Distributed Tracing

# OpenTelemetry Configuration

from opentelemetry import trace
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import BatchSpanProcessor
from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import (
    OTLPSpanExporter
)
from opentelemetry.instrumentation.fastapi import FastAPIInstrumentor
from opentelemetry.instrumentation.httpx import HTTPXClientInstrumentor
from opentelemetry.instrumentation.sqlalchemy import SQLAlchemyInstrumentor
from opentelemetry.instrumentation.redis import RedisInstrumentor

# Configure provider
provider = TracerProvider(
    resource=Resource.create({
        "service.name": "justkalm-api",
        "service.version": "1.2.3",
        "deployment.environment": "production"
    })
)

# Configure exporter (Tempo/Jaeger)
exporter = OTLPSpanExporter(
    endpoint="http://tempo:4317",
    insecure=True
)
provider.add_span_processor(BatchSpanProcessor(exporter))
trace.set_tracer_provider(provider)

# Auto-instrument frameworks
FastAPIInstrumentor.instrument_app(app)
HTTPXClientInstrumentor().instrument()
SQLAlchemyInstrumentor().instrument(engine=engine)
RedisInstrumentor().instrument()

# Trace Context Propagation

# W3C Trace Context Headers
traceparent: 00-0af7651916cd43dd8448eb211c80319c-b7ad6b7169203331-01
tracestate: justkalm=eyJyZWdpb24iOiJ1cy1lYXN0LTEifQ

# Header breakdown
traceparent format:
  version-trace_id-parent_id-flags
  
  version:    00 (current version)
  trace_id:   0af7651916cd43dd8448eb211c80319c (128-bit)
  parent_id:  b7ad6b7169203331 (64-bit span ID)
  flags:      01 (sampled)

# Cross-service propagation
async def call_ml_service(product_id: str):
    tracer = trace.get_tracer(__name__)
    
    with tracer.start_as_current_span("ml_inference") as span:
        span.set_attribute("product.id", product_id)
        
        # Context automatically propagated
        async with httpx.AsyncClient() as client:
            response = await client.post(
                "http://ml-service/predict",
                json={"product_id": product_id}
            )
            
        span.set_attribute("ml.confidence", response.json()["confidence"])