mirror of
https://github.com/meta-llama/llama-stack.git
synced 2025-12-05 02:17:31 +00:00
metrics tests
- Add _create_metric_stub_from_protobuf method to correctly parse protobuf metrics - Add _extract_attributes_from_data_point helper method - Change metric handling to use protobuf-specific parsing instead of OpenTelemetry native parsing - Add missing typing import - Add OTEL_METRIC_EXPORT_INTERVAL environment variable for test configuration This fixes the CI failure where metrics were not being properly extracted from protobuf data in server mode tests.
This commit is contained in:
Emilio Garcia
Eric Huang
parent
415fd9e36b
commit
7a19488787
8 changed files with 420 additions and 125 deletions
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@ -6,20 +6,88 @@
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"""Shared helpers for telemetry test collectors."""
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import time
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from collections.abc import Iterable
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from dataclasses import dataclass
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from typing import Any
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@dataclass
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class SpanStub:
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class MetricStub:
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"""Unified metric interface for both in-memory and OTLP collectors."""
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name: str
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attributes: dict[str, Any]
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value: Any
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attributes: dict[str, Any] | None = None
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@dataclass
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class SpanStub:
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"""Unified span interface for both in-memory and OTLP collectors."""
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name: str
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attributes: dict[str, Any] | None = None
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resource_attributes: dict[str, Any] | None = None
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events: list[dict[str, Any]] | None = None
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trace_id: str | None = None
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span_id: str | None = None
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@property
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def context(self):
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"""Provide context-like interface for trace_id compatibility."""
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if self.trace_id is None:
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return None
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return type("Context", (), {"trace_id": int(self.trace_id, 16)})()
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def get_trace_id(self) -> str | None:
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"""Get trace ID in hex format.
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Tries context.trace_id first, then falls back to direct trace_id.
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"""
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context = getattr(self, "context", None)
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if context and getattr(context, "trace_id", None) is not None:
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return f"{context.trace_id:032x}"
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return getattr(self, "trace_id", None)
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def has_message(self, text: str) -> bool:
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"""Check if span contains a specific message in its args."""
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if self.attributes is None:
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return False
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args = self.attributes.get("__args__")
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if not args or not isinstance(args, str):
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return False
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return text in args
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def is_root_span(self) -> bool:
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"""Check if this is a root span."""
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if self.attributes is None:
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return False
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return self.attributes.get("__root__") is True
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def is_autotraced(self) -> bool:
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"""Check if this span was automatically traced."""
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if self.attributes is None:
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return False
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return self.attributes.get("__autotraced__") is True
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def get_span_type(self) -> str | None:
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"""Get the span type (async, sync, async_generator)."""
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if self.attributes is None:
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return None
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return self.attributes.get("__type__")
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def get_class_method(self) -> tuple[str | None, str | None]:
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"""Get the class and method names for autotraced spans."""
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if self.attributes is None:
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return None, None
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return (self.attributes.get("__class__"), self.attributes.get("__method__"))
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def get_location(self) -> str | None:
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"""Get the location (library_client, server) for root spans."""
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if self.attributes is None:
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return None
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return self.attributes.get("__location__")
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def _value_to_python(value: Any) -> Any:
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kind = value.WhichOneof("value")
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@ -56,14 +124,18 @@ def events_to_list(events: Iterable[Any]) -> list[dict[str, Any]]:
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class BaseTelemetryCollector:
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"""Base class for telemetry collectors that ensures consistent return types.
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All collectors must return SpanStub objects to ensure test compatibility
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across both library-client and server modes.
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"""
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def get_spans(
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self,
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expected_count: int | None = None,
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timeout: float = 5.0,
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poll_interval: float = 0.05,
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) -> tuple[Any, ...]:
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import time
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) -> tuple[SpanStub, ...]:
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deadline = time.time() + timeout
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min_count = expected_count if expected_count is not None else 1
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last_len: int | None = None
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@ -91,16 +163,206 @@ class BaseTelemetryCollector:
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last_len = len(spans)
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time.sleep(poll_interval)
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def get_metrics(self) -> Any | None:
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return self._snapshot_metrics()
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def get_metrics(
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self,
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expected_count: int | None = None,
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timeout: float = 5.0,
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poll_interval: float = 0.05,
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expect_model_id: str | None = None,
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) -> dict[str, MetricStub]:
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"""Get metrics with polling until metrics are available or timeout is reached."""
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# metrics need to be collected since get requests delete stored metrics
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deadline = time.time() + timeout
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min_count = expected_count if expected_count is not None else 1
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accumulated_metrics = {}
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count_metrics_with_model_id = 0
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while time.time() < deadline:
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current_metrics = self._snapshot_metrics()
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if current_metrics:
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for metric in current_metrics:
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metric_name = metric.name
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if metric_name not in accumulated_metrics:
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accumulated_metrics[metric_name] = metric
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if (
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expect_model_id
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and metric.attributes
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and metric.attributes.get("model_id") == expect_model_id
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):
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count_metrics_with_model_id += 1
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else:
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accumulated_metrics[metric_name] = metric
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# Check if we have enough metrics
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if len(accumulated_metrics) >= min_count:
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if not expect_model_id:
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return accumulated_metrics
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if count_metrics_with_model_id >= min_count:
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return accumulated_metrics
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time.sleep(poll_interval)
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return accumulated_metrics
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@staticmethod
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def _convert_attributes_to_dict(attrs: Any) -> dict[str, Any]:
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"""Convert various attribute types to a consistent dictionary format.
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Handles mappingproxy, dict, and other attribute types.
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"""
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if attrs is None:
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return {}
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try:
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return dict(attrs.items()) # type: ignore[attr-defined]
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except AttributeError:
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try:
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return dict(attrs)
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except TypeError:
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return dict(attrs) if attrs else {}
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@staticmethod
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def _extract_trace_span_ids(span: Any) -> tuple[str | None, str | None]:
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"""Extract trace_id and span_id from OpenTelemetry span object.
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Handles both context-based and direct attribute access.
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"""
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trace_id = None
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span_id = None
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context = getattr(span, "context", None)
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if context:
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trace_id = f"{context.trace_id:032x}"
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span_id = f"{context.span_id:016x}"
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else:
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trace_id = getattr(span, "trace_id", None)
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span_id = getattr(span, "span_id", None)
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return trace_id, span_id
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@staticmethod
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def _create_span_stub_from_opentelemetry(span: Any) -> SpanStub:
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"""Create SpanStub from OpenTelemetry span object.
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This helper reduces code duplication between collectors.
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"""
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trace_id, span_id = BaseTelemetryCollector._extract_trace_span_ids(span)
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attributes = BaseTelemetryCollector._convert_attributes_to_dict(span.attributes) or {}
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return SpanStub(
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name=span.name,
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attributes=attributes,
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trace_id=trace_id,
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span_id=span_id,
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)
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@staticmethod
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def _create_span_stub_from_protobuf(span: Any, resource_attrs: dict[str, Any] | None = None) -> SpanStub:
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"""Create SpanStub from protobuf span object.
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This helper handles the different structure of protobuf spans.
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"""
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attributes = attributes_to_dict(span.attributes) or {}
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events = events_to_list(span.events) if span.events else None
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trace_id = span.trace_id.hex() if span.trace_id else None
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span_id = span.span_id.hex() if span.span_id else None
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return SpanStub(
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name=span.name,
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attributes=attributes,
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resource_attributes=resource_attrs,
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events=events,
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trace_id=trace_id,
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span_id=span_id,
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)
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@staticmethod
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def _extract_metric_from_opentelemetry(metric: Any) -> MetricStub | None:
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"""Extract MetricStub from OpenTelemetry metric object.
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This helper reduces code duplication between collectors.
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"""
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if not (hasattr(metric, "name") and hasattr(metric, "data") and hasattr(metric.data, "data_points")):
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return None
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if not (metric.data.data_points and len(metric.data.data_points) > 0):
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return None
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# Get the value from the first data point
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data_point = metric.data.data_points[0]
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# Handle different metric types
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if hasattr(data_point, "value"):
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# Counter or Gauge
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value = data_point.value
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elif hasattr(data_point, "sum"):
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# Histogram - use the sum of all recorded values
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value = data_point.sum
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else:
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return None
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# Extract attributes if available
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attributes = {}
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if hasattr(data_point, "attributes"):
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attrs = data_point.attributes
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if attrs is not None and hasattr(attrs, "items"):
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attributes = dict(attrs.items())
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elif attrs is not None and not isinstance(attrs, dict):
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attributes = dict(attrs)
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return MetricStub(
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name=metric.name,
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value=value,
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attributes=attributes or {},
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)
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@staticmethod
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def _create_metric_stub_from_protobuf(metric: Any) -> MetricStub | None:
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"""Create MetricStub from protobuf metric object.
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Protobuf metrics have a different structure than OpenTelemetry metrics.
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They can have sum, gauge, or histogram data.
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"""
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if not hasattr(metric, "name"):
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return None
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# Try to extract value from different metric types
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for metric_type in ["sum", "gauge", "histogram"]:
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if hasattr(metric, metric_type):
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metric_data = getattr(metric, metric_type)
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if metric_data and hasattr(metric_data, "data_points"):
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data_points = metric_data.data_points
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if data_points and len(data_points) > 0:
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data_point = data_points[0]
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# Extract attributes first (needed for all metric types)
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attributes = (
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attributes_to_dict(data_point.attributes) if hasattr(data_point, "attributes") else {}
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)
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# Extract value based on metric type
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if metric_type == "sum":
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value = data_point.as_int
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elif metric_type == "gauge":
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value = data_point.as_double
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else: # histogram
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value = data_point.sum
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return MetricStub(
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name=metric.name,
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value=value,
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attributes=attributes,
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)
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return None
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def clear(self) -> None:
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self._clear_impl()
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def _snapshot_spans(self) -> tuple[Any, ...]: # pragma: no cover - interface hook
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def _snapshot_spans(self) -> tuple[SpanStub, ...]: # pragma: no cover - interface hook
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raise NotImplementedError
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def _snapshot_metrics(self) -> Any | None: # pragma: no cover - interface hook
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def _snapshot_metrics(self) -> tuple[MetricStub, ...] | None: # pragma: no cover - interface hook
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raise NotImplementedError
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def _clear_impl(self) -> None: # pragma: no cover - interface hook
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