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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

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Product type Paperback
Published in Aug 2024
Publisher Packt
ISBN-13 9781805124993
Length 384 pages
Edition 1st Edition
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Authors (2):
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Dhirendra Sinha Dhirendra Sinha
Author Profile Icon Dhirendra Sinha
Dhirendra Sinha
Tejas Chopra Tejas Chopra
Author Profile Icon Tejas Chopra
Tejas Chopra
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Toc

Table of Contents (21) Chapters Close

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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