Book Image

Effective Concurrency in Go

By : Burak Serdar
5 (1)
Book Image

Effective Concurrency in Go

5 (1)
By: Burak Serdar

Overview of this book

The Go language has been gaining momentum due to its treatment of concurrency as a core language feature, making concurrent programming more accessible than ever. However, concurrency is still an inherently difficult skill to master, since it requires the development of the right mindset to decompose problems into concurrent components correctly. This book will guide you in deepening your understanding of concurrency and show you how to make the most of its advantages. You’ll start by learning what guarantees are offered by the language when running concurrent programs. Through multiple examples, you will see how to use this information to develop concurrent algorithms that run without data races and complete successfully. You’ll also find out all you need to know about multiple common concurrency patterns, such as worker pools, asynchronous pipelines, fan-in/fan-out, scheduling periodic or future tasks, and error and panic handling in goroutines. The central theme of this book is to give you, the developer, an understanding of why concurrent programs behave the way they do, and how they can be used to build correct programs that work the same way in all platforms. By the time you finish the final chapter, you’ll be able to develop, analyze, and troubleshoot concurrent algorithms written in Go.
Table of Contents (13 chapters)

Detecting failures and healing

Most software systems will fail despite the efforts spent on testing them. This suggests there are limits to what can be achieved by testing. These limitations stem from several facts about non-trivial systems. Any non-trivial system interacts with its environment, and it is simply not practical (and in many cases, not possible) to enumerate all possible environments in which the system will run. Also, it is usually possible to test a system to make sure it behaves as expected, but it is much harder to develop tests to make sure the system does not behave unexpectedly. Concurrency adds additional complexities: a program that was successfully tested for a particular scenario may fail for the same scenario when put into production.

In other words, no matter how much you test your programs, all sufficiently complex programs will eventually fail. So, it makes sense to architect systems for graceful failure and quick recovery. Part of this architecture...