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System Design Guide for Software Professionals

System Design Guide for Software Professionals

By : Dhirendra Sinha, Tejas Chopra
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System Design Guide for Software Professionals

System Design Guide for Software Professionals

By: Dhirendra Sinha, Tejas Chopra

Overview of this book

Building scalable software systems is more critical than ever. Yet, many software professionals struggle to navigate the complexities of system design, especially when aiming for positions at top tech companies. Written by Dhirendra Sinha, a seasoned Engineering Leader at Google with a blend of experience working at large companies such as Cisco, Oracle, and Yahoo, and Tejas Chopra, a Senior Software Engineer at Netflix, a TEDx speaker, and a Co-Founder of GoEB1, this comprehensive and authoritative resource on system design offers invaluable insights and strategies to help you excel in interviews with all major tech companies. This guide covers the basics of system design, including the principles and techniques of distributed systems, and delves into core building blocks such as distributed system theorems, attributes, and the design and implementation of system components. Following examples of popular applications such as Uber, Twitter, Instagram, Google Docs, and Netflix, you’ll learn how to apply concepts to real-world scenarios. The book offers expert advice and strategies for preparing and acing system design interviews, along with a mind map/cheat sheet summarizing the key takeaways. By the end of this book, you’ll be equipped with unique techniques and the confidence to solve any coding interview question.
Table of Contents (21 chapters)
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1
Part 1: Foundations of System Design
5
Part 2: Core Components of Distributed Systems
10
Part 3: System Design in Practice

Consistent hashing

Consistent hashing is a technique that’s used in distributed systems to efficiently distribute data across multiple nodes while minimizing the need for data reorganization or rebalancing when nodes are added or removed from the system. It provides a scalable and fault-tolerant approach to handling data distribution.

In traditional hashing techniques, such as modulo hashing, the number of nodes or buckets where data can be stored is fixed. When nodes are added or removed, the hash function that’s used to map data keys to nodes changes, requiring a significant amount of data to be remapped and redistributed across the nodes. This process can be time-consuming, resource-intensive, and disruptive to the system’s availability.

The key problem that consistent hashing addresses is the scalability and fault tolerance of distributed systems. It aims to minimize the impact of adding or removing nodes from the system by ensuring that only a fraction...

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