chore(telemetry): code cleanup (#3897)

# What does this PR do?
Clean up telemetry code since the telemetry API has been remove.
- moved telemetry files out of providers to core
- removed from Api

## Test Plan

❯ OTEL_SERVICE_NAME=llama_stack
OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:4318 uv run llama stack run
starter
❯ curl http://localhost:8321/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "openai/gpt-4o-mini",
    "messages": [
      {
        "role": "user",
        "content": "Hello!"
      }
    ]
  }'

-> verify traces in Grafana

CI

llama_stack/providers/inline/agents/meta_reference/agent_instance.py

@@ -67,6 +67,7 @@ from llama_stack.apis.safety import Safety
 from llama_stack.apis.tools import ToolGroups, ToolInvocationResult, ToolRuntime
 from llama_stack.apis.vector_io import VectorIO
 from llama_stack.core.datatypes import AccessRule
+from llama_stack.core.telemetry import tracing
 from llama_stack.log import get_logger
 from llama_stack.models.llama.datatypes import (
     BuiltinTool,
@@ -78,7 +79,6 @@ from llama_stack.providers.utils.inference.openai_compat import (
     convert_tooldef_to_openai_tool,
 )
 from llama_stack.providers.utils.kvstore import KVStore
-from llama_stack.providers.utils.telemetry import tracing
 
 from .persistence import AgentPersistence
 from .safety import SafetyException, ShieldRunnerMixin

llama_stack/providers/inline/agents/meta_reference/responses/streaming.py

@@ -65,9 +65,9 @@ from llama_stack.apis.inference import (
     OpenAIChoice,
     OpenAIMessageParam,
 )
+from llama_stack.core.telemetry import tracing
 from llama_stack.log import get_logger
 from llama_stack.providers.utils.inference.prompt_adapter import interleaved_content_as_str
-from llama_stack.providers.utils.telemetry import tracing
 
 from .types import ChatCompletionContext, ChatCompletionResult
 from .utils import (

llama_stack/providers/inline/agents/meta_reference/responses/tool_executor.py

@@ -37,8 +37,8 @@ from llama_stack.apis.inference import (
 )
 from llama_stack.apis.tools import ToolGroups, ToolInvocationResult, ToolRuntime
 from llama_stack.apis.vector_io import VectorIO
+from llama_stack.core.telemetry import tracing
 from llama_stack.log import get_logger
-from llama_stack.providers.utils.telemetry import tracing
 
 from .types import ChatCompletionContext, ToolExecutionResult
 

llama_stack/providers/inline/agents/meta_reference/safety.py

@@ -8,8 +8,8 @@ import asyncio
 
 from llama_stack.apis.inference import Message
 from llama_stack.apis.safety import Safety, SafetyViolation, ViolationLevel
+from llama_stack.core.telemetry import tracing
 from llama_stack.log import get_logger
-from llama_stack.providers.utils.telemetry import tracing
 
 log = get_logger(name=__name__, category="agents::meta_reference")
 

llama_stack/providers/inline/telemetry/__init__.py

@@ -1,5 +0,0 @@
-# Copyright (c) Meta Platforms, Inc. and affiliates.
-# All rights reserved.
-#
-# This source code is licensed under the terms described in the LICENSE file in
-# the root directory of this source tree.

llama_stack/providers/inline/telemetry/meta_reference/__init__.py

@@ -1,21 +0,0 @@
-# Copyright (c) Meta Platforms, Inc. and affiliates.
-# All rights reserved.
-#
-# This source code is licensed under the terms described in the LICENSE file in
-# the root directory of this source tree.
-
-from typing import Any
-
-from llama_stack.core.datatypes import Api
-
-from .config import TelemetryConfig, TelemetrySink
-
-__all__ = ["TelemetryConfig", "TelemetrySink"]
-
-
-async def get_provider_impl(config: TelemetryConfig, deps: dict[Api, Any]):
-    from .telemetry import TelemetryAdapter
-
-    impl = TelemetryAdapter(config, deps)
-    await impl.initialize()
-    return impl

llama_stack/providers/inline/telemetry/meta_reference/config.py

@@ -1,47 +0,0 @@
-# Copyright (c) Meta Platforms, Inc. and affiliates.
-# All rights reserved.
-#
-# This source code is licensed under the terms described in the LICENSE file in
-# the root directory of this source tree.
-
-from enum import StrEnum
-from typing import Any
-
-from pydantic import BaseModel, Field, field_validator
-
-
-class TelemetrySink(StrEnum):
-    OTEL_TRACE = "otel_trace"
-    OTEL_METRIC = "otel_metric"
-    CONSOLE = "console"
-
-
-class TelemetryConfig(BaseModel):
-    otel_exporter_otlp_endpoint: str | None = Field(
-        default=None,
-        description="The OpenTelemetry collector endpoint URL (base URL for traces, metrics, and logs). If not set, the SDK will use OTEL_EXPORTER_OTLP_ENDPOINT environment variable.",
-    )
-    service_name: str = Field(
-        # service name is always the same, use zero-width space to avoid clutter
-        default="\u200b",
-        description="The service name to use for telemetry",
-    )
-    sinks: list[TelemetrySink] = Field(
-        default_factory=list,
-        description="List of telemetry sinks to enable (possible values: otel_trace, otel_metric, console)",
-    )
-
-    @field_validator("sinks", mode="before")
-    @classmethod
-    def validate_sinks(cls, v):
-        if isinstance(v, str):
-            return [TelemetrySink(sink.strip()) for sink in v.split(",")]
-        return v or []
-
-    @classmethod
-    def sample_run_config(cls, __distro_dir__: str) -> dict[str, Any]:
-        return {
-            "service_name": "${env.OTEL_SERVICE_NAME:=\u200b}",
-            "sinks": "${env.TELEMETRY_SINKS:=}",
-            "otel_exporter_otlp_endpoint": "${env.OTEL_EXPORTER_OTLP_ENDPOINT:=}",
-        }

llama_stack/providers/inline/telemetry/meta_reference/telemetry.py

@@ -1,252 +0,0 @@
-# Copyright (c) Meta Platforms, Inc. and affiliates.
-# All rights reserved.
-#
-# This source code is licensed under the terms described in the LICENSE file in
-# the root directory of this source tree.
-
-import os
-import threading
-from typing import Any
-
-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.export import PeriodicExportingMetricReader
-from opentelemetry.sdk.trace import TracerProvider
-from opentelemetry.sdk.trace.export import BatchSpanProcessor
-from opentelemetry.trace.propagation.tracecontext import TraceContextTextMapPropagator
-
-from llama_stack.apis.telemetry import (
-    Event,
-    MetricEvent,
-    SpanEndPayload,
-    SpanStartPayload,
-    SpanStatus,
-    StructuredLogEvent,
-    Telemetry,
-    UnstructuredLogEvent,
-)
-from llama_stack.core.datatypes import Api
-from llama_stack.log import get_logger
-from llama_stack.providers.utils.telemetry.tracing import ROOT_SPAN_MARKERS
-
-from .config import TelemetryConfig
-
-_GLOBAL_STORAGE: dict[str, dict[str | int, Any]] = {
-    "active_spans": {},
-    "counters": {},
-    "gauges": {},
-    "up_down_counters": {},
-}
-_global_lock = threading.Lock()
-_TRACER_PROVIDER = None
-
-logger = get_logger(name=__name__, category="telemetry")
-
-
-def is_tracing_enabled(tracer):
-    with tracer.start_as_current_span("check_tracing") as span:
-        return span.is_recording()
-
-
-class TelemetryAdapter(Telemetry):
-    def __init__(self, _config: TelemetryConfig, deps: dict[Api, Any]) -> None:
-        self.datasetio_api = deps.get(Api.datasetio)
-        self.meter = None
-
-        global _TRACER_PROVIDER
-        # Initialize the correct span processor based on the provider state.
-        # This is needed since once the span processor is set, it cannot be unset.
-        # Recreating the telemetry adapter multiple times will result in duplicate span processors.
-        # Since the library client can be recreated multiple times in a notebook,
-        # the kernel will hold on to the span processor and cause duplicate spans to be written.
-        if os.environ.get("OTEL_EXPORTER_OTLP_ENDPOINT"):
-            if _TRACER_PROVIDER is None:
-                provider = TracerProvider()
-                trace.set_tracer_provider(provider)
-                _TRACER_PROVIDER = provider
-
-                # Use single OTLP endpoint for all telemetry signals
-
-                # Let OpenTelemetry SDK handle endpoint construction automatically
-                # The SDK will read OTEL_EXPORTER_OTLP_ENDPOINT and construct appropriate URLs
-                # https://opentelemetry.io/docs/languages/sdk-configuration/otlp-exporter
-                span_exporter = OTLPSpanExporter()
-                span_processor = BatchSpanProcessor(span_exporter)
-                trace.get_tracer_provider().add_span_processor(span_processor)
-
-                metric_reader = PeriodicExportingMetricReader(OTLPMetricExporter())
-                metric_provider = MeterProvider(metric_readers=[metric_reader])
-                metrics.set_meter_provider(metric_provider)
-            self.is_otel_endpoint_set = True
-        else:
-            logger.warning("OTEL_EXPORTER_OTLP_ENDPOINT is not set, skipping telemetry")
-            self.is_otel_endpoint_set = False
-
-        self.meter = metrics.get_meter(__name__)
-        self._lock = _global_lock
-
-    async def initialize(self) -> None:
-        pass
-
-    async def shutdown(self) -> None:
-        if self.is_otel_endpoint_set:
-            trace.get_tracer_provider().force_flush()
-
-    async def log_event(self, event: Event, ttl_seconds: int = 604800) -> None:
-        if isinstance(event, UnstructuredLogEvent):
-            self._log_unstructured(event, ttl_seconds)
-        elif isinstance(event, MetricEvent):
-            self._log_metric(event)
-        elif isinstance(event, StructuredLogEvent):
-            self._log_structured(event, ttl_seconds)
-        else:
-            raise ValueError(f"Unknown event type: {event}")
-
-    def _log_unstructured(self, event: UnstructuredLogEvent, ttl_seconds: int) -> None:
-        with self._lock:
-            # Use global storage instead of instance storage
-            span_id = int(event.span_id, 16)
-            span = _GLOBAL_STORAGE["active_spans"].get(span_id)
-
-            if span:
-                timestamp_ns = int(event.timestamp.timestamp() * 1e9)
-                span.add_event(
-                    name=event.type.value,
-                    attributes={
-                        "message": event.message,
-                        "severity": event.severity.value,
-                        "__ttl__": ttl_seconds,
-                        **(event.attributes or {}),
-                    },
-                    timestamp=timestamp_ns,
-                )
-            else:
-                print(f"Warning: No active span found for span_id {span_id}. Dropping event: {event}")
-
-    def _get_or_create_counter(self, name: str, unit: str) -> metrics.Counter:
-        assert self.meter is not None
-        if name not in _GLOBAL_STORAGE["counters"]:
-            _GLOBAL_STORAGE["counters"][name] = self.meter.create_counter(
-                name=name,
-                unit=unit,
-                description=f"Counter for {name}",
-            )
-        return _GLOBAL_STORAGE["counters"][name]
-
-    def _get_or_create_gauge(self, name: str, unit: str) -> metrics.ObservableGauge:
-        assert self.meter is not None
-        if name not in _GLOBAL_STORAGE["gauges"]:
-            _GLOBAL_STORAGE["gauges"][name] = self.meter.create_gauge(
-                name=name,
-                unit=unit,
-                description=f"Gauge for {name}",
-            )
-        return _GLOBAL_STORAGE["gauges"][name]
-
-    def _log_metric(self, event: MetricEvent) -> None:
-        # Add metric as an event to the current span
-        try:
-            with self._lock:
-                # Only try to add to span if we have a valid span_id
-                if event.span_id:
-                    try:
-                        span_id = int(event.span_id, 16)
-                        span = _GLOBAL_STORAGE["active_spans"].get(span_id)
-
-                        if span:
-                            timestamp_ns = int(event.timestamp.timestamp() * 1e9)
-                            span.add_event(
-                                name=f"metric.{event.metric}",
-                                attributes={
-                                    "value": event.value,
-                                    "unit": event.unit,
-                                    **(event.attributes or {}),
-                                },
-                                timestamp=timestamp_ns,
-                            )
-                    except (ValueError, KeyError):
-                        # Invalid span_id or span not found, but we already logged to console above
-                        pass
-        except Exception:
-            # Lock acquisition failed
-            logger.debug("Failed to acquire lock to add metric to span")
-
-        # Log to OpenTelemetry meter if available
-        if self.meter is None:
-            return
-        if isinstance(event.value, int):
-            counter = self._get_or_create_counter(event.metric, event.unit)
-            counter.add(event.value, attributes=event.attributes)
-        elif isinstance(event.value, float):
-            up_down_counter = self._get_or_create_up_down_counter(event.metric, event.unit)
-            up_down_counter.add(event.value, attributes=event.attributes)
-
-    def _get_or_create_up_down_counter(self, name: str, unit: str) -> metrics.UpDownCounter:
-        assert self.meter is not None
-        if name not in _GLOBAL_STORAGE["up_down_counters"]:
-            _GLOBAL_STORAGE["up_down_counters"][name] = self.meter.create_up_down_counter(
-                name=name,
-                unit=unit,
-                description=f"UpDownCounter for {name}",
-            )
-        return _GLOBAL_STORAGE["up_down_counters"][name]
-
-    def _log_structured(self, event: StructuredLogEvent, ttl_seconds: int) -> None:
-        with self._lock:
-            span_id = int(event.span_id, 16)
-            tracer = trace.get_tracer(__name__)
-            if event.attributes is None:
-                event.attributes = {}
-            event.attributes["__ttl__"] = ttl_seconds
-
-            # Extract these W3C trace context attributes so they are not written to
-            # underlying storage, as we just need them to propagate the trace context.
-            traceparent = event.attributes.pop("traceparent", None)
-            tracestate = event.attributes.pop("tracestate", None)
-            if traceparent:
-                # If we have a traceparent header value, we're not the root span.
-                for root_attribute in ROOT_SPAN_MARKERS:
-                    event.attributes.pop(root_attribute, None)
-
-            if isinstance(event.payload, SpanStartPayload):
-                # Check if span already exists to prevent duplicates
-                if span_id in _GLOBAL_STORAGE["active_spans"]:
-                    return
-
-                context = None
-                if event.payload.parent_span_id:
-                    parent_span_id = int(event.payload.parent_span_id, 16)
-                    parent_span = _GLOBAL_STORAGE["active_spans"].get(parent_span_id)
-                    context = trace.set_span_in_context(parent_span)
-                elif traceparent:
-                    carrier = {
-                        "traceparent": traceparent,
-                        "tracestate": tracestate,
-                    }
-                    context = TraceContextTextMapPropagator().extract(carrier=carrier)
-
-                span = tracer.start_span(
-                    name=event.payload.name,
-                    context=context,
-                    attributes=event.attributes or {},
-                )
-                _GLOBAL_STORAGE["active_spans"][span_id] = span
-
-            elif isinstance(event.payload, SpanEndPayload):
-                span = _GLOBAL_STORAGE["active_spans"].get(span_id)
-                if span:
-                    if event.attributes:
-                        span.set_attributes(event.attributes)
-
-                    status = (
-                        trace.Status(status_code=trace.StatusCode.OK)
-                        if event.payload.status == SpanStatus.OK
-                        else trace.Status(status_code=trace.StatusCode.ERROR)
-                    )
-                    span.set_status(status)
-                    span.end()
-                    _GLOBAL_STORAGE["active_spans"].pop(span_id, None)
-            else:
-                raise ValueError(f"Unknown structured log event: {event}")