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donnemartin/system-design-primer

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TLDR

Study guide and reference for designing large-scale software systems and preparing for system design interviews at tech companies.

Mindmap

mindmap
  root((repo))
    Core Concepts
      Trade-offs
      CAP Theorem
      Consistency Patterns
    System Components
      Load Balancers
      Caching Strategies
      Databases
      Message Queues
    Learning Resources
      Flashcard Decks
      Design Exercises
      Interview Prep
    Use Cases
      Senior Engineer Interviews
      System Architecture
      Scalability Learning
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Things people build with this

USE CASE 1

Prepare for system design interviews at major tech companies by studying trade-offs, CAP theorem, and architectural patterns.

USE CASE 2

Learn how to architect scalable systems by understanding load balancers, caching, databases, and asynchronous messaging.

USE CASE 3

Build a shared vocabulary for discussing large-system design with flashcard decks and design exercises.

USE CASE 4

Teach yourself distributed systems concepts like replication, failover, microservices, and content delivery networks.

Tech stack

Python

Getting it running

Difficulty · easy Time to first run · 5min
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In plain English

This repository is a free, community-maintained study resource for learning how to design large software systems. It is aimed at two audiences: engineers who want to get better at building software that runs at scale, and candidates preparing for the system design portion of a tech interview. The author frames it as an organized collection of resources, gathering material that is otherwise scattered across the web. The README is mostly a long index that links into the deeper guide. The opening sections include study guides, advice on how to approach a system design interview question, and pointers to sample interview questions with worked solutions, both for system design and for object-oriented design. A sister repository called Interactive Coding Challenges is also referenced for coding-interview prep. The index then walks through the main concepts you would meet on the job or in interviews. Topics include performance versus scalability, latency versus throughput, availability versus consistency, the CAP theorem, consistency patterns (weak, eventual, strong), availability patterns (fail-over, replication, availability in numbers), DNS, content delivery networks (push and pull), load balancers (active-passive, active-active, layer 4 vs layer 7, horizontal scaling), reverse proxies, the application layer (microservices, service discovery), databases (relational systems with replication, federation, sharding, denormalization and SQL tuning, NoSQL key-value, document, wide column, and graph stores), caching (client, CDN, web server, database, application, query- and object-level, plus cache-aside, write-through, write-behind, and refresh-ahead update strategies), and asynchronous work via message queues, task queues, and back pressure. The repo also ships Anki flashcard decks, which use spaced repetition to help you remember the material. There are three decks: a system design deck, a system design exercises deck, and an object-oriented design exercises deck. The README is translated into many languages (Japanese, Simplified and Traditional Chinese, Arabic, Bengali, Brazilian Portuguese, German, Greek, Hebrew, Italian, Korean, Persian, Polish, Russian, Spanish, Thai, Turkish, Vietnamese, French), with open issues tracking each translation effort.

Copy-paste prompts

Prompt 1
I'm interviewing for a senior role and need to understand CAP theorem and consistency patterns. Walk me through the trade-offs using examples from the System Design Primer.
Prompt 2
Help me design a scalable system using load balancers, caching, and databases. What are the pros and cons of each component?
Prompt 3
Create a study plan for system design using the flashcard decks and exercises from the System Design Primer.
Prompt 4
Explain the difference between latency and throughput, and when each matters in system design.
Prompt 5
I need to understand microservices and service discovery. What are the key concepts and trade-offs?
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