Propagation
Propagation is the mechanism that moves data between services and processes. Although not limited to tracing, it is what allows traces to build causal information about a system across services that are arbitrarily distributed across process and network boundaries.
OpenTelemetry provides a text-based approach to propagate context to remote services using the W3C Trace Context HTTP headers.
Automatic context propagation
Instrumentation libraries for popular Python frameworks and libraries, such as Jinja2, Flask, Django, and Celery.propagate context across services for you.
Note
Use instrumentation libraries to propagate context. Although it is possible to propagate context manually, the Python auto-instrumentation and instrumentation libraries are well-tested and easier to use.Manual context propagation
The following generic example shows how you can propagate trace context manually.
First, on the sending service, inject the current context:
from flask import Flask
import requests
from opentelemetry import trace, propagators, baggage
from opentelemetry.trace.propagation.tracecontext import TraceContextTextMapPropagator
from opentelemetry.baggage.propagation import W3CBaggagePropagator
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import ConsoleSpanExporter, BatchSpanProcessor
app = Flask(__name__)
trace.set_tracer_provider(TracerProvider())
trace.get_tracer_provider().add_span_processor(BatchSpanProcessor(ConsoleSpanExporter()))
tracer = trace.get_tracer(__name__)
@app.route('/')
def hello():
with tracer.start_as_current_span("api1_span") as span:
ctx = baggage.set_baggage("hello", "world")
headers = {}
W3CBaggagePropagator().inject(headers, ctx)
TraceContextTextMapPropagator().inject(headers, ctx)
print(headers)
response = requests.get('http://127.0.0.1:5001/', headers=headers)
return f"Hello from API 1! Response from API 2: {response.text}"
if __name__ == '__main__':
app.run(port=5002)
On the receiving service, extract context, for example, from parsed HTTP
headers, and then set them as the current trace context.
from flask import Flask, request
from opentelemetry import trace, baggage
from opentelemetry.trace.propagation.tracecontext import TraceContextTextMapPropagator
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import ConsoleSpanExporter, BatchSpanProcessor
from opentelemetry.baggage.propagation import W3CBaggagePropagator
app = Flask(__name__)
trace.set_tracer_provider(TracerProvider())
trace.get_tracer_provider().add_span_processor(BatchSpanProcessor(ConsoleSpanExporter()))
tracer = trace.get_tracer(__name__)
@app.route('/')
def hello():
# Example: Log headers received in the request in API 2
headers = dict(request.headers)
print(f"Received headers: {headers}")
carrier ={'traceparent': headers['Traceparent']}
ctx = TraceContextTextMapPropagator().extract(carrier=carrier)
print(f"Received context: {ctx}")
b2 ={'baggage': headers['Baggage']}
ctx2 = W3CBaggagePropagator().extract(b2, context=ctx)
print(f"Received context2: {ctx2}")
# Start a new span
with tracer.start_span("api2_span", context=ctx2):
# Use propagated context
print(baggage.get_baggage('hello', ctx2))
return "Hello from API 2!"
if __name__ == '__main__':
app.run(port=5001)
From there, when you have a deserialized active context, you can create spans that are part of the same trace from the other service.
Next steps
To learn more about propagation, see Propagators API.
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