Book Image

Test-Driven Development in Go

By : Adelina Simion
Book Image

Test-Driven Development in Go

By: Adelina Simion

Overview of this book

Experienced developers understand the importance of designing a comprehensive testing strategy to ensure efficient shipping and maintaining services in production. This book shows you how to utilize test-driven development (TDD), a widely adopted industry practice, for testing your Go apps at different levels. You’ll also explore challenges faced in testing concurrent code, and learn how to leverage generics and write fuzz tests. The book begins by teaching you how to use TDD to tackle various problems, from simple mathematical functions to web apps. You’ll then learn how to structure and run your unit tests using Go’s standard testing library, and explore two popular testing frameworks, Testify and Ginkgo. You’ll also implement test suites using table-driven testing, a popular Go technique. As you advance, you’ll write and run behavior-driven development (BDD) tests using Ginkgo and Godog. Finally, you’ll explore the tricky aspects of implementing and testing TDD in production, such as refactoring your code and testing microservices architecture with contract testing implemented with Pact. All these techniques will be demonstrated using an example REST API, as well as smaller bespoke code examples. By the end of this book, you’ll have learned how to design and implement a comprehensive testing strategy for your Go applications and microservices architecture.
Table of Contents (18 chapters)
1
Part 1: The Big Picture
6
Part 2: Integration and End-to-End Testing with TDD
11
Part 3: Advanced Testing Techniques

Chapter 8, Testing Microservice Architectures

  1. Functional testing ensures that the features of the system work correctly. Non-functional testing verifies that other aspects of the system behave as expected. The two main types of non-functional testing are performance tests and usability tests.
  2. Performance testing relies on key metrics to quantify and compare the performance of the application. Important key metrics to monitor are response time, error rate, concurrent users, data throughput, and CPU/memory usage.
  3. Performance testing ensures that the system is scalable by measuring the performance of the individual parts of the system, allowing us to identify bottlenecks and improvements required. Furthermore, testing at higher loads of the system allows us to estimate the limits of what the system can handle, and helps us understand what the growth runway of the current system configuration is.
  4. Microservice architectures provide scalability benefits because they allow...