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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

Memory ballast

Memory ballast in Go, at its core, is like putting a heavy suitcase in the trunk of a car to prevent it from being too light and skidding on ice. In Go’s context, a memory ballast is a large allocation of memory that is never used but serves to influence the behavior of the garbage collector.

Traditionally, Go’s GC would trigger based on the heap size doubling from the size at the end of the last collection (GOGC=100). In applications with large heap sizes, this could lead to long periods between GC cycles, followed by large, disruptive collections.

Developers used memory ballast as a buffer, artificially increasing the heap size to prompt more frequent, but smaller and less disruptive, GC cycles. It was a manual tuning method to optimize performance, particularly in high-throughput, low-latency systems. This technique was developed by the streaming company Twitch in 2019 in their post How I learnt to stop worrying and love the heap (https://blog...

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