trace-context-w3c VS ASP.NET Core

The answer is Context Propagation. The HTTP example is a classic and W3C even covers it. The propagation is adding the important fields from the context into the HTTP headers and having the other application extract those values and inject them into its trace context. This concept applies to any other way of communication. Here, we will focus on message brokers and how you can achieve context propagation for those.

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/

-- https://www.w3.org/TR/trace-context/

For context propagation, why not just reuse the existing trace context that most frameworks and toolkits generate for http requests? I've had to apply some elbow grease to get it play nice but once it does you're able to use tools like Jeager, etc as part of your asynchronous flow as well.

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

World Wide Web Consortium (W3C) has recommendations on the format of trace contexts. The aim is to develop a standardized format of passing trace context over standard protocols like HTTP. It saves a lot of time in distributed tracing implementation and ensures interoperability between various tracing tools.

The main objective is to propagate a message with traceparent id throw two APIs and one worker using W3C trace context standard. The first-api calls the second-api by a http call while the second-api has an asynchronous communication with the worker by a message broker (rabbitmq was chosen for that). Furthermore, zipkin was the trace system chosen (or vendor as the standard call it), being responsible for getting the application traces and building the distributed tracing diagram:

> Just .GetAwaiter().GetResult() it.

That won’t work with various synchronization contexts, where doing this would cause a deadlock. There’s not much fun in trying to debug such issues.

And now that various libraries only provide async api, or worse an non-async version wrapping the async one with . GetAwaiter().GetResult(), you’ll be in for a treat updating your dependencies.

Async all the way is the answer, although various frameworks still don’t offer async hooks. Recently I ran into this for example trying to write an async validator in blazor, but that’s not possible and you have to work around it [1].

C# 5 introduced async/await almost 12 years ago. And we’re still not “async all the way”.

[1]: https://github.com/dotnet/aspnetcore/issues/40244

This approach to organizing middleware enhances code readability, maintainability, and reusability. By following this encapsulation pattern, you're adhering to best practices in ASP.NET Core development, ensuring your application remains well-organized and scalable.

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https://github.com/dotnet/aspnetcore/issues/50643

Even if you look at Microsoft’s by far most popular GitHub project, they’re still only half as big as SupaBase. If you believe “the SupaBase story”, SupaBase grew and became twice as large as Microsoft in 3 years. Below is their likes over time if you’re curious, together with a couple of additional “too good to be true” Silicon Valley projects.

https://github.com/dotnet/aspnetcore/issues/10117

To achieve these objectives, we will take inspiration from ASP.NET Core Identity's PasswordHasher class. It incorporates a concept of hash versioning, allowing only the number of iterations to be modified.

yes I watched several courses, may be aim not getting clearly. but i worked with asp.net which uses http call and firebase cloud function also which uses socket connection, for socket connection its makes sense to use observable bcoz there streams of data we can observe once the connection establish ,but for http it need to be call every time.