.NET Runtime VS trace-context-w3c

These can also be passed as arguments to `dotnet publish` if necessary.

Reference:

- https://learn.microsoft.com/en-us/dotnet/core/deploying/nati...

- https://github.com/dotnet/runtime/blob/main/src/coreclr/nati...

- https://github.com/dotnet/runtime/blob/5b4e770daa190ce69f402... (full list of recognized keys for IlcInstructionSet)

Yes, that is true. I'm not sure about JVM implementation details but the reason the comment says "virtual and interface" calls is to outline the difference. Virtual calls in .NET are sufficiently close[0] to virtual calls in C++. Interface calls, however, are coded differently[1].

Also you are correct - virtual calls are not terribly expensive, but they encroach on ever limited* CPU resources like indirect jump and load predictors and, as noted in parent comments, block inlining, which is highly undesirable for small and frequently called methods, particularly when they are in a loop.

* through great effort of our industry to take back whatever performance wins each generation brings with even more abstractions that fail to improve our productivity

[0] https://github.com/dotnet/coreclr/blob/4895a06c/src/vm/amd64...

[1] https://github.com/dotnet/runtime/blob/main/docs/design/core... (mind you, the text was initially written 18 ago, wow)

If you care about portable SIMD and performance, you may want to save yourself trouble and skip to C# instead, it also has an extensive guide to using it: https://github.com/dotnet/runtime/blob/69110bfdcf5590db1d32c...

CoreLib and many new libraries are using it heavily to match performance of manually intensified C++ code.

DEBUG: packageFiles with updates (repository=local) "config": { "nuget": [ { "deps": [ { "datasource": "nuget", "depType": "nuget", "depName": "Microsoft.Extensions.Hosting", "currentValue": "7.0.0", "updates": [ { "bucket": "non-major", "newVersion": "7.0.1", "newValue": "7.0.1", "releaseTimestamp": "2023-02-14T13:21:52.713Z", "newMajor": 7, "newMinor": 0, "updateType": "patch", "branchName": "renovate/dotnet-monorepo" }, { "bucket": "major", "newVersion": "8.0.0", "newValue": "8.0.0", "releaseTimestamp": "2023-11-14T13:23:17.653Z", "newMajor": 8, "newMinor": 0, "updateType": "major", "branchName": "renovate/major-dotnet-monorepo" } ], "packageName": "Microsoft.Extensions.Hosting", "versioning": "nuget", "warnings": [], "sourceUrl": "https://github.com/dotnet/runtime", "registryUrl": "https://api.nuget.org/v3/index.json", "homepage": "https://dot.net/", "currentVersion": "7.0.0", "isSingleVersion": true, "fixedVersion": "7.0.0" } ], "packageFile": "RenovateDemo.csproj" } ] }

https://github.com/dotnet/runtime/issues/59591

Support zstd Content-Encoding:

We might not be that far away already. There is this issue[1] on Github, where Microsoft and the community discuss some significant changes.

There is still a lot of questions unanswered, but initial tests look promising.

Ref: https://github.com/dotnet/runtime/issues/94620

https://github.com/dotnet/dotnet exists for source build that stitches together SDK, Roslyn, runtime and other dependencies. A lot of them can be built and used individually, which is what contributors usually do. For example, you can clone and build https://github.com/dotnet/runtime and use the produced artifacts to execute .NET assemblies or build .NET binaries.

Yeah, it kind of is. There are quite a few of experiments that are conducted to see if they show promise in the prototype form and then are taken further for proper integration if they do.

Unfortunately, object stack allocation was not one of them even though DOTNET_JitObjectStackAllocation configuration knob exists today, enabling it makes zero impact as it almost never kicks in. By the end of the experiment[0], it was concluded that before investing effort in this kind of feature becomes profitable given how a lot of C# code is written, there are many other lower hanging fruits.

To contrast this, in continuation to green threads experiment, a runtime handled tasks experiment[1] which moves async state machine handling from IL emitted by Roslyn to special-cased methods and then handling purely in runtime code has been a massive success and is now being worked on to be integrated in one of the future version of .NET (hopefully 10?)

[0] https://github.com/dotnet/runtime/issues/11192

[1] https://github.com/dotnet/runtimelab/blob/feature/async2-exp...

Orderby Linq Code Reference

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: