System Design Guide for Software Professionals : Build Scalable Solutions - from Fundamental Concepts to Cracking Top Tech Company Interviews / Dhirendra Sinha and Tejas Chopra.

Format:

Book

Author/Creator:

Sinha, Dhirendra, author.

Chopra, Tejas, author.

Language:

English

Subjects (All):

Computer software--Development.

Computer software.

Software architecture.

Physical Description:

1 online resource (384 pages)

Edition:

First edition.

Place of Publication:

Birmingham, England : Packt Publishing, [2024]

Biography/History:

Sinha Dhirendra: 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. Chopra Tejas: 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.

Summary:

Enhance your system design skills to build scalable and efficient systems by working through real-world case studies and expert strategies to excel in interviews Key Features Comprehensive coverage of distributed systems concepts and practical system design techniques. Insider tips and proven strategies from engineering leaders at top tech companies. Detailed case studies of widely used applications and their system architectures. Purchase of the print or Kindle book includes a free PDF eBook Book Description Building scalable software systems is more critical than ever. Yet, many software professionals struggle to navigate the complexities of system design, especially when aiming for positions at top tech companies. Written by Dhirendra Sinha, a seasoned Engineering Leader at Google with a blend of experience working at large companies such as Cisco, Oracle, and Yahoo, and Tejas Chopra, a Senior Software Engineer at Netflix, a TEDx speaker, and a Co-Founder of GoEB1, this comprehensive and authoritative resource on system design offers invaluable insights and strategies to help you excel in interviews with all major tech companies. This guide covers the basics of system design, including the principles and techniques of distributed systems, and delves into core building blocks such as distributed system theorems, attributes, and the design and implementation of system components. Following examples of popular applications such as Uber, Twitter, Instagram, Google Docs, and Netflix, you'll learn how to apply concepts to real-world scenarios. The book offers expert advice and strategies for preparing and acing system design interviews, along with a mind map/cheat sheet summarizing the key takeaways. By the end of this book, you'll be equipped with unique techniques and the confidence to solve any coding interview question. What you will learn Design for scalability and efficiency with expert insights Apply distributed system theorems and attributes Implement DNS, databases, caches, queues, and APIs Analyze case studies of real-world systems Discover tips to excel in system design interviews with confidence Apply industry-standard methodologies for system design and evaluation Explore the architecture and operation of cloud-based systems Who this book is for This book is a must-have resource for experienced software professionals, particularly those with 5-15 years of experience in building scalable distributed systems, web applications, and backend microservices. Whether you're a seasoned developer or an architect looking to deepen your expertise in system design, this book provides the insights and practical knowledge you need to excel in tech interviews and advance your career. A solid foundation in distributed systems, data structures/algorithms, and web development will help you get the most out of this comprehensive guide.

Contents:

Cover

Title Page

Copyright and Credits

Contributors

Table of Contents

Preface

Part 1: Foundations of System Design

Chapter 1: Basics of System Design

What is system design?

Software system

Distributed software system

Understanding system design

What are the types of system design?

High-level system design

System architecture

Data flow

Scalability

Fault tolerance

Low-level system design

Algorithms

Data structures

APIs

Code optimization

Importance of system design in the industry

Practical examples of the importance of system design

Summary

Chapter 2: Distributed System Attributes

A hotel room booking example

Consistency

Strong consistency

Eventual consistency

Availability

Understanding partition tolerance

Network partition

Partition tolerance

Latency

Durability

Reliability

Vertical scaling

Horizontal scaling

Chapter 3: Distributed Systems Theorems and Data Structures

CAP theorem

PACELC theorem

Paxos

Raft

BGP

The Byzantine fault

Byzantine fault tolerance

Modern BFT

FLP impossibility theorem

Consistent hashing

Bloom filters

Count-min sketch

HyperLogLog

Part 2: Core Components of Distributed Systems

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

Exploring DNS

DNS querying

Scalability, reliability, and consistency in DNS

Load balancers

Placing load balancers

Advantages of load balancers

Global and local load balancing

DNS and GSLB

Load balancer algorithms

Load balancing at different layers of the Open Systems Interconnection (OSI) model

Deployment of load balancers

Implementing load balancers.

Application gateways

Features and capabilities

Microservices architectures

Cloud-native implementations

On-premises options

Chapter 5: Design and Implementation of System Components -Databases and Storage

Databases

Types of databases

Relational databases

NoSQL databases

The advantages and disadvantages of relational and NoSQL databases

Key-value stores

What is a key-value store?

Use in distributed systems

Designing a key-value store

Enhancing scalability and data replication

Boosting scalability

Virtual nodes

Data duplication strategies

Implementing get and put functions

Implementing get and put operations

Using r and w

Ensuring fault tolerance and identifying failures in a key-value store

Managing temporary failures

Addressing permanent failures

Ring membership promotion for failure detection

A system design interview - key value store design questions and strategies

DynamoDB

No fixed schema

API functions

Partitioning data in DynamoDB

Throughput optimizations in DynamoDB

High availability in DynamoDB

Column-family databases

HBase

HBase details

Graph-based databases

The Neo4j graph database

Neo4j details

Relational modeling versus graph modeling

Graph modeling

Adding a new node to an existing graph

References

Chapter 6: Distributed Cache

What is caching?

What is distributed caching?

How is it different from regular caching?

Use cases

Benefits of using a distributed cache

Challenges of using distributed caching

Designing a distributed cache

Requirements

Design journey

Popular distributed cache solutions

Redis

Memcached

How to choose between Redis and Memcached

Chapter 7: Pub/Sub and Distributed Queues.

The evolution of distributed systems

Designing a distributed queue

Designing a pub/sub system

Key characteristics of pub/sub systems

Pub/sub system design considerations

Kafka

The importance of Kafka in distributed systems

Kafka Streams

Kinesis

Part 3: System Design in Practice

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

REST APIs

Design principles of REST APIs

Use cases for REST APIs

Strengths and weaknesses

gRPC APIs

Design principles of gRPC APIs

Use cases for gRPC APIs

Comparing REST and gRPC

API security

Authentication

Authorization

Secure communication of APIs

Rate limiting

Distributed systems logging

Centralized logging

Best practices for implementing distributed logging

Metrics in a distributed system

Types of metrics

Open source tools for metrics

Best practices for implementing metrics

Alerting in a distributed system

Designing effective alerts

Open-source tools for alerting

Best practices for implementing alerting

Tracing in a distributed system

Distributed tracing

Open-source tools for distributed tracing

Best practices for implementing tracing

Best practices

Chapter 9: System Design - URL Shortener

Real-world use cases

Functional requirements

Non-functional requirements

Client APIs needed

Estimates and calculations

System design

Core challenge

Choice of database

High-level solution architecture

Requirements verification

Chapter 10: System Design - Proximity Service

Core challenge.

Final high-level solution architecture

Chapter 11: Designing a Service Like Twitter

Data model

Scale calculations

Exploring high-level design

Microservices architecture

Designing Tweet Service

Data storage

Tweet creation flow

Tweet retrieval flow

Caching

Designing User Service

User registration flow

User authentication flow

Follow/unfollow flow

Retrieving followers/followees

Low-level design - Timeline Service

Timeline retrieval flow

Push-based updates

Designing Search Service

Data flow and indexing

Search query processing

Relevance scoring and ranking

Additional considerations

Chapter 12: Designing a Service Like Instagram

Designing the data model

High-level design

Components and modules in the high-level architecture

Low-level design

Designing the Photo Upload Service

News Feed Service

User Service

Chapter 13: Designing a Service Like Google Docs

Relationships

Assumptions

Storage requirements

Bandwidth considerations

Processing requirements

Software components and modules of high-level design

Designing the document service

Designing the Collaboration Service

Designing the Access Control Service

Additional considerations and best practices

Chapter 14: Designing a Service Like Netflix

Assumptions.

Storage estimation

Bandwidth estimation

Processing estimation

Video Service

Video upload and storage

Video encoding and transcoding

Video streaming

Caching and content delivery

User authentication and authorization

User profile management

Database and caching

Recommendation Service

The CDN

CDN architecture and content distribution

Request routing and video streaming

Adaptive bitrate streaming

Content security and DRM

Chapter 15: Tips for Interviewees

Tips for preparation for system design interviews

Understanding the fundamentals

Studying common system design patterns

Practicing designing systems

Learning from online resources

Honing your communication skills

Reviewing and reflecting

Tips for the interview session

Understanding the problem statement

Breaking down the problem

Key steps to follow

Communicating your solution effectively

Chapter 16: System Design Cheat Sheet

Which data store should we use for a use case?

Which data structures should we use for a use case?

Which components should we use for which use case?

What protocol should we use for which use case?

Which solution should we use for which core challenge?

Index.

Notes:

Description based upon print version of record.

API functions

Includes bibliographical references and index.

Description based on publisher supplied metadata and other sources.

Description based on print version record.

ISBN:

9781805122319

1805122312

OCLC:

1451796826