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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
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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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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

Developing REST services and clients

Before the web and distributed systems that now permeate the cloud space, standards for communicating between systems were not in widespread use. This communication is often called an RPC. This simply means that a program on one machine has a method to call a function running on a different machine and receive any output.

Monolithic applications were the norm and servers tended to either be silo'd per application and vertically scaled or were run as jobs on larger, more specialized hardware from companies such as IBM, Sun, SGI, or Cray. When systems did need to communicate with each other, they tended to use their own custom wire formats, such as what you would see with Microsoft SQL Server.

With the web defining the internet of the 2000s, large monolithic systems could not provide the compute power behind services such as Google Search or Facebook at any reasonable cost point. To power these services, companies needed to treat large...

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