zipkin VS opentelemetry-dotnet

When choosing distributed tracing tools, considerations include your technology stack, business requirements, and monitoring complexity. Zipkin, SkyWalking, and OpenTelemetry are popular distributed tracing solutions, each with its unique features.

From the perspective of the realization of GraphQL infrastructure, the interesting direction is "Finding". How to find the problem? How to find the bottleneck of the system? Distributed Tracing System (DTS) will help answer this question. Distributed tracing is a method of observing requests as they propagate through distributed environments. In our scenario, we have dozens of subgraphs, gateway, and transport layer through which the request goes. We have several tools that can be used to detect the whole lifecycle of the request through the system, e.g. Jaeger, Zipkin or solutions that provided DTS as a part of the solution NewRelic.

Zipkin is a distributed tracing system used for tracking and analyzing how requests move through complex systems, especially in setups with many interconnected services, known as microservices.

Distributed Tracing: Middleware for distributed tracing like Jaeger and Zipkin helps monitor and trace requests as they flow through multiple microservices, aiding in debugging, performance optimization, and understanding the system's behavior.

For microservice tracing, you might want to look at Zipkin [0], or OpenTelemetry [1]

[0] https://zipkin.io/

I’ve not used a self-hosted solution before, but here’s one I found. https://zipkin.io/

> IMO the reason these vendors can and do charge so much is not because telemetry software is hard.

I always saw it as "they are charging for their polished UI/experience"

The UI of https://zipkin.io/ versus DataDog is kind of... not really in the same ballpark?

There are the zipkin https://zipkin.io/ and jaeger https://www.jaegertracing.io/ packages/components you can use both have quickstarts if you consider that to be a beginner's guide.

Zipkin, which was developed by Twitter, is an open source tool for distributed tracing that can also be used to troubleshoot latency issues in your application. While Zipkin is Java-based, py_zipkin is an implementation for Python.

open-telemetry/opentelemetry-dotnet: The OpenTelemetry .NET Client (github.com)

💡Good to know -- If you wish to export traces to Jaeger, you should use the AddJaegerExporter instead of the AddOtlpExporter. Visit the opentelemetry-dotnet repository to see how it's done.

We're going to use OpenTelemetry .NET SDK. Add following nuget dependencies to the project:

We instrument the application with the OpenTelemetry SDK and SqlClient instrumentation library for .NET. First, we add the following NuGet package references to the API’s project file:

It should be handled automatically by OpenTelemetry middlewares. Just look through documentation and samples https://github.com/open-telemetry/opentelemetry-dotnet

Besides that, the propagation fields (traceparent and tracestate) were added in the message header. In the last article, I said that the standard (in the Working Draft (WD) step of the w3c process) recommends to add the propagation fields in the application-properties section by the message publisher. For the current example, I chose to propagate that context in the message header even for AMQP calls as was done in the dotnet OpenTelemetry example. It's important to reinforce that Trace Context: AMQP protocol is not a W3C Recommendation yet. Take a look at the place where the propagation fields were added:

As long as the Azure Functions app knows the instrumentation key from an Application Insights instance, it traces almost everything. OpenTelemetry.NET is one of the Open Telemetry implementations, has recently released v1.0 for tracing. Both metrics and logging are close to GA. However, it doesn't work well with Azure Functions. Therefore, in this post, let's manually implement the tracing at the log level, which is sent to Application Insights.