OpenTelemetry for Python

OpenTelemetry (OTel) is the observability framework for generating and collecting traces, metrics, and logs from distributed systems.

Signal Status

Installation

# Core packages
pip install opentelemetry-api opentelemetry-sdk

# Automatic instrumentation
pip install opentelemetry-distro
opentelemetry-bootstrap -a install

# OTLP exporters
pip install opentelemetry-exporter-otlp-proto-grpc

Complete SDK Setup

from opentelemetry import trace, metrics
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import BatchSpanProcessor
from opentelemetry.sdk.metrics import MeterProvider
from opentelemetry.sdk.metrics.export import PeriodicExportingMetricReader
from opentelemetry.sdk.resources import Resource, SERVICE_NAME, SERVICE_VERSION
from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import OTLPSpanExporter
from opentelemetry.exporter.otlp.proto.grpc.metric_exporter import OTLPMetricExporter
from opentelemetry.propagate import set_global_textmap
from opentelemetry.propagators.composite import CompositePropagator
from opentelemetry.trace.propagation.tracecontext import TraceContextTextMapPropagator
from opentelemetry.baggage.propagation import W3CBaggagePropagator

def setup_otel():
    resource = Resource.create({
        SERVICE_NAME: "my-service",
        SERVICE_VERSION: "1.0.0",
        "deployment.environment": "production",
    })

    set_global_textmap(CompositePropagator([
        TraceContextTextMapPropagator(),
        W3CBaggagePropagator(),
    ]))

    # TracerProvider
    trace_exporter = OTLPSpanExporter(endpoint="localhost:4317", insecure=True)
    trace_provider = TracerProvider(resource=resource)
    trace_provider.add_span_processor(BatchSpanProcessor(trace_exporter))
    trace.set_tracer_provider(trace_provider)

    # MeterProvider
    metric_exporter = OTLPMetricExporter(endpoint="localhost:4317", insecure=True)
    metric_reader = PeriodicExportingMetricReader(metric_exporter, export_interval_millis=30000)
    meter_provider = MeterProvider(resource=resource, metric_readers=[metric_reader])
    metrics.set_meter_provider(meter_provider)

    return trace_provider, meter_provider

def shutdown_otel(trace_provider, meter_provider):
    trace_provider.shutdown()
    meter_provider.shutdown()

Automatic Instrumentation

opentelemetry-instrument \
    --traces_exporter otlp \
    --metrics_exporter otlp \
    --logs_exporter otlp \
    --service_name my-service \
    python app.py

# Console export (development)
opentelemetry-instrument \
    --traces_exporter console \
    --service_name my-service \
    flask run -p 8080

Tracing

Creating Spans

from opentelemetry import trace

tracer = trace.get_tracer("my.app.tracer")

# Context manager
def process_request(request):
    with tracer.start_as_current_span("process-request") as span:
        span.set_attribute("request.id", request.id)
        return do_work(request)

# Decorator
@tracer.start_as_current_span("do_work")
def do_work(request):
    return "result"

Nested Spans

def parent_operation():
    with tracer.start_as_current_span("parent") as parent_span:
        child_operation()  # Automatically linked to parent

def child_operation():
    with tracer.start_as_current_span("child") as child_span:
        pass

Span Attributes

from opentelemetry.semconv.trace import SpanAttributes

span = trace.get_current_span()

# Custom attributes
span.set_attribute("user.id", "12345")
span.set_attribute("order.total", 99.99)

# Semantic conventions
span.set_attribute(SpanAttributes.HTTP_METHOD, "GET")
span.set_attribute(SpanAttributes.HTTP_STATUS_CODE, 200)
span.set_attribute(SpanAttributes.DB_SYSTEM, "postgresql")

Span Events

span = trace.get_current_span()
span.add_event("Cache lookup started")
span.add_event("Cache miss", {"cache.key": "user:123", "cache.type": "redis"})

Error Handling

from opentelemetry.trace import Status, StatusCode

span = trace.get_current_span()

try:
    result = risky_operation()
except Exception as ex:
    span.record_exception(ex)
    span.set_status(Status(StatusCode.ERROR, str(ex)))
    raise

span.set_status(Status(StatusCode.OK))

Manual Context Propagation

from opentelemetry.propagate import inject, extract

# Inject into headers (outgoing)
headers = {}
inject(headers)

# Extract from headers (incoming)
ctx = extract(headers)
with tracer.start_as_current_span("child", context=ctx) as span:
    pass

Metrics

Acquiring a Meter

from opentelemetry import metrics
meter = metrics.get_meter("my.app.meter")

Counter

request_counter = meter.create_counter(
    name="http.requests.total",
    description="Total HTTP requests",
    unit="1",
)

request_counter.add(1, {"http.method": "GET", "http.status_code": 200})

UpDown Counter

active_connections = meter.create_up_down_counter("connections.active")
active_connections.add(1)   # Connection opened
active_connections.add(-1)  # Connection closed

Histogram

request_duration = meter.create_histogram(
    name="http.request.duration",
    unit="s",
)

start = time.time()
# ... process ...
request_duration.record(time.time() - start, {"http.route": "/api/users"})

Observable Gauge (Async)

from opentelemetry.metrics import CallbackOptions, Observation

def get_memory_usage(options: CallbackOptions):
    import psutil
    mem = psutil.virtual_memory()
    yield Observation(mem.used, {"memory.type": "used"})

meter.create_observable_gauge(
    name="system.memory.usage",
    callbacks=[get_memory_usage],
    unit="By",
)

Framework Integration

Flask

from flask import Flask
from opentelemetry.instrumentation.flask import FlaskInstrumentor

app = Flask(__name__)
FlaskInstrumentor().instrument_app(app)

@app.route("/")
def index():
    return "Hello!"  # Automatic span created

FastAPI

from fastapi import FastAPI
from opentelemetry.instrumentation.fastapi import FastAPIInstrumentor

app = FastAPI()
FastAPIInstrumentor.instrument_app(app)

@app.get("/")
async def index():
    return {"message": "Hello!"}

Requests

from opentelemetry.instrumentation.requests import RequestsInstrumentor
RequestsInstrumentor().instrument()
# All requests.* calls now create spans

SQLAlchemy

from opentelemetry.instrumentation.sqlalchemy import SQLAlchemyInstrumentor
engine = create_engine("postgresql://...")
SQLAlchemyInstrumentor().instrument(engine=engine)

Exporters

OTLP

# gRPC
from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import OTLPSpanExporter
trace_exporter = OTLPSpanExporter(endpoint="localhost:4317", insecure=True)

# HTTP
from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
trace_exporter = OTLPSpanExporter(endpoint="http://localhost:4318/v1/traces")

Console

from opentelemetry.sdk.trace.export import ConsoleSpanExporter
trace_exporter = ConsoleSpanExporter()

Prometheus

from prometheus_client import start_http_server
from opentelemetry.exporter.prometheus import PrometheusMetricReader

start_http_server(port=8000)
reader = PrometheusMetricReader()
meter_provider = MeterProvider(metric_readers=[reader])

Environment Variables

export OTEL_SERVICE_NAME="my-service"
export OTEL_RESOURCE_ATTRIBUTES="service.version=1.0.0"
export OTEL_EXPORTER_OTLP_ENDPOINT="http://localhost:4317"
export OTEL_TRACES_EXPORTER="otlp"
export OTEL_METRICS_EXPORTER="otlp"
export OTEL_LOGS_EXPORTER="otlp"
export OTEL_TRACES_SAMPLER="parentbased_traceidratio"
export OTEL_TRACES_SAMPLER_ARG="0.1"
export OTEL_PYTHON_LOGGING_AUTO_INSTRUMENTATION_ENABLED="true"

Complete Flask Example

from flask import Flask, request
from opentelemetry import trace, metrics
from opentelemetry.instrumentation.flask import FlaskInstrumentor
import random
import time

tracer = trace.get_tracer("dice-roller")
meter = metrics.get_meter("dice-roller")

roll_counter = meter.create_counter("dice.rolls")
roll_histogram = meter.create_histogram("dice.roll.duration", unit="s")

app = Flask(__name__)
FlaskInstrumentor().instrument_app(app)

@app.route("/roll")
def roll_dice():
    player = request.args.get("player", "anonymous")

    with tracer.start_as_current_span("roll") as span:
        start = time.time()
        result = random.randint(1, 6)

        span.set_attribute("player.name", player)
        span.set_attribute("dice.result", result)

        roll_counter.add(1, {"player": player, "result": result})
        roll_histogram.record(time.time() - start, {"player": player})

        return {"player": player, "result": result}

if __name__ == "__main__":
    app.run(port=8080)

Best Practices

1. Use automatic instrumentation - Start with opentelemetry-instrument
2. Add manual spans - Enhance auto-instrumentation with business logic spans
3. Use semantic conventions - Import from opentelemetry.semconv
4. Batch exports - Use BatchSpanProcessor for production
5. Set service name - Always identify your service via resource attributes
6. Handle shutdown - Call shutdown() on providers for clean exit
7. Use context managers - Prefer with tracer.start_as_current_span()
8. Record exceptions - Use record_exception() AND set_status(ERROR)
9. Keep cardinality low - Avoid high-cardinality attribute values on metrics