Book Image

Hands-On Software Engineering with Golang

By : Achilleas Anagnostopoulos
Book Image

Hands-On Software Engineering with Golang

By: Achilleas Anagnostopoulos

Overview of this book

Over the last few years, Go has become one of the favorite languages for building scalable and distributed systems. Its opinionated design and built-in concurrency features make it easy for engineers to author code that efficiently utilizes all available CPU cores. This Golang book distills industry best practices for writing lean Go code that is easy to test and maintain, and helps you to explore its practical implementation by creating a multi-tier application called Links ‘R’ Us from scratch. You’ll be guided through all the steps involved in designing, implementing, testing, deploying, and scaling an application. Starting with a monolithic architecture, you’ll iteratively transform the project into a service-oriented architecture (SOA) that supports the efficient out-of-core processing of large link graphs. You’ll learn about various cutting-edge and advanced software engineering techniques such as building extensible data processing pipelines, designing APIs using gRPC, and running distributed graph processing algorithms at scale. Finally, you’ll learn how to compile and package your Go services using Docker and automate their deployment to a Kubernetes cluster. By the end of this book, you’ll know how to think like a professional software developer or engineer and write lean and efficient Go code.
Table of Contents (21 chapters)
1
Section 1: Software Engineering and the Software Development Life Cycle
3
Section 2: Best Practices for Maintainable and Testable Go Code
7
Section 3: Designing and Building a Multi-Tier System from Scratch
14
Section 4: Scaling Out to Handle a Growing Number of Users
18
Epilogue

Understanding the need for a data layer abstraction

Before we delve deeper into modeling the data layer for the link graph and text indexer components, we need to spend some time discussing the reasoning behind the introduction of a data layer abstraction.

First and foremost, the primary purpose of the data layer is to decouple our code from the underlying data store implementation. By programming against a well-defined and data store-agnostic interface, we ensure that our code remains clean, modular, and totally oblivious to the nuances of accessing each data store.

An extra benefit of this approach is that it offers us the flexibility to A/B test different data store technologies before we decide which one to use for our production systems. What's more, even if our original decision proves to be less than stellar in the long term (for example, service traffic exceeds the...