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System Design Guide for Software Professionals

You're reading from System Design Guide for Software Professionals Build scalable solutions – from fundamental concepts to cracking top tech company interviews

Product type Paperback

Published in Aug 2024

Publisher Packt

ISBN-13 9781805124993

Length 384 pages

Edition 1st Edition

Concepts

Application Development

Authors (2):

Dhirendra Sinha

Tejas Chopra

View More author details

Table of Contents (21) Chapters

Preface

1. Part 1: Foundations of System Design

2. Chapter 1: Basics of System Design FREE CHAPTER

3. Chapter 2: Distributed System Attributes

4. Chapter 3: Distributed Systems Theorems and Data Structures

5. Part 2: Core Components of Distributed Systems

6. Chapter 4: Distributed Systems Building Blocks: DNS, Load Balancers, and Application Gateways

7. Chapter 5: Design and Implementation of System Components –Databases and Storage

8. Chapter 6: Distributed Cache

9. Chapter 7: Pub/Sub and Distributed Queues

10. Part 3: System Design in Practice

11. Chapter 8: Design and Implementation of System Components: API, Security, and Metrics

12. Chapter 9: System Design – URL Shortener

13. Chapter 10: System Design – Proximity Service

14. Chapter 11: Designing a Service Like Twitter

15. Chapter 12: Designing a Service Like Instagram

16. Chapter 13: Designing a Service Like Google Docs

17. Chapter 14: Designing a Service Like Netflix

18. Chapter 15: Tips for Interviewees

19. Chapter 16: System Design Cheat Sheet

20. Index

Load balancers

Load balancing distributes workload across multiple computing resources, such as servers, CPUs, hard drives, and network links, to achieve optimal resource utilization, maximize throughput, minimize response time, and avoid overload. Figure 4.5 shows a load balancer connected to clients on one end and a pool of server machines on the other end.

Figure 4.5: Load balancer

Figure 4.5: Load balancer

The following are some key points about load balancing:

It allows the spread of a huge amount of traffic across multiple servers so that no single server gets overloaded.
It improves fault tolerance by failing over (i.e., retrying the failed requests from failed or slowed-down servers to functioning servers).
It increases overall service availability since requests can still be serviced by the functioning servers even if some servers fail.
It can enable a graceful degradation of performance during periods of high load instead of a complete failure of the...

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Authors (2)

Dhirendra Sinha

Dhirendra Sinha

Dhirendra Sinha is a Software Engineering Manager at Google. He is an angel investor and has served as a Strategic and Technology advisor at a few startups. Dhirendra has around two decades of experience in the Software Engineering field building highly scalable complex distributed systems and managing multiple Engineering teams. While he has experience in working at large companies such as Cisco, Oracle, Yahoo, and Google, he has also been involved with early and late-stage startups in leadership positions. In addition to his strong Software Engineering experience, he has been teaching the Distributed System Design course for the last seven years. He has also been coaching and mentoring Software Engineers and Software Engineering Managers for over a decade. He completed his Bachelor of Technology degree from IIT Guwahati and Master of Science from Texas A and M University, College Station, Texas.

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Tejas Chopra

Tejas Chopra

Tejas Chopra is a Senior Engineer at Netflix working on building the Machine Learning Platform powering Netflix recommendations and personalization. He is also a Co-founder at GoEB1, which is the world's first thought leadership platform for immigrants. Tejas is a recipient of the prestigious EB1A (Einstein) visa in the US. He is a Tech 40 under 40 Award winner, a 2xTEDx speaker, a British Computer Society (BCS) Fellow, and has spoken at conferences and panels on Cloud Computing, Blockchain, Machine Learning, Software Development, and Engineering Leadership. Tejas has been awarded the “International Achievers Award, 2023” by the Indian Achievers' Forum. He is an Adjunct Professor of Software Development at the University of Advancing Technology, Arizona, an Angel Investor, and has previously been an Advisor to startups such as Nillion, Inc. He is also a member of the Advisory Board for Future of Memory and Storage Summit. Tejas' experience has been in companies such as Box, Apple, Samsung, Cadence, and Datrium. Tejas holds a Masters Degree in Electrical and Computer Engineering from Carnegie Mellon University, Pittsburgh.

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