test to use telemetry.query_metrics for verification
- test now validates actual queryable metrics data
- verified by query metrics functionality added in #3074
This commit is contained in:
skamenan7 2025-09-19 10:47:16 -04:00
parent 69b692af91
commit 8f0413e743
5 changed files with 406 additions and 208 deletions
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27
llama_stack/providers/inline/telemetry/meta_reference/telemetry.py
View file

@ -12,7 +12,9 @@ from opentelemetry import metrics, trace
from opentelemetry.exporter.otlp.proto.http.metric_exporter import OTLPMetricExporter
from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
from opentelemetry.sdk.metrics import MeterProvider
from opentelemetry.sdk.metrics._internal.aggregation import ExplicitBucketHistogramAggregation
from opentelemetry.sdk.metrics.export import PeriodicExportingMetricReader
from opentelemetry.sdk.metrics.view import View
from opentelemetry.sdk.resources import Resource
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import BatchSpanProcessor
@ -110,7 +112,17 @@ class TelemetryAdapter(TelemetryDatasetMixin, Telemetry):
if TelemetrySink.OTEL_METRIC in self.config.sinks:
metric_reader = PeriodicExportingMetricReader(OTLPMetricExporter())
metric_provider = MeterProvider(resource=resource, metric_readers=[metric_reader])
# decent default buckets for agent workflow timings
hist_buckets = [0.1, 0.5, 1.0, 2.5, 5.0, 10.0, 25.0, 50.0, 100.0]
views = [
View(
instrument_type=metrics.Histogram,
aggregation=ExplicitBucketHistogramAggregation(boundaries=hist_buckets),
)
]
metric_provider = MeterProvider(resource=resource, metric_readers=[metric_reader], views=views)
metrics.set_meter_provider(metric_provider)
if TelemetrySink.SQLITE in self.config.sinks:
@ -140,8 +152,6 @@ class TelemetryAdapter(TelemetryDatasetMixin, Telemetry):
self._log_metric(event)
elif isinstance(event, StructuredLogEvent):
self._log_structured(event, ttl_seconds)
else:
raise ValueError(f"Unknown event type: {event}")
async def query_metrics(
self,
@ -211,7 +221,7 @@ class TelemetryAdapter(TelemetryDatasetMixin, Telemetry):
_GLOBAL_STORAGE["counters"][name] = self.meter.create_counter(
name=name,
unit=unit,
description=f"Counter for {name}",
description=name.replace("_", " "),
)
return _GLOBAL_STORAGE["counters"][name]
@ -221,7 +231,7 @@ class TelemetryAdapter(TelemetryDatasetMixin, Telemetry):
_GLOBAL_STORAGE["gauges"][name] = self.meter.create_gauge(
name=name,
unit=unit,
description=f"Gauge for {name}",
description=name.replace("_", " "),
)
return _GLOBAL_STORAGE["gauges"][name]
@ -265,7 +275,6 @@ class TelemetryAdapter(TelemetryDatasetMixin, Telemetry):
histogram = self._get_or_create_histogram(
event.metric,
event.unit,
[0.1, 0.5, 1.0, 2.5, 5.0, 10.0, 25.0, 50.0, 100.0],
)
histogram.record(event.value, attributes=event.attributes)
elif event.metric_type == MetricType.UP_DOWN_COUNTER:
@ -281,17 +290,17 @@ class TelemetryAdapter(TelemetryDatasetMixin, Telemetry):
_GLOBAL_STORAGE["up_down_counters"][name] = self.meter.create_up_down_counter(
name=name,
unit=unit,
description=f"UpDownCounter for {name}",
description=name.replace("_", " "),
)
return _GLOBAL_STORAGE["up_down_counters"][name]
def _get_or_create_histogram(self, name: str, unit: str, buckets: list[float] | None = None) -> metrics.Histogram:
def _get_or_create_histogram(self, name: str, unit: str) -> metrics.Histogram:
assert self.meter is not None
if name not in _GLOBAL_STORAGE["histograms"]:
_GLOBAL_STORAGE["histograms"][name] = self.meter.create_histogram(
name=name,
unit=unit,
description=f"Histogram for {name}",
description=name.replace("_", " "),
)
return _GLOBAL_STORAGE["histograms"][name]