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

Additional considerations

When designing and implementing the Twitter-like service, there are several additional considerations and best practices to keep in mind. These considerations ensure the system is scalable, maintainable, and aligned with business requirements. Let’s explore some of these key aspects:

Handling trending topics and hashtags: We can implement a mechanism to track and identify trending topics and hashtags based on their popularity and frequency of use. To do so, we can utilize real-time stream processing frameworks such as Apache Storm or Apache Flink to analyze the incoming tweet data and update the trending topics in real-time. For performance, we can store the trending topics and hashtags in a cache or database for quick retrieval and display to users. Finally, we can provide API endpoints to retrieve the current trending topics and allow users to explore tweets related to those topics.
Implementing rate limiting and throttling: One of the...