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Go for DevOps

You're reading from   Go for DevOps Learn how to use the Go language to automate servers, the cloud, Kubernetes, GitHub, Packer, and Terraform

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Product type Paperback
Published in Jul 2022
Publisher Packt
ISBN-13 9781801818896
Length 634 pages
Edition 1st Edition
Languages
Tools
Concepts
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Authors (2):
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John Doak John Doak
Author Profile Icon John Doak
John Doak
David Justice David Justice
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David Justice
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Toc

Table of Contents (22) Chapters Close

Preface 1. Section 1: Getting Up and Running with Go
2. Chapter 1: Go Language Basics FREE CHAPTER 3. Chapter 2: Go Language Essentials 4. Chapter 3: Setting Up Your Environment 5. Chapter 4: Filesystem Interactions 6. Chapter 5: Using Common Data Formats 7. Chapter 6: Interacting with Remote Data Sources 8. Chapter 7: Writing Command-Line Tooling 9. Chapter 8: Automating Command-Line Tasks 10. Section 2: Instrumenting, Observing, and Responding
11. Chapter 9: Observability with OpenTelemetry 12. Chapter 10: Automating Workflows with GitHub Actions 13. Chapter 11: Using ChatOps to Increase Efficiency 14. Section 3: Cloud ready Go
15. Chapter 12: Creating Immutable Infrastructure Using Packer 16. Chapter 13: Infrastructure as Code with Terraform 17. Chapter 14: Deploying and Building Applications in Kubernetes 18. Chapter 15: Programming the Cloud 19. Chapter 16: Designing for Chaos 20. Index 21. Other Books You May Enjoy

Utilizing goroutines for concurrency

In the modern era of computers, concurrency is the name of the game. In the years before 2005 or so, computers used Moore's law to double the speed of a single central processing unit (CPU) every 18 months. Multiple CPU consumer systems were rare and there was one core per CPU in the system. Software that utilized multiple cores efficiently was rare.

Over time, it became more expensive to increase single-core speed and multi-core CPUs have become the norm. Each core on a CPU supports a number of hardware threads and operating systems (OSs) provide OS threads that are mapped to hardware threads that are then shared between processes.

Languages can utilize these OS threads to run functions in their language concurrently instead of serially as we have been doing in all of our code so far.

Starting an OS thread is an expensive operation and to fully utilize the thread's time requires paying a lot of attention to what you are doing...

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