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liquidslr/system-design-notes

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TLDR

Notes summarizing the two 'System Design Interview' books across 28 chapters, covering scaling basics, rate limiters, chat systems, and advanced topics like payment systems and stock exchanges, with links to real engineering blogs.

Mindmap

mindmap
  root((system design))
    Foundations
      Scaling basics
      Estimation math
      Design framework
    Specific Systems
      Rate limiter
      URL shortener
      Chat system
      Web crawler
    Advanced Topics
      Payment systems
      Stock exchange
      Gaming leaderboards
      Proximity services
    Resources
      Research papers
      Engineering blogs
      Company case studies
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Things people build with this

USE CASE 1

Use as a structured study guide when preparing for system design interview rounds at Google, Amazon, or other large tech companies.

USE CASE 2

Look up how a specific system type works, like consistent hashing, URL shorteners, or web crawlers, using the condensed chapter summaries.

USE CASE 3

Follow the linked research papers and engineering blog posts to see how real companies like Discord or Netflix solved large-scale problems.

Getting it running

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In plain English

This repository contains notes taken from a popular pair of textbooks called "System Design Interview: An Insider's Guide" (Volumes 1 and 2). The books walk through how large software systems are built and scaled, and these notes summarize each chapter in a more condensed form. They are described as a work in progress, so not every section may be fully complete. The notes cover 28 chapters, each focused on a different kind of problem that engineers face when building systems that need to handle millions of users. Early chapters cover foundational topics like how to scale a small app to serve massive traffic, how to estimate the resources a system needs, and a general framework for approaching design questions in interviews. Later chapters tackle specific systems: a rate limiter (which controls how often users can make requests), consistent hashing (a technique for distributing data across many servers), key-value stores (a type of database), URL shorteners, web crawlers, notification systems, chat systems, and search autocomplete. The second volume continues with more advanced scenarios including proximity services (finding things near you on a map), real-time gaming leaderboards, payment systems, digital wallets, and stock exchanges. Each of these is a real type of system that companies like Google, Uber, Discord, or Netflix have had to build at scale. Alongside the chapter notes, the repository links to additional reference materials: research papers, engineering blog posts, and talks from companies like Amazon, Google, Twitter, Slack, and Netflix. These give real-world examples of the concepts described in the books, such as how Discord stores billions of messages or how Netflix encodes video at scale. If you are preparing for a software engineering interview at a large tech company, or simply want to understand how big systems are put together, this repository provides a structured reading path tied to a well-known study guide. You do not need to read the books themselves to get value from the links and notes here, though having the books alongside would help with context.

Copy-paste prompts

Prompt 1
Using the system design framework from this guide, walk me through designing a URL shortener that handles 100 million URLs with sub-50ms redirect latency, cover storage, hashing, and the redirect flow.
Prompt 2
Explain consistent hashing and show with a numeric example how it distributes data across 10 database servers when one is added or removed.
Prompt 3
Design a notification system that delivers 10 million push notifications per day across iOS and Android, list the components and data flow.
Prompt 4
What are the key differences between designing a read-heavy versus a write-heavy system, and how does this change my database choice?
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