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

Kafka Streams

Kafka Streams is a powerful stream-processing library built on top of Apache Kafka. It allows developers to build scalable, fault-tolerant, and real-time stream processing applications using a high-level Domain-Specific Language (DSL) or a low-level Processor API. Kafka Streams enables you to process and analyze data directly within Kafka, eliminating the need for separate stream processing frameworks. The following are the key features of Kafka Streams:

Native Kafka integration: Kafka Streams is tightly integrated with Kafka, allowing seamless reading from and writing to Kafka topics. It leverages Kafka’s features, such as partitioning and replication, for fault tolerance and scalability.
High-level DSL: Kafka Streams provides a high-level DSL that simplifies the development of stream processing applications. The DSL includes operations such as map, filter, join, and aggregate, which can be combined to express complex processing logic declaratively...