Book Image

Building Microservices with Go

By : Nic Jackson
Book Image

Building Microservices with Go

By: Nic Jackson

Overview of this book

Microservice architecture is sweeping the world as the de facto pattern to build web-based applications. Golang is a language particularly well suited to building them. Its strong community, encouragement of idiomatic style, and statically-linked binary artifacts make integrating it with other technologies and managing microservices at scale consistent and intuitive. This book will teach you the common patterns and practices, showing you how to apply these using the Go programming language. It will teach you the fundamental concepts of architectural design and RESTful communication, and show you patterns that provide manageable code that is supportable in development and at scale in production. We will provide you with examples on how to put these concepts and patterns into practice with Go. Whether you are planning a new application or working in an existing monolith, this book will explain and illustrate with practical examples how teams of all sizes can start solving problems with microservices. It will help you understand Docker and Docker-Compose and how it can be used to isolate microservice dependencies and build environments. We finish off by showing you various techniques to monitor, test, and secure your microservices. By the end, you will know the benefits of system resilience of a microservice and the advantages of Go stack.
Table of Contents (18 chapters)
Title Page
Credits
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
Index

Types of asynchronous messages


Asynchronous processing often comes in two different forms, such as push and pull. The strategy that you implement is dependent upon your requirements, and often a single system implements both patterns. Let's take a look at the two different approaches.

Pull/queue messaging

The pull pattern is an excellent design where you may have a worker process running, for example, resizing images. The API would receive the request and then add this to a queue for background processing. The worker process or processes read from the queue, retrieve the messages one by one, perform the required work, and then delete the message from the queue. Often, there is also a queue commonly called a dead letter queue. Should the worker process fail for any reason, then the message would be added to the dead letter queue. The dead letter queue allows the messages to be re-processed in the case of an incremental failure or for debugging purposes. Let's take a look at the following diagram...