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Hands-On Software Architecture with Golang

Hands-On Software Architecture with Golang

By : Raiturkar
4 (12)
close
Hands-On Software Architecture with Golang

Hands-On Software Architecture with Golang

4 (12)
By: Raiturkar

Overview of this book

Building software requires careful planning and architectural considerations; Golang was developed with a fresh perspective on building next-generation applications on the cloud with distributed and concurrent computing concerns. Hands-On Software Architecture with Golang starts with a brief introduction to architectural elements, Go, and a case study to demonstrate architectural principles. You'll then move on to look at code-level aspects such as modularity, class design, and constructs specific to Golang and implementation of design patterns. As you make your way through the chapters, you'll explore the core objectives of architecture such as effectively managing complexity, scalability, and reliability of software systems. You'll also work through creating distributed systems and their communication before moving on to modeling and scaling of data. In the concluding chapters, you'll learn to deploy architectures and plan the migration of applications from other languages. By the end of this book, you will have gained insight into various design and architectural patterns, which will enable you to create robust, scalable architecture using Golang.
Table of Contents (14 chapters)
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Scaling systems

It's now time to take a slightly higher-level view of scalability. Once we have written code and deployed it, how can we scale it?

The book The Art of Scalability (http://theartofscalability.com/), describes a really useful, three-dimensional scalability model in the form of a scale cube:

Each of the axes represents a specific way in which an application can be augmented to enable scalability in the face of increased load/traffic. They are described in the next sections.

X-axis scaling

Scaling along the x-axis means running multiple copies (instances) of the application behind a load balancer. If there are n instances, then each handles 1/n of the load. This is the simplest way of increasing scalability...

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