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

SLIs and SLOs – setting goals

SLIs and SLOs are two paradigms that were brought to the computer science world by Google. They are defined in the SRE workbook
( and are an excellent way to measure actionable items within your computing system. These measurements normally follow Google's four golden signals:

  • Latency: The amount of time a request takes to complete (usually measured in milliseconds)
  • Traffic: The volume of traffic that your service is receiving (usually measured in requests per second)
  • Errors: The percentage of failed requests over total requests (usually measured with a percentage)
  • Saturation: The measure of hardware saturation (usually measured by queued request counts)

These measurements can then be used to create one or more SLAs. These are frequently delivered to customers...