Book Image

Hands-On High Performance with Go

By : Bob Strecansky
Book Image

Hands-On High Performance with Go

By: Bob Strecansky

Overview of this book

Go is an easy-to-write language that is popular among developers thanks to its features such as concurrency, portability, and ability to reduce complexity. This Golang book will teach you how to construct idiomatic Go code that is reusable and highly performant. Starting with an introduction to performance concepts, you’ll understand the ideology behind Go’s performance. You’ll then learn how to effectively implement Go data structures and algorithms along with exploring data manipulation and organization to write programs for scalable software. This book covers channels and goroutines for parallelism and concurrency to write high-performance code for distributed systems. As you advance, you’ll learn how to manage memory effectively. You’ll explore the compute unified device architecture (CUDA) application programming interface (API), use containers to build Go code, and work with the Go build cache for quicker compilation. You’ll also get to grips with profiling and tracing Go code for detecting bottlenecks in your system. Finally, you’ll evaluate clusters and job queues for performance optimization and monitor the application for performance regression. By the end of this Go programming book, you’ll be able to improve existing code and fulfill customer requirements by writing efficient programs.
Table of Contents (20 chapters)
Section 1: Learning about Performance in Go
Section 2: Applying Performance Concepts in Go
Section 3: Deploying, Monitoring, and Iterating on Go Programs with Performance in Mind

Comparing Code Quality Across Versions

After you've written, debugged, profiled, and monitored your Go code, you need to monitor your application in the long term for performance regressions. Adding new features to your code is useless if you can't continue to deliver a level of performance that other systems in your infrastructure depend on.

In this chapter, we will learn about the following topics:

  • Utilizing the Go Prometheus exporter
  • Application performance monitoring (APM) tools
  • Service-level indicators and service-level objectives (SLIs and SLOs)
  • Utilizing logging

Understanding these concepts should help drive you to write performant code over the longer term. When working on larger-scale projects, work often doesn't scale well. Having 10 times the number of engineers often does not guarantee 10 times the output. Being able to programmatically quantify code...