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System Programming Essentials with Go

System Programming Essentials with Go

By : Alex Rios
5 (5)
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System Programming Essentials with Go

System Programming Essentials with Go

5 (5)
By: Alex Rios

Overview of this book

Alex Rios, a seasoned Go developer and active community builder, shares his 15 years of expertise in designing large-scale systems through this book. It masterfully cuts through complexity, enabling you to build efficient and secure applications with Go's streamlined syntax and powerful concurrency features. In this book, you’ll learn how Go, unlike traditional system programming languages (C/C++), lets you focus on the problem by prioritizing readability and elevating developer experience with features like automatic garbage collection and built-in concurrency primitives, which remove the burden of low-level memory management and intricate synchronization. Through hands-on projects, you'll master core concepts like file I/O, process management, and inter-process communication to automate tasks and interact with your system efficiently. You'll delve into network programming in Go, equipping yourself with the skills to build robust, distributed applications. This book goes beyond the basics by exploring modern practices like logging and tracing for comprehensive application monitoring, and advance to distributed system design using Go to prepare you to tackle complex architectures. By the end of this book, you'll emerge as a confident Go system programmer, ready to craft high-performance, secure applications for the modern world.
Table of Contents (24 chapters)
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Free Chapter
1
Part 1: Introduction
4
Part 2: Interaction with the OS
10
Part 3: Performance
13
Part 4: Connected Apps
17
Part 5: Going Beyond

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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