llama-stack/llama_stack/providers/remote/telemetry/opentelemetry/opentelemetry.py
Dinesh Yeduguru 501e7c9d64
Fix opentelemetry adapter (#510)
# What does this PR do?

This PR fixes some of the issues with our telemetry setup to enable logs
to be delivered to opentelemetry and jaeger. Main fixes
1) Updates the open telemetry provider to use the latest oltp exports
instead of deprected ones.
2) Adds a tracing middleware, which injects traces into each HTTP
request that the server recieves and this is going to be the root trace.
Previously, we did this in the create_dynamic_route method, which is
actually not the actual exectuion flow, but more of a config and this
causes the traces to end prematurely. Through middleware, we plugin the
trace start and end at the right location.
3) We manage our own methods to create traces and spans and this does
not fit well with Opentelemetry SDK since it does not support provide a
way to take in traces and spans that are already created. it expects us
to use the SDK to create them. For now, I have a hacky approach of just
maintaining a map from our internal telemetry objects to the open
telemetry specfic ones. This is not the ideal solution. I will explore
other ways to get around this issue. for now, to have something that
works, i am going to keep this as is.

Addresses: #509
2024-11-22 18:18:11 -08:00

208 lines
7.9 KiB
Python

# 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 threading
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.resources import Resource
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import BatchSpanProcessor
from opentelemetry.semconv.resource import ResourceAttributes
from llama_stack.apis.telemetry import * # noqa: F403
from .config import OpenTelemetryConfig
_GLOBAL_STORAGE = {
"active_spans": {},
"counters": {},
"gauges": {},
"up_down_counters": {},
}
_global_lock = threading.Lock()
def string_to_trace_id(s: str) -> int:
# Convert the string to bytes and then to an integer
return int.from_bytes(s.encode(), byteorder="big", signed=False)
def string_to_span_id(s: str) -> int:
# Use only the first 8 bytes (64 bits) for span ID
return int.from_bytes(s.encode()[:8], byteorder="big", signed=False)
def is_tracing_enabled(tracer):
with tracer.start_as_current_span("check_tracing") as span:
return span.is_recording()
class OpenTelemetryAdapter(Telemetry):
def __init__(self, config: OpenTelemetryConfig):
self.config = config
resource = Resource.create(
{
ResourceAttributes.SERVICE_NAME: self.config.service_name,
}
)
provider = TracerProvider(resource=resource)
trace.set_tracer_provider(provider)
otlp_exporter = OTLPSpanExporter(
endpoint=self.config.otel_endpoint,
)
span_processor = BatchSpanProcessor(otlp_exporter)
trace.get_tracer_provider().add_span_processor(span_processor)
# Set up metrics
metric_reader = PeriodicExportingMetricReader(
OTLPMetricExporter(
endpoint=self.config.otel_endpoint,
)
)
metric_provider = MeterProvider(
resource=resource, metric_readers=[metric_reader]
)
metrics.set_meter_provider(metric_provider)
self.meter = metrics.get_meter(__name__)
self._lock = _global_lock
async def initialize(self) -> None:
pass
async def shutdown(self) -> None:
trace.get_tracer_provider().force_flush()
trace.get_tracer_provider().shutdown()
metrics.get_meter_provider().shutdown()
async def log_event(self, event: Event) -> None:
if isinstance(event, UnstructuredLogEvent):
self._log_unstructured(event)
elif isinstance(event, MetricEvent):
self._log_metric(event)
elif isinstance(event, StructuredLogEvent):
self._log_structured(event)
def _log_unstructured(self, event: UnstructuredLogEvent) -> None:
with self._lock:
# Use global storage instead of instance storage
span_id = string_to_span_id(event.span_id)
span = _GLOBAL_STORAGE["active_spans"].get(span_id)
if span:
timestamp_ns = int(event.timestamp.timestamp() * 1e9)
span.add_event(
name=event.type,
attributes={
"message": event.message,
"severity": event.severity.value,
**event.attributes,
},
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:
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:
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:
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:
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) -> None:
with self._lock:
span_id = string_to_span_id(event.span_id)
trace_id = string_to_trace_id(event.trace_id)
tracer = trace.get_tracer(__name__)
if isinstance(event.payload, SpanStartPayload):
# Check if span already exists to prevent duplicates
if span_id in _GLOBAL_STORAGE["active_spans"]:
return
parent_span = None
if event.payload.parent_span_id:
parent_span_id = string_to_span_id(event.payload.parent_span_id)
parent_span = _GLOBAL_STORAGE["active_spans"].get(parent_span_id)
# Create a new trace context with the trace_id
context = trace.Context(trace_id=trace_id)
if parent_span:
context = trace.set_span_in_context(parent_span, context)
span = tracer.start_span(
name=event.payload.name,
context=context,
attributes=event.attributes or {},
start_time=int(event.timestamp.timestamp() * 1e9),
)
_GLOBAL_STORAGE["active_spans"][span_id] = span
# Set as current span using context manager
with trace.use_span(span, end_on_exit=False):
pass # Let the span continue beyond this block
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(end_time=int(event.timestamp.timestamp() * 1e9))
# Remove from active spans
_GLOBAL_STORAGE["active_spans"].pop(span_id, None)
async def get_trace(self, trace_id: str) -> Trace:
raise NotImplementedError("Trace retrieval not implemented yet")