Efficient Go: Data-Driven Performance Optimization

Plotka, Bartlomiej

ISBN 10: 1098105710 / ISBN 13: 9781098105716

Published by O'Reilly Media, 2022

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Bibliographic Details

• Title: Efficient Go: Data-Driven Performance Optimization
• Publisher: O'Reilly Media
• Publication Date: 2022
• Language: English
• ISBN 10: 1098105710
• ISBN 13: 9781098105716
• Binding: Soft cover
• Condition: as new

About this title

Synopsis

With technological advancements, fast markets, and higher complexity of systems, software engineers tend to skip the uncomfortable topic of software efficiency. However, tactical, observability-driven performance optimizations are vital for every product to save money and ensure business success.

With this book, any engineer can learn how to approach software efficiency effectively, professionally, and without stress. Author Bartłomiej Płotka provides the tools and knowledge required to make your systems faster and less resource-hungry. Efficient Go guides you in achieving better day-to-day efficiency using Go. In addition, most content is language-agnostic, allowing you to bring small but effective habits to your programming or product management cycles.

This book shows you how to:

• Clarify and negotiate efficiency goals
• Optimize efficiency on various levels
• Use common resources like CPU and memory effectively
• Assess efficiency using observability signals like metrics, logging, tracing, and (continuous) profiling via open source projects like Prometheus, Jaeger, and Parca
• Apply tools like go test, pprof, benchstat, and k6 to create reliable micro and macro benchmarks
• Efficiently use Go and its features like slices, generics, goroutines, allocation semantics, garbage collection, and more!

About the Author

Bartlomiej Plotka is a Principal Software Engineer at Red Hat with a background in SRE. Working primarily on observability topics, he helped to build many popular, reliable, performance, and efficiency-oriented distributed systems in Go. He is a core maintainer of various open-source projects including the CNCF Prometheus (https://prometheus.io/), libraries in the gRPC ecosystem, and more. In 2017 he created, together with Fabian Reinartz, a popular, open source distributed time series database. Focused on cheap and efficient metric monitoring, written in Go and called Thanos (http://thanos.io/), it went through hundreds of performance and efficiency focused improvements and researches. Developing in Go since 2014, Bartekâ??s passion was always to focus on the readability, reliability, and efficiency aspect of the language. On the way, Bartek helped to develop many tools, blog posts and even created opinionated Go code style to teach others on writing pragmatic, but efficient Go applications.