opentelemetry-dotnet VS prometheus-net

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.

You might want to look into prometheus https://github.com/prometheus-net/prometheus-net, https://prometheus.io/.

You would need to build a custom endpoint if it's a custom application that Prometheus can scrape but there are many libraries for that like prom-client for NodeJS or prometheus-net for C#. The list of client libraries can be found here.

You could probably combine a HangFire Job Filter with the Prometheus C# library and log the things you want. Looks pretty extensible.

prometheus-net

I have a websocket server that hoards memory during days, till the point that Kubernetes eventually kills it. We monitor it using prometheous-net.

A library that makes this really easy for us is prometheus-net - we can create a minimal API that exposes metrics quickly and demonstrate a few different ways of creating metric data

// example taken from https://github.com/prometheus-net/prometheus-net#quick-start private static readonly Counter ProcessedJobCount = Metrics .CreateCounter("myapp_jobs_processed_total", "Number of processed jobs."); ... ProcessJob(); ProcessedJobCount.Inc();