opentelemetry-go-contrib VS microservices-demo

While many programming languages provide robust support for Open Telemetry, this instance focuses on Golang. It's important to note that, in the current context, the logs SDK for Golang is not implemented. For future reference consult the list of supported languages and explore the Open Telemetry repositories. Always prioritize the main repository and its contrib repository, housing extensions and instrumentation libraries crucial to the Open Telemetry framework. Stay updated with the latest developments to ensure seamless integration and enhanced functionality.

It’s assumed that the instrumentation of each component has been completed, and the HTTP communication has also been instrumented by net/http auto instrumentation library.

Tracing, including context propagation, is easy to set up with REST or gRPC. You can instrument most important parts of your application with the contrib package. Some libraries like go-redis have their own otel features, which could be a promising trend in the future. There are some important gaps though; for example, you'll have to go third party for database/sql.

I see! Yeah, this is one where where otel-go is a lot harder to use, but it's something the SIG is looking at. A coworker of mine is helping drive a design that's sort of an "easy button" to configure all the things with the least-surprising defaults[0] and we're seeing how people like it in our SDK distribution that uses it[1]. I hope that sometime soon we'll have the design polished-up enough to get merged in. Like most OSS projects, it'll take some time but I'm confident we can get it done.

The main challenge is that there's a large variety of use cases to fulfill (e.g., someone wants custom context propagation, a custom span processor, and export over HTTP+json but not HTTP+protobuf) and today the answer to that is that you have to pull in all the libraries for all the things you need. It's a lot more energy you need to expend to get started with all of this than it needs to be.

As for logging support in the Go SDK, it's frozen mostly just due to lack of bandwidth and a need to finish what's already been started. Metrics have proven to be much more difficult and time-consuming to implement correctly across all languages, with Go being impacted harder than other languages (e.g., Python and .NET). I think you can expect logging integrations in the near-ish future though.

This is great feedback. I'll pass it on folks who haven't seen it. Thank you! And please feel free to file issues about all the things that rub you the wrong way

[0]: https://github.com/open-telemetry/opentelemetry-go-contrib/p...

[1]: https://github.com/honeycombio/honeycomb-opentelemetry-go

OpenTelemetry middleware for Gin

OpenTelemetry is the work-in-progress merge of OpenCensus and OpenTracing. It is still in early stages as of 2021. We are using its instrumentation libraries opentelemetry-go and [opentelemetry-go-contrib]https://github.com/open-telemetry/opentelemetry-go-contrib/) for our Go services.

Usually the span propagation is located in headers Here you can see an example https://github.com/open-telemetry/opentelemetry-go-contrib/blob/main/instrumentation/github.com/gin-gonic/gin/otelgin/gintrace.go

OpenTelemetry has specific instrumentation packages to support popular Golang packages and use cases. For example, this app uses the Gin framework for request routing. OpenTelemetry provides instrumentation package named otelgin to instrument the Gin framework which you need to import in your app. You can find the complete list of supported Golang packages by OpenTelemetry here.

Hi u/brofesor, Your understanding is correct. Though the library you mentioned is not official. I found an issue in the official repo regarding this https://github.com/open-telemetry/opentelemetry-go-contrib/issues/714

Here I described all my experiments: https://github.com/open-telemetry/opentelemetry-go-contrib/issues/746

You can check https://github.com/GoogleCloudPlatform/microservices-demo for Kubernetes show-casing

Skyramp provides a sample project, sample-microservices, which serves as an excellent starting point for demonstrating testing and mocking with a full-featured distributed application. The application is based on Google's Online Boutique repo, which is an e-commerce store consisting of 11 different microservices. The docker-compose-demo branch referenced above showcases how Skyramp can be seamlessly integrated with Docker Compose for testing microservices with no local setup required. You can also clone the repository and explore the structure of the microservices setup for your own purposes.

Our starting point is the hot-code-reload-demo branch in Skyramp's letsramp/sample-microservices GitHub repo. You can use your browser to navigate to the correct branch in the repo here. The sample-microservices repo contains a demo project based on GCP's Online Boutique with added support for REST and Thrift APIs. This sample e-commerce application is perfect for demonstrating cloud-native development and testing, including debugging with Hot Code Reload with Skyramp.

This blog features the Skyramp fork of Google’s popular cloud-native microservices demo app, Online Boutique. Online Boutique is a web-based e-commerce app containing microservices that mimic real-world services, such as a product catalog, shopping cart, ad service, recommendation service, payment service, and others. The services use gRPC APIs by default, but Skyramp has also added support for REST and Thrift APIs.

I'm planning to host this application: Google Microservices Demo (It's an online shop)

Well, what is considered "real" data here? Why couldn't you simply set up a managed k8s cluster with some prometheus monitoring and run the microservices-demo on it. There is even a synthetic load generator. You could purposefully add in specific kinds of faults into the working system, ones that are supported in metasploit so you can automate intrusions. Consider some goals for gaining access like: exfiltration, denial of service, ransomware. Then consider how you might detect such attacks purely from what you can read out of the prometheus time series data (eg. high egress traffic plus high req/s to redis might mean an exfiltration).

The microservices source code repository for this project is from this link; google-microservices-demo, containing 11 services we will deploy with this demo. Also, from the same repo, it was illustrated and visualized how these services are connected to each other including a 3rd party service for database - redis. Among the services, Frontend serves as an entrypoint for all the services receiving external requests from the browser. Meanwhile, the load generator deployment is optional, so in this demo we wouldn't bother deploying it.

This demo repo might be a good starting point: https://github.com/GoogleCloudPlatform/microservices-demo

OpenAPI and possibly developing reusable, versioned client libraries could help, but it's a major undertaking that gRPC makes redundant. I'd be tempted to use grpc-gateway even if I had to implement a REST API. Try looking into buf and monorepo structures for proto management, e.g. something like GoogleCloudPlatform/microservices-demo. For more thorough proto and grpc-gateway definition examples, see googleapis/googleapis.

I also just discovered Google Cloud's microservices-demo repository, which has some samples of how to set up otel observability and GCP-specific Go profiling on GCP. I wish I'd found it before setting up otel myself.