The System Design Manual
The System Design Manual
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The System Design Manual

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Last updated on 2020-09-06

About the Book

Learning to design, build, and operate distributed systems is the single best thing you can do as a software engineer if you desire a higher salary or a better position. Don't take my word for it - according to Stack Overflow's 2020 developer survey, the best-paid engineering roles, like Site Reliability Engineering, require distributed systems expertise.

Designing large-scale distributed systems requires experience and a firm grasp of the core principles. By learning those, you will add a powerful tool to your toolbelt - one that will make you stand out from the crowd. There is more to designing systems than connecting boxes with arrows - that's the easy part. The hard part is understanding failure modes and trade-offs.

I recall how hard it was to find the right information when I first started learning about distributed systems. I was looking for a pragmatic and timeless guide covering all the angles on the subject, but there was nothing like it. Some books were too theoretical, while others felt like marketing material for a technology stack that would be obsolete in a few years. I spent hours trying to connect the missing dots without a solid grasp of the fundamentals.

This is why I decided to write a book to teach the core principles of large-scale distributed systems. The book contains knowledge I have used over the years to solve concrete problems, the kind that needs to scale to millions of requests per second, and billions of devices. But, no matter the scale of the systems you work on today, the core principles are universal.

After reading the book, you are not going to look at a network calls the same way. And you will start applying your newly gained knowledge from day one at your job and on personal projects. Armed with the fundamentals, you will have the tools to understand technical whitepapers, build systems of your own, and nail interviews.

About the Author

Roberto Vitillo
Roberto Vitillo

Hi! My name is Roberto Vitillo. I have over 15 years’ experience in the tech industry as a software engineer, tech lead, and manager.

In 2017 I joined Microsoft to work on an internal data platform as a SaaS product. Since then, I have helped launch two public SaaS products, Product Insights and Playfab. The data pipeline I am responsible for is one of the largest in the world. It processes millions of events per second from billions of devices worldwide.

Before that, I worked for Mozilla, where I wore different hats, from performance engineer to data platform engineer. What I am most proud of is having set the direction of the data platform from its very early days and built a large part of it, including the team.

Table of Contents

  • Copyright
  • About the Author
  • Acknowledgements
  • Preface
    • Who should read this book
  • Introduction
    • Scalability
    • Resiliency
    • Operability
  • Network Fundamentals
    • Transmission Control Protocol
      • Reliability
      • Connection Lifecycle
      • Flow Control
      • Congestion Control
    • User Datagram Protocol
    • Transport Layer Security
      • Encryption
      • Authentication
      • Integrity
      • Handshake
    • Domain Name System
    • Application Programming Interfaces
      • Resources
      • Request Methods
      • Response Status Code
      • Headers
      • Connection Management
      • Statelessness
      • Authentication and Authorization
      • Reverse Proxies
      • Caching
  • Distributed Algorithms
    • Failure Detection
    • Time
      • Physical Clocks
      • Logical Clocks
      • Vector Clocks
    • Leader Election
      • Raft Leader Election
      • Practical Considerations
    • Replication
      • State Machine Replication
      • Consensus
    • Consistency Models
      • Strong Consistency
      • Sequential Consistency
      • Eventual Consistency
      • CAP Theorem
    • Transactions
      • Isolation
      • Atomicity
  • Architectural Patterns
    • Sharding
    • Replication
    • Caching
    • Asynchrony
    • Publish-Subscribe
    • Scatter-Gather
    • Map-Reduce
  • Resiliency Patterns
    • Common Failure Causes
      • Single Point of Failure
      • Unreliable Network
      • Slow Processes
      • Unexpected Load
      • Cascading failures
      • Risk Management
    • Timeout
    • Retry
      • Exponential Backoff
      • Retry Amplification
    • Circuit Breaker
      • State Machine
    • Load Shedding
    • Load Leveling
    • Rate-Limiting
      • Single-Node Implementation
      • Distributed implementation
    • Health Endpoint
      • Health Checks
    • Watchdog
  • Operational Patterns
    • Metrics
    • Logs
    • Alerts
    • SLOs
    • Prober
    • Chaos Engineering

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