microservices-demo VS buf

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.

The Buf CLI is a versatile tool designed for handling Protocol Buffers (Protobuf), a method of serializing structured data. It offers several key features, including managing Protobuf assets through the Buf Schema Registry (BSR), providing a linter to enforce optimal API design and structure, and a breaking change detector to maintain compatibility either in source code or at the wire level. Additionally, the Buf CLI includes a generator that activates plugins based on user-defined templates and a formatter to standardize the formatting of Protobuf files according to industry norms. It also integrates seamlessly with the Buf Schema Registry, supporting comprehensive dependency management.

We'll use the Buf CLI as an alternative to protoc so that we can save our generation configuration as YAML. Buf is compatible with protoc plugins.

Not so much anymore! Take a look at buf.build, it makes the whole thing notoriously easy :)

In my opinion it's a good idea, it's the architecture we use at work, and it works well for us. The main limitation to be aware of is that many PaaS don't support gRPC traffic (because of the proxies used). For example, DigitalOcean App Platform or Heroku if I remember correctly. If the way you want to host your backend is OK with HTTP/2 and gRPC traffic, then it's not a limitation. One way around this limitation is to use the gRPC-Web protocol, or the Connect protocol (https://connect.build/). Unfortunately, Dart's gRPC client does not support the gRPC-Web protocol outside the web platform. So for a mobile application, it's not usable at the moment. (If this PR were accepted, it would solve the issue: https://github.com/grpc/grpc-dart/pull/557.) As for Connect, no client is currently offered by Buf for Dart. Don't hesitate if you want to know more. That said, I'd advise you to use the Connect implementation for Go to implement your backend. Connect will enable your server to speak all three protocols (gRPC, gRPC-Web and Connect), which is very useful in the long term. What's more, the code is cleaner, and you benefit from official support for observability with OpenTelemetry. If you don't know Buf (the creators of Connect),I suggest you visit their website: https://buf.build/. :-) Good luck!

As mentioned in the intro, we are going to use Buf and Connect as our tools. We’ll start by installing the dependencies.

gRPC itself is quite nice, especially with buf which makes generating Go code much easier. The rest of the code was in a bad state. Unmaintained router packages, repository pattern without any actual benefit or a repository pattern.

The second big difference is that we now have auto-generated client and server stubs. For this task, I chose to use buf and the protobuf-ts plugin in order to generate idiomatic Typescript classes and objects. Not only do these classes describe the types we'll use in the server and client, but also includes the actual gRPC implementations used to serialize and send messages back and forth across the wire.

Our team has been using Buf (https://buf.build) recently, and they have a nice solution for schema dependency management.

I've found that https://buf.build/ is easier to use than protoc directly.

Consider checking out https://connect.build from https://buf.build. Supports a simpler protocol than grpc-web. Includes a js/ts client for frontend. Then you don’t necessarily need a rest layer, but could leverage the proxy your building.