community VS b3-propagation

otel is working on their events spec https://github.com/open-telemetry/community/issues/1688

1. Agreed. It's the sink and the house attached to it, and the docs are thin and confusing as a result.

2. I had a similar experience to you. I wanted to implement a simple heartbeat in our app to get an idea of usage numbers. This is surprisingly not possible, which greatly confuses me given the name of the project. The low engagement on my question put me off and I abandoned my OpenTelemetry planning completely. [1][2]

[1] https://github.com/open-telemetry/community/discussions/1598

One of the OpenTelemetry Project's many Special Interest Groups (SIG) is the OpenTelemetry Community Demo SIG which gives support to a set of instrumented backend microservices and a web frontend app that are primarily used to showcase how to instrument a distributed system using OpenTelemetry. The application's main focus is to demonstrate the implementation process to instrument an application no matter what programming language, platform, or operating system your team is using, as well as providing different approaching techniques (automatic and manual instrumentation, metrics, baggage). All of this while following the standards and conventions defined by the official OpenTelemetry Documentation. More about the specific requirements can be found here. At Tracetest, we have always focused on becoming part of and embracing the OpenTelemetry community. One of our goals this summer was to get more involved with a core OpenTelemetry project where we could provide a meaningful contribution. The OTel demo became the best match for achieving that goal as it would not only help the community, but we at Tracetest needed a good example to test and showcase what can be done with our tool. During the version 0.7 project cycle, we created two specific tickets to get us closer to the community and start looking for things to pick up:

I've been playing with OTEL for a while, with a few backends like Jaeger and Zipkin, and am trying to figure out a way to perform end to end timing measurements across a graph of services triggered by any of several events.

Consider this scenario: There is a collection of services that talk to one another, and not all use HTTP. Say agent A0 makes a connection to agent A1, this is observed by service S0 which triggers service S1 to make calls to S2 and S3, which propagate elsewhere and return answers.

If we limit the scope of this problem to services explicitly making HTTP calls to other services, we can easily use the Propagators API [1] and use X-B3 headers [2] to propagate the trace context (trace ID, span ID, parent span ID) across this graph, from the origin through to the destination and back. This allows me to query the metrics collector (Jaeger or Zipkin) using this trace ID, look at the timestamps originating at the various services and do a T_end - T_start to determine the overall time taken by one call for a round trip across all the related services.

However, this breaks when a subset of these functions cannot propagate the B3 trace IDs for various reasons (e.g., a service is watching a specific state and acts when the state changes). I've been looking into OTEL and other related non-OTEL ways to capture metrics, but it appears there's not much research into this area though it does not seem like a unique or new problem.

Has anyone here looked at this scenario, and have you had any luck with OTEL or other mechanisms to get results?

[1] https://opentelemetry.io/docs/specs/otel/context/api-propaga...

[2] https://github.com/openzipkin/b3-propagation

[3] https://www.w3.org/TR/trace-context/

(Note that OpenTelemetry uses, by default, the W3C context propagation specification, while Istio uses the B3 context propagation specification – this can be modified).

The default format for context propagation is B3 so we use headers X-B3-TraceId and X-B3-SpanId