Book Image

gRPC Go for Professionals

By : Clément Jean
Book Image

gRPC Go for Professionals

By: Clément Jean

Overview of this book

In recent years, the popularity of microservice architecture has surged, bringing forth a new set of requirements. Among these, efficient communication between the different services takes center stage, and that's where gRPC shines. This book will take you through creating gRPC servers and clients in an efficient, secure, and scalable way. However, communication is just one aspect of microservices, so this book goes beyond that to show you how to deploy your application on Kubernetes and configure other tools that are needed for making your application more resilient. With these tools at your disposal, you’ll be ready to get started with using gRPC in a microservice architecture. In gRPC Go for Professionals, you'll explore core concepts such as message transmission and the role of Protobuf in serialization and deserialization. Through a step-by-step implementation of a TODO list API, you’ll see the different features of gRPC in action. You’ll then learn different approaches for testing your services and debugging your API endpoints. Finally, you’ll get to grips with deploying the application services via Docker images and Kubernetes.
Table of Contents (13 chapters)
10
Epilogue

Summary

In this chapter, we looked at the key features that we can get by using community projects such as protoc-gen-validate or go-grpc-middleware. We saw that we can encode request validation logic in our proto files. This makes our code less bloated and provides error message consistency across all the endpoints of our API.

Then, we looked at what middleware are and how to create one. We started with refactoring our authentication and logging interceptors. We saw that by using go-grpc-middleware, we can focus only on the actual logic of the interceptor and have less boilerplate to deal with.

After that, we saw that we can expose tracing data from our API. We used OpenTelemetry and Prometheus to gather the data from the gRPC API and expose it through an HTTP server.

We then learned how to apply rate limiting on our APIs. This is helpful to prevent fraudulent actors or defective clients from overloading our server. We used the Token Bucket algorithm and an already existing...