Book Image

Hands-On RESTful Web Services with Go - Second Edition

By : Naren Yellavula
Book Image

Hands-On RESTful Web Services with Go - Second Edition

By: Naren Yellavula

Overview of this book

Building RESTful web services can be tough as there are countless standards and ways to develop API. In modern architectures such as microservices, RESTful APIs are common in communication, making idiomatic and scalable API development crucial. This book covers basic through to advanced API development concepts and supporting tools. You’ll start with an introduction to REST API development before moving on to building the essential blocks for working with Go. You’ll explore routers, middleware, and available open source web development solutions in Go to create robust APIs, and understand the application and database layers to build RESTful web services. You’ll learn various data formats like protocol buffers and JSON, and understand how to serve them over HTTP and gRPC. After covering advanced topics such as asynchronous API design and GraphQL for building scalable web services, you’ll discover how microservices can benefit from REST. You’ll also explore packaging artifacts in the form of containers and understand how to set up an ideal deployment ecosystem for web services. Finally, you’ll cover the provisioning of infrastructure using infrastructure as code (IaC) and secure your REST API. By the end of the book, you’ll have intermediate knowledge of web service development and be able to apply the skills you’ve learned in a practical way.
Table of Contents (16 chapters)

Delaying API jobs with queuing

In synchronous APIs, the blocking code plays a crucial role in preparing the response that is sent to the client. However, in the asynchronous design, non-blocking is key. A queue and workers can be helpful in achieving non-blocking code. A server can have multiple workers running in parallel who can exhaust the contents of a queue and work on them. Whenever a client requests an operation through an asynchronous API, the server can put that request in a job queue, and all the workers can pick up a task whenever their turn comes.

This approach can offload an API server and focus on its business logic instead of getting blocked on parallel/independent tasks such as sending emails, contacting third-party services, and so on.

A few use cases of queuing are as follows:

  • Compress images and email the final result
  • Automatic back pressuring (limiting the...