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

Implementing OpenCensus for your application

Let's use a practical example for OpenCensus tracing in an application. To get started, we need to make sure that we have Docker installed on our machine. You should be able to use the installation documents at in order to be certain that Docker is installed and runs correctly on your machine. Once this is completed, we can get going with creating, implementing, and viewing a sample application. Once we have Docker installed, we can pull important images for our instrumentation. In our example, we will use Redis (a key–value store) to store key–value events in our application and Zipkin (a distributed tracing system) to view these traces.

Let's pull our dependencies for this project:

  1. Redis, which is a key–value store that we are going to use in our sample application: