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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

Implementing get and put functions

This section will delve into how to implement get and put functions in our key-value store.

Implementing get and put operations

A key requirement for our system is configurability. This means the ability to adjust the balance between availability, consistency, cost-effectiveness, and efficiency. We can achieve this by incorporating the fundamental get and put functions of a key-value store.

In our system, every node can perform get (read) and put (write) operations. The node that manages these operations is known as a coordinator, which is usually the first among the top n nodes on the preference list.

Clients can select a node in two ways:

  • By routing the request through a generic load balancer
  • By using a partition-aware client library that directs requests straight to the relevant coordinator nodes

Both methods have their advantages. The first approach doesn’t tie the client to the code, while the second one...

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