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

Questions

  1. What are the key differences between a relational database and a NoSQL database? Provide an example use case where a relational database would be a better fit than a NoSQL database and vice versa.
  2. How would you scale a relational database system for a read-heavy and a write-heavy workload?
  3. What is the CAP theorem and is it important when choosing which NoSQL implementation to use?
  1. Why is it important to provide an abstraction layer between our business logic and the underlying database?
  2. How would you go about adding a new method to the Indexer interface we discussed in the last part of this chapter?