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System Programming Essentials with Go

You're reading from   System Programming Essentials with Go System calls, networking, efficiency, and security practices with practical projects in Golang

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Product type Paperback
Published in Jun 2024
Publisher Packt
ISBN-13 9781837634132
Length 408 pages
Edition 1st Edition
Languages
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Author (1):
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Alex Rios Alex Rios
Author Profile Icon Alex Rios
Alex Rios
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Table of Contents (24) Chapters Close

Preface 1. Part 1: Introduction
2. Chapter 1: Why Go? FREE CHAPTER 3. Chapter 2: Refreshing Concurrency and Parallelism 4. Part 2: Interaction with the OS
5. Chapter 3: Understanding System Calls 6. Chapter 4: File and Directory Operations 7. Chapter 5: Working with System Events 8. Chapter 6: Understanding Pipes in Inter-Process Communication 9. Chapter 7: Unix Sockets 10. Part 3: Performance
11. Chapter 8: Memory Management 12. Chapter 9: Analyzing Performance 13. Part 4: Connected Apps
14. Chapter 10: Networking 15. Chapter 11: Telemetry 16. Chapter 12: Distributing Your Apps 17. Part 5: Going Beyond
18. Chapter 13: Capstone Project – Distributed Cache 19. Chapter 14: Effective Coding Practices 20. Chapter 15: Stay Sharp with System Programming 21. Index 22. Other Books You May Enjoy Appendix : Hardware Automation

Understanding distributed caching

So, do you think distributed caching is just a fancy term for storing stuff in memory across a few servers? Bless your heart. If only life were that simple. Let me guess, you’re the type who thinks that simply slapping “distributed” in front of anything makes it automatically better, faster, and cooler. Well, strap in because we’re about to dive into the rabbit hole of distributed caching, where nothing is as straightforward as it seems.

Imagine you’re at a software developer’s party (because we all know how wild those get), and someone casually mentions, “Hey, why don’t we just cache everything?” This is like saying, “Why don’t we just solve world hunger by ordering more pizza?” Sure, the idea is nice, but the devil is in the details. Distributed caching is not about stuffing more data into memory. It’s about smartly managing data spread across multiple nodes...

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