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A declarative JavaScript library for application development using cloud services.
An iOS library to natively render After Effects vector animations
All files for 6 axis robot arm with cycloidal gearboxes .

A repository for All algorithms implemented in Javascript (for educational purposes only)
Show your latest blog posts from any sources or StackOverflow activity on your GitHub profile/project readme automatically using the RSS feed
Questions to ask the company during your interview
An open-source platform for making universal native apps with React. Expo runs on Android, iOS, and the web.
955 不加班的公司名单 - 工作 955,work–life balance (工作与生活的平衡)
✅ Curated list of resources for college students
An open-source big data platform designed and optimized for the Internet of Things (IoT).
Jazzy theme for Django
Full stack, modern web application generator. Using FastAPI, PostgreSQL as database, Docker, automatic HTTPS and more.
? Some useful websites for programmers.
Linux/OSX/FreeBSD resource monitor
Enumerate and disable common sources of telemetry used by AV/EDR.
InstaGrabber, the open-source Instagram client for Android. Originally by @AwaisKing.

Helpful list of powershell scripts I have found/created
Source to
Simple and privacy-friendly alternative to Google Analytics
An open source, low-code machine learning library in Python
Automated decryption tool
A repository listing out the potential sources which will help you in preparing for a Data Science/Machine Learning interview. New resources added frequently.

Curso de programación en Python - 2do cuatrimestre 2020 - UNSAM
GPU Accelerated JavaScript
How to systematically secure anything: a repository about security engineering
A high performance X11 animated wallpaper setter
? JAVClub - 让你的大姐姐不再走丢
The "cloud" at home

? Instagram Bot - Tool for automated Instagram interactions
A cat(1) clone with wings.
A Deep Learning based project for colorizing and restoring old images (and video!)
this is downloadings of all free student subscription courses as pdf from GitHub student pack
? Small exercises to get you used to reading and writing Rust code!
Updated list of public BitTorrent trackers
React Native client application for COVID Shield on iOS and Android
A collection of improved binary search algorithms.

Port of the double tap on back of device feature from Android 11 to any armv8 Android device
Starter files, final projects and FAQ for my Complete JavaScript course
Official open source SVG icon library for Bootstrap.
OneFlow is a performance-centered and open-source deep learning framework.
WIP: Roadmap to becoming a machine learning engineer in 2020
Hypervisor Memory Introspection Core Library
IBM Fully Homomorphic Encryption Toolkit For Linux
Tiny minimal 1px icons designed to fit in the smallest places.
An open source project management tool with Kanban boards
Exposure notification client application / Application client de notification d'exposition
?谷粒-Chrome插件英雄榜, 为优秀的Chrome插件写一本中文说明书, 让Chrome插件英雄们造福人类~ ChromePluginHeroes, Write a Chinese manual for the excellent Chrome plugin, let the Chrome plugin heroes benefit the human~ 公众号「0加1」同步更新
SSPanel V3 魔改再次修改版
Gets the last 5 months of volume history for every ticker, and alerts you when a stock's volume exceeds 10 standard deviations from the mean within the last 3 days
Build forms in React, without the tears ?
Standard and Advanced Demos for courses
Public release of the TransCoder research project
This repo contains hourly-updated data dumps of bug bounty platform scopes (like Hackerone/Bugcrowd/Intigriti/etc) that are eligible for reports
Cracking the Coding Interview 6th Ed. Solutions
?? Windows 95 in Electron. Runs on macOS, Linux, and Windows.
SkyArk helps to discover, assess and secure the most privileged entities in Azure and AWS
Everything you need to know to get the job.
Getting Genymotion & Burpsuite setup for Android Mobile App Analysis
DeText: A Deep Neural Text Understanding Framework for Ranking and Classification Tasks
A curated list of awesome frameworks, libraries and software for the Java programming language.

Tye is a tool that makes developing, testing, and deploying microservices and distributed applications easier. Project Tye includes a local orchestrator to make developing microservices easier and the
Design patterns implemented in Java
Modern Java - A Guide to Java 8
JHipster is a development platform to quickly generate, develop, & deploy modern web applications & microservice architectures.
Official repository for the STAYAWAY COVID mobile application
Microsoft REST API Guidelines
This is the Ultimate Windows 10 Script from a creation from multiple debloat scripts and gists from github.
Just Announced - "Learn Spring Security OAuth":
Otto makes machine learning an intuitive, natural language experience.? Facebook AI Challenge winner
This repository contains the source code for the paper First Order Motion Model for Image Animation
Laravel best practices
⭐️ Companies that don't have a broken hiring process
PyTorch implementation of YOLOv4
A virtual Apple Macintosh with System 8, running in Electron. I'm sorry.
Your most handy video processing software
Proximal Policy Optimization (PPO) algorithm for Super Mario Bros
Apache Arrow is a cross-language development platform for in-memory data. It specifies a standardized language-independent columnar memory format for flat and hierarchical data, organized for efficien
The Swift Programming Language
Flutter makes it easy and fast to build beautiful apps for mobile and beyond.
Open and cheap DIY IP-KVM based on Raspberry Pi
.NET Decompiler with support for PDB generation, ReadyToRun, Metadata (&more) - cross-platform!
⚛️ Projeto feito durante a Imersão React da Alura
☄?️ The minimal, blazing-fast, and infinitely customizable prompt for any shell!
Leon Sans is a geometric sans-serif typeface made with code in 2019 by Jongmin Kim.
Order computer parts from a satellite orbiting around your minecraft world and build actual working computers with them!
An implementation of Clean Architecture for ASP.NET Core 3.1 WebAPI. Built with loosely coupled architecture and clean-code practices in mind.
RISC-V SoC designed by students in UCAS
Code and exercises from Bartosz Milewski's Basics of Haskell Tutorial
GraphQL first full-stack starter kit with Node, React. Powered by TypeScript
UP - DOWN - LEFT - RIGHT movement tracking.
? OSCP Exam Report Template in Markdown
A React Native app - Clone Instagram mobile app (In progress)
Satellite imagery for dummies.
Vim-fork focused on extensibility and usability
A roadmap connecting many of the most important concepts in machine learning, how to learn them and what tools to use to perform them.
Comprehensive Python Cheatsheet
For when people get too hyped up about things
Free and Open Source Reverse Engineering Platform powered by radare2
ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual-Inertial and Multi-Map SLAM
Faster Nmap Scanning with Rust
openpilot is an open source driver assistance system. openpilot performs the functions of Automated Lane Centering and Adaptive Cruise Control for over 85 supported car makes and models.
The remake of the

?让你“爱”上 GitHub,解决访问时图裂、加载慢的问题。
Tetris game built with Angular 10 and Akita ?
UMI Core Go Library
Faster Nmap Scanning with Rust
Raspberry Pi Power Monitor
UMI Core Python Library
The goal of this project is to enable users to create cool web demos using the newly released OpenAI GPT-3 API with just a few lines of Python.
Rust explained using easy English
reNgine is an automated reconnaissance framework meant for gathering information during penetration testing of web applications. reNgine has customizable scan engines, which can be used to scan the we
A curated list of applied machine learning and data science notebooks and libraries across different industries (by @firmai)
UMI Core JS Library
☑️? Get rid of bloatware and clean your Windows 10 Start menu
UMI Core PHP Library
ECMAScript proposal for the Record and Tuple value types. | Stage 2: it will change!
Curated papers, articles & videos on data science & machine learning applied in production, with results.
Implementation of the Filecoin protocol, written in Go
CAT 作为服务端项目基础组件,提供了 Java, C/C++, Node.js, Python, Go 等多语言客户端,已经在美团点评的基础架构中间件框架(MVC框架,RPC框架,数据库框架,缓存框架等,消息队列,配置系统等)深度集成,为美团点评各业务线提供系统丰富的性能指标、健康状况、实时告警等。
Fawkes, privacy preserving tool against facial recognition systems. More info at
The new Windows Terminal and the original Windows console host, all in the same place!
Your window into the Elastic Stack
Terraform enables you to safely and predictably create, change, and improve infrastructure. It is an open source tool that codifies APIs into declarative configuration files that can be shared amongst
Go Training Class Material :
【Java面试+Java学习指南】 一份涵盖大部分Java程序员所需要掌握的核心知识。
? The UI component workshop. Develop, document, & test for React, Vue, Angular, Ember, Web Components, & more!
A curated list of awesome remote jobs and resources. Inspired by
? Collection of Composition API utils for Vue 2 and 3
前端面试每日 3+1,以面试题来驱动学习,提倡每日学习与思考,每天进步一点!每天早上5点纯手工发布面试题(死磕自己,愉悦大家),3000+道前端面试题全面覆盖,HTML/CSS/JavaScript/Vue/React/Nodejs/TypeScript/ECMAScritpt/Webpack/Jquery/小程序/软技能……
Awesome free machine learning and AI courses with video lectures.
The Laravel Boilerplate Project -
List of top 500 ReactJS Interview Questions & Answers....Coding exercise questions are coming soon!!
一个基于 electron 的音乐软件
Number Verifier is a SMS verification tool that makes it easy to get a disposable SMS number and bypass SMS number verifications on any site.
An awesome list of FREE resources for training, conferences, speaking, labs, reading, etc that are free all the time or during COVID-19 that cybersecurity professionals with downtime can take advantag
Specifications for OpenTelemetry
? No bullshit answers to the famous h5bp "Front-end Job Interview Questions"
?????? 本项目包括:1、我写的 30w 字图解算法题典 2、100 张编程类超清晰思维导图 3、100 篇大厂面经汇总 4、各语言编程电子书 100 本 5、小浩算法网站源代码 ( ?? 国人项目上榜不容易,右上角助力一波!干就对了,奥利给 !??)
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
Bypass Paywalls web browser extension for Chrome and Firefox.
A curated list of references for MLOps
Test prompts for OpenAI's GPT-3 API and the resulting AI-generated texts.

Elyra extends JupyterLab Notebooks with an AI centric approach.
Computer vision based ML training data generation tool. ?
? Path to a free self-taught education in Computer Science!
Open Source Web Application Framework for ASP.NET Core
completely free for everyone. Its build-in Flutter Dart.
Vue 3 core documentation
A Minecraft mod designed to improve frame rates and reduce micro-stutter
Puppeteer recorder is a Chrome extension that records your browser interactions and generates a Puppeteer script.
Fully functional Twitter clone built in flutter framework using Firebase realtime database and storage
Experience, Learn and Code the latest breakthrough innovations with Microsoft AI
For empowering community ?
An open source scientific computing environment for JavaScript TOTALLY in your browser, matrix operations with GPU acceleration, TeX support, data visualization and symbolic computation.
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
Библия QA это 163 страницы смеси ответов на вопросы с реальных собеседований на manual QA, перевода интересного контента с зарубежных ресурсов и агрегации материала с отечественных.
? The Cloud-Native API Gateway
?️ Android Pokedex using Dagger Hilt, Motion, Coroutines, Flow, Jetpack (Room, ViewModel, LiveData) based on MVVM architecture.
PS4 6.72 jailbreak
PowerShell for every system!
The FLARE team's open-source tool to identify capabilities in executable files.
React Hooks — ?
A libre lightweight streaming front-end for Android.
Define infrastructure resources using programming constructs and provision them using HashiCorp Terraform
Roadmap to becoming a web developer in 2020
List of Data Science Cheatsheets to rule the world
Android client SDK for communicating with OAuth 2.0 and OpenID Connect providers.
Toturial coming with "data science roadmap" graphe.
Tutorials and programming exercises for learning Q# and quantum computing
Fancy reverse and bind shell handler
jQuery JavaScript Library
Industrial-grade RPC framework used throughout Baidu, with 1,000,000+ instances and thousands kinds of services, called "baidu-rpc" inside Baidu.
A web framework for Rust.
Protocol Buffers - Google's data interchange format
Awesome OCR toolkits based on PaddlePaddle (8.6M ultra-lightweight pre-trained model, support training and deployment among server, mobile, embeded and IoT devices)
Sample queries for Advanced hunting in Microsoft Threat Protection
Reactive Programming in Swift
An open-source digital image forensic toolset
Phaser is a fun, free and fast 2D game framework for making HTML5 games for desktop and mobile web browsers, supporting Canvas and WebGL rendering.
A curated list of awesome Github Profile READMEs
A collection of various awesome lists for hackers, pentesters and security researchers
Papers from the computer science community to read and discuss.
A lightweight RTSP/RTMP/HTTP/HLS/HTTP-FLV/WebSocket-FLV/GB28181 server and client framework based on C++11
Public interface definitions of Google APIs.
Simple (relatively) things allowing you to dig a bit deeper than usual.
? 本代码库是作者小傅哥多年从事一线互联网 Java 开发的学习历程技术汇总,旨在为大家提供一个清晰详细的学习教程,侧重点更倾向编写Java核心内容。如果本仓库能为您提供帮助,请给予支持(关注、点赞、分享)!

Rapidly create UIs for prototyping your machine learning model in 3 minutes
? A SnapChat clone built with React, Redux and Typescript. Styled with SASS. Tested with Cypress, Jest and Enzyme. Linted with Eslint and formatted with Prettier!
? Clean Architecture with .NET Core 3.1, C# 8 and React+Redux. Use cases as central organizing structure, completely testable, decoupled from frameworks
Apache Flink
Full Modular Monolith application with Domain-Driven Design approach.
Practice your pandas skills!
❤️Flutter ❤️ tips and tricks ❤️ Awesome Flutter ❤️ tips and tricks ❤️
Voilà turns Jupyter notebooks into standalone web applications
I developed this application just for learning purpose. There are 20+ screen variations.

Master the command line, in one page
FastAPI framework, high performance, easy to learn, fast to code, ready for production
Academic papers related to fuzzing, binary analysis and exploit dev, that I want to read or have already read
《神经网络与深度学习》 邱锡鹏著 Neural Network and Deep Learning
An opinionated guide on how to become a professional Web/Mobile App Developer.
A collection of tiny XSS Payloads that can be used in different contexts.
100 Days of ML Coding
Youtube Clone Backend (Express + Sequelize)
Build ECommerce Website Like Amazon By React & Node & MongoDB
?A set of enterprise-class UI components based on Ant Design and Blazor WebAssembly.
Deezer source separation library including pretrained models.
Youtube Clone Frontend (React + Redux)
.NET is a cross-platform runtime for cloud, mobile, desktop, and IoT apps.
Apache Pulsar - distributed pub-sub messaging system
???A faster, better and more stable redis desktop manager, compatible with Linux, windows, mac. What's more, it won't crash when loading a large number of keys.
"The mother of all demo apps" — Exemplary fullstack clone powered by React, Angular, Node, Django, and many more ?
Beyond Accuracy: Behavioral Testing of NLP models with CheckList
The PyTorch Implementation based on YOLOv4 of the paper: "Complex-YOLO: Real-time 3D Object Detection on Point Clouds"
Yandex UI Kit build on React and bem-react
The Prometheus monitoring system and time series database.
A collection of awesome readme templates to display on your profile
A SwiftUI Reddit client for macOS Big Sur
Used to integrate the Facebook Platform with your iOS & tvOS apps.
The official home of the Presto distributed SQL query engine for big data
? Amazon Web Services — a practical guide
The AWS Copilot CLI is a tool for developers to build, release and operate production ready containerized applications on Amazon ECS and AWS Fargate.
Moby Project - a collaborative project for the container ecosystem to assemble container-based systems
Differentiable SDE solvers with GPU support and efficient sensitivity analysis.
This project aims to provide a central repository for many useful Tsunami Security Scanner plugins.
MeterSphere 是一站式的开源企业级持续测试平台,涵盖测试跟踪、接口测试、性能测试、团队协作等功能
A fresh and modern Google Contacts manager that integrates with GitHub and Twitter.
A list of SaaS, PaaS and IaaS offerings that have free tiers of interest to devops and infradev
Emscripten: An LLVM-to-Web Compiler
The Java gRPC implementation. HTTP/2 based RPC
Repository for all TeamARES POC code and tools.
Official Matplotlib cheat sheets
The adaptive interface system
 for modern web experiences.
This repository is for active development of the Azure SDK for Python. For consumers of the SDK we recommend visiting our public developer docs at or our
BottlEye is a usermode emulator for the popular anti-cheat BattlEye
CML - Continuous Machine Learning or CI/CD for ML
Framework agnostic toolchain for building highly secure native apps that have tiny binaries and are very fast.
Code for the book Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann.
A hex editor for WeChat/QQ/TIM - PC版微信/QQ/TIM防撤回补丁(我已经看到了,撤回也没用了)
? A well-tested feature-rich modular Firebase implementation for React Native. Supports both iOS & Android platforms for all Firebase services.
Alibaba Dragonwell8 JDK
君の then-then-then 世は Promise で Future
This repository contains source code for the TaBERT model, a pre-trained language model for learning joint representations of natural language utterances and (semi-)structured tables for semantic pars
Dask tutorial
Find pearls on open-source seashore 分享 GitHub 上有趣、入门级的开源项目
COVID Tracker App Repository
Resources, links, projects, and ideas for gardeners tending their digital notes on the public interwebs
ALL IN ONE Hacking Tool For Hackers
An Application built for students to access Notes , Question Papers , Syllabus and Resources for all Subjects of O.U (Osmania University) ??‍?
Docker Cheat Sheet
gamedev blog
CVE-2020-5902 BIG-IP
Summer course content for Neuromatch Academy
Text preprocessing, representation and visualization from zero to hero.
深度学习500问,以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述,以帮助自己及有需要的读者。 全书分为18个章节,50余万字。由于水平有限,书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作,联系[email protected] 版权所有,违权必究 Tan 2018.06
A cross-platform, customizable science fiction terminal emulator with advanced monitoring & touchscreen support.

A powerful JavaScript library for interacting with the Discord API
A curated list of awesome Machine Learning frameworks, libraries and software.
Visualize and compare datasets, target values and associations, with one line of code.
Nice and clean Online Shop app UI by using #Flutter.
Rich is a Python library for rich text and beautiful formatting in the terminal.
? Algorithms and data structures implemented in JavaScript with explanations and links to further readings
Query git repositories with SQL. Uses SQLite virtual tables and go-git
A Non-Euclidean Rendering Engine for 3D scenes.
Rudimentary Roam replica with Org-mode

1000+ Hand-Crafted Go Examples, Exercises, and Quizzes
Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.
jExcel is a lightweight vanilla javascript plugin to create amazing web-based interactive tables and spreadsheets compatible with Excel or any other spreadsheet software.
? A collection of pure bash alternatives to external processes.
Google Research
Course Files for Complete Python 3 Bootcamp Course on Udemy
A book series on JavaScript. @YDKJS on twitter.
Backstage is an open platform for building developer portals
Simple and minimalistic server dashboard
A super-easy, composable, web server framework for warp speeds.
Midway is a Node.js Serverless Framework for front-end/full-stack developers. Build the application for next decade. Works on AWS, Aliyun, Tencent-Cloud and traditional VM/Container.
Ready-to-use OCR with 40+ languages supported including Chinese, Japanese, Korean and Thai
A curated list of awesome Discord communities for programmers
Build cross-platform desktop apps with JavaScript, HTML, and CSS
A database software completely built as JSON files in backend. A powerful, portable and simple database works on top of JSON files. It is like a database software, currently having basic CRUD operatio
Simple and minimalistic server dashboard
App to show cast info for breaking bad

python powered Intelligent System
Repository for tutorial sessions at EEML2020
? A collection of Firebase plugins for Flutter apps.
Firefox Preview
基于Gin + Vue + Element UI的前后端分离权限管理系统脚手架(包含了:基础用户管理功能,jwt鉴权,代码生成器,RBAC资源控制,表单构建等)文档: Demo:
Vite & Vue powered static site generator
Zulip server - powerful open source team chat
If Google News had a Python library
Revive unavailable songs for Netease Cloud Music
YApi 是一个可本地部署的、打通前后端及QA的、可视化的接口管理平台
The plugin-driven server agent for collecting & reporting metrics.
All materials for the Cassandra Workshop Series in a single place
A beautiful Redis GUI ?
Collection of Summer 2021 tech internships!
Cubit is a lightweight state management solution. It is a subset of the bloc package that does not rely on events and instead uses methods to emit new states.
Native-ESM powered web dev build tool. It's fast.
An Electron boilerplate including TypeScript, React, Jest and ESLint.
A modified browser that helps in responsive web development.
Build Mobile, Desktop and WebAssembly apps with C# and XAML. Today. Open source and professionally supported.
React components for faster and easier web development. Build your own design system, or start with Material Design.
Welcome to the Bot Framework samples repository. Here you will find task-focused samples in C#, JavaScript and TypeScript to help you get started with the Bot Framework SDK!
OpenPCDet Toolbox for LiDAR-based 3D Object Detection.
A simplified Jira clone built with Angular 9 and Akita
The ultimate snippets collection for VS Code
Based on a true story
Simple, fast, safe, compiled language for developing maintainable software. Compiles itself in <1s with zero library dependencies.

? React Hooks for forms validation (Web + React Native)
Node Version Manager - POSIX-compliant bash script to manage multiple active node.js versions
开放式跨端跨框架解决方案,支持使用 React/Vue/Nerv 等框架来开发微信/京东/百度/支付宝/字节跳动/ QQ 小程序/H5 等应用。
A GUI frontend for @werman's Pulse Audio real-time noise suppression plugin
Updates to this repository will continue to arrive until the number of links reaches 10000 links & 10000 pdf files .Learn Ethical Hacking and penetration testing .hundreds of ethical hacking & penetra
Blazing fast hexapod robot simulator with React and Plotly.
C++ game engine focusing on modern rendering techniques and performance.
Silice is an open source language that simplifies writing algorithms fully exploiting FPGA architectures.
Python training for business analysts and traders
Official tensorflow implementation for CVPR2020 paper “Learning to Cartoonize Using White-box Cartoon Representations”
Ultimate Go study guide
This is a fun, new monospaced font that includes programming ligatures and is designed to enhance the modern look and feel of the Windows Terminal.
Rolling Rhino; convert Ubuntu into a rolling release as seen on YouTube
A repo for the pre-course work at home exercises
Learn python3 in one picture.
? TensorflowTTS: Real-Time State-of-the-art Speech Synthesis for Tensorflow 2
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
Matplotlib styles for scientific plotting
A pendant to warn you when you touch your face
A collection of all my Flutter Challenges
To-do list & time tracker for programmers & other digital workers with Jira, Github and Gitlab integration
Instant messaging server; backend in Go; iOS, Android, web, command line clients; chatbots
Graph Neural Networks with Keras and Tensorflow 2.
The near-instant build tool for modern web apps.
Books for machine learning, deep learning, math, NLP, CV, RL, etc
? List of awesome university courses for learning Computer Science!
Distributed scheduled job framework
? 互联网 Java 工程师进阶知识完全扫盲:涵盖高并发、分布式、高可用、微服务、海量数据处理等领域知识,后端同学必看,前端同学也可学习
PlayStation 2 DVD Player Exploit
Store SSH keys in the Secure Enclave
Learning Convolutional Neural Networks with Interactive Visualization.
阿里巴巴 MySQL binlog 增量订阅&消费组件
Open Source Computer Vision Library
Gin is a HTTP web framework written in Go (Golang). It features a Martini-like API with much better performance -- up to 40 times faster. If you need smashing performance, get yourself some Gin.
LeetCode Solutions: A Record of My Problem Solving Journey.( leetcode题解,记录自己的leetcode解题之路。)
? Building a federated alternative to reddit in rust
egui: Immediate mode GUI written in Rust, made for WASM
Open screens/snackbars/dialogs/bottomSheets without context, manage states and inject dependencies easily with Get.
beego is an open-source, high-performance web framework for the Go programming language.
A lightweight and ultra-fast tool for building observability pipelines
BBT - Bug Bounty Tools
Example code for HTML, CSS, and Javascript for Web Developers Coursera Course
? HonKit is building beautiful books using Markdown - Fork of GitBook
Display and control your Android device
Build forms in React, without the tears ?
A sandbox tower defense game
ARCore Depth Lab is a set of Depth API samples that provides assets using depth for advanced geometry-aware features in AR interaction and rendering. (UIST 2020)
Virtual-machine Translation Intermediate Language
Free online textbook of Jupyter notebooks for Computational Linear Algebra course
PyTorch implementation of FastSurferCNN
Solar2D Game Engine main repository (ex Corona SDK)
《On Java 8》中文版,又名《Java编程思想》 第5版
A collection of all the data i could extract from 1 billion leaked credentials from internet.
Minimal distributed configuration management in bash
California COVID Assessment Tool
CLI tool for Angular
? fgprof is a sampling Go profiler that allows you to analyze On-CPU as well as Off-CPU (e.g. I/O) time together.
Terraform AWS provider
Finally, a "back to top" button that behaves like a real elevator.
A toolkit for developing high-performance HTTP reverse proxy applications.
One framework. Mobile & desktop.
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AW
Learn the skills required to sysadmin a remote Linux server from the commandline.
A Patch for GIMP 2.10+ for Photoshop Users
Distributed SQL database in Rust, written as a learning project
A cheat sheet that contains common enumeration and attack methods for Windows Active Directory.
Fluent System Icons is a set of mobile platform icons from Microsoft
The PHP Interpreter
A list of Free Software network services and web applications which can be hosted locally. Selfhosting is the process of hosting and managing applications instead of renting from Software-as-a-Service
? Open source machine learning framework to automate text- and voice-based conversations: NLU, dialogue management, connect to Slack, Facebook, and more - Create chatbots and voice assistants
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
A curated awesome list of lists of interview questions. Feel free to contribute! ?
Windows system utilities to maximize productivity
Build a ReactJS App workshop
This cheasheet is aimed at the CTF Players and Beginners to help them understand the fundamentals of Privilege Escalation with examples.
Highly cited and useful papers related to machine learning, deep learning, AI, game theory, reinforcement learning
The Ruby Programming Language [mirror]
? The missing package manager for macOS (or Linux)
[CVPR2020] Adversarial Latent Autoencoders
? A UI Design Language and React UI library
High performance Spigot fork that aims to fix gameplay and mechanics inconsistencies
Learn OpenCV : C++ and Python Examples
A utility-first CSS framework for rapid UI development.
An extremely fast JavaScript bundler and minifier
⚛️ Hooks for fetching, caching and updating asynchronous data in React
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Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.

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The System Design Primer


Learn how to design large-scale systems.

Prep for the system design interview.

Learn how to design large-scale systems

Learning how to design scalable systems will help you become a better engineer.

System design is a broad topic. There is a vast amount of resources scattered throughout the web on system design principles.

This repo is an organized collection of resources to help you learn how to build systems at scale.

Learn from the open source community

This is a continually updated, open source project.

Contributions are welcome!

Prep for the system design interview

In addition to coding interviews, system design is a required component of the technical interview process at many tech companies.

Practice common system design interview questions and compare your results with sample solutions: discussions, code, and diagrams.

Additional topics for interview prep:

Anki flashcards

The provided Anki flashcard decks use spaced repetition to help you retain key system design concepts.

Great for use while on-the-go.

Coding Resource: Interactive Coding Challenges

Looking for resources to help you prep for the Coding Interview?

Check out the sister repo Interactive Coding Challenges, which contains an additional Anki deck:


Learn from the community.

Feel free to submit pull requests to help:

Content that needs some polishing is placed under development.

Review the Contributing Guidelines.

Index of system design topics

Summaries of various system design topics, including pros and cons. Everything is a trade-off.

Each section contains links to more in-depth resources.

Study guide

Suggested topics to review based on your interview timeline (short, medium, long).


Q: For interviews, do I need to know everything here?

A: No, you don't need to know everything here to prepare for the interview.

What you are asked in an interview depends on variables such as:

More experienced candidates are generally expected to know more about system design. Architects or team leads might be expected to know more than individual contributors. Top tech companies are likely to have one or more design interview rounds.

Start broad and go deeper in a few areas. It helps to know a little about various key system design topics. Adjust the following guide based on your timeline, experience, what positions you are interviewing for, and which companies you are interviewing with.

Short Medium Long
Read through the System design topics to get a broad understanding of how systems work :+1: :+1: :+1:
Read through a few articles in the Company engineering blogs for the companies you are interviewing with :+1: :+1: :+1:
Read through a few Real world architectures :+1: :+1: :+1:
Review How to approach a system design interview question :+1: :+1: :+1:
Work through System design interview questions with solutions Some Many Most
Work through Object-oriented design interview questions with solutions Some Many Most
Review Additional system design interview questions Some Many Most

How to approach a system design interview question

How to tackle a system design interview question.

The system design interview is an open-ended conversation. You are expected to lead it.

You can use the following steps to guide the discussion. To help solidify this process, work through the System design interview questions with solutions section using the following steps.

Step 1: Outline use cases, constraints, and assumptions

Gather requirements and scope the problem. Ask questions to clarify use cases and constraints. Discuss assumptions.

Step 2: Create a high level design

Outline a high level design with all important components.

Step 3: Design core components

Dive into details for each core component. For example, if you were asked to design a url shortening service, discuss:

Step 4: Scale the design

Identify and address bottlenecks, given the constraints. For example, do you need the following to address scalability issues?

Discuss potential solutions and trade-offs. Everything is a trade-off. Address bottlenecks using principles of scalable system design.

Back-of-the-envelope calculations

You might be asked to do some estimates by hand. Refer to the Appendix for the following resources:

Source(s) and further reading

Check out the following links to get a better idea of what to expect:

System design interview questions with solutions

Common system design interview questions with sample discussions, code, and diagrams.

Solutions linked to content in the solutions/ folder.

Design (or Solution
Design the Twitter timeline and search (or Facebook feed and search) Solution
Design a web crawler Solution
Design Solution
Design the data structures for a social network Solution
Design a key-value store for a search engine Solution
Design Amazon's sales ranking by category feature Solution
Design a system that scales to millions of users on AWS Solution
Add a system design question Contribute

Design (or

View exercise and solution


Design the Twitter timeline and search (or Facebook feed and search)

View exercise and solution


Design a web crawler

View exercise and solution



View exercise and solution


Design the data structures for a social network

View exercise and solution


Design a key-value store for a search engine

View exercise and solution


Design Amazon's sales ranking by category feature

View exercise and solution


Design a system that scales to millions of users on AWS

View exercise and solution


Object-oriented design interview questions with solutions

Common object-oriented design interview questions with sample discussions, code, and diagrams.

Solutions linked to content in the solutions/ folder.

Note: This section is under development

Design a hash map Solution
Design a least recently used cache Solution
Design a call center Solution
Design a deck of cards Solution
Design a parking lot Solution
Design a chat server Solution
Design a circular array Contribute
Add an object-oriented design question Contribute

System design topics: start here

New to system design?

First, you'll need a basic understanding of common principles, learning about what they are, how they are used, and their pros and cons.

Step 1: Review the scalability video lecture

Scalability Lecture at Harvard

Step 2: Review the scalability article


Next steps

Next, we'll look at high-level trade-offs:

Keep in mind that everything is a trade-off.

Then we'll dive into more specific topics such as DNS, CDNs, and load balancers.

Performance vs scalability

A service is scalable if it results in increased performance in a manner proportional to resources added. Generally, increasing performance means serving more units of work, but it can also be to handle larger units of work, such as when datasets grow.1

Another way to look at performance vs scalability:

Source(s) and further reading

Latency vs throughput

Latency is the time to perform some action or to produce some result.

Throughput is the number of such actions or results per unit of time.

Generally, you should aim for maximal throughput with acceptable latency.

Source(s) and further reading

Availability vs consistency

CAP theorem

Source: CAP theorem revisited

In a distributed computer system, you can only support two of the following guarantees:

Networks aren't reliable, so you'll need to support partition tolerance. You'll need to make a software tradeoff between consistency and availability.

CP - consistency and partition tolerance

Waiting for a response from the partitioned node might result in a timeout error. CP is a good choice if your business needs require atomic reads and writes.

AP - availability and partition tolerance

Responses return the most readily available version of the data available on any node, which might not be the latest. Writes might take some time to propagate when the partition is resolved.

AP is a good choice if the business needs allow for eventual consistency or when the system needs to continue working despite external errors.

Source(s) and further reading

Consistency patterns

With multiple copies of the same data, we are faced with options on how to synchronize them so clients have a consistent view of the data. Recall the definition of consistency from the CAP theorem - Every read receives the most recent write or an error.

Weak consistency

After a write, reads may or may not see it. A best effort approach is taken.

This approach is seen in systems such as memcached. Weak consistency works well in real time use cases such as VoIP, video chat, and realtime multiplayer games. For example, if you are on a phone call and lose reception for a few seconds, when you regain connection you do not hear what was spoken during connection loss.

Eventual consistency

After a write, reads will eventually see it (typically within milliseconds). Data is replicated asynchronously.

This approach is seen in systems such as DNS and email. Eventual consistency works well in highly available systems.

Strong consistency

After a write, reads will see it. Data is replicated synchronously.

This approach is seen in file systems and RDBMSes. Strong consistency works well in systems that need transactions.

Source(s) and further reading

Availability patterns

There are two main patterns to support high availability: fail-over and replication.



With active-passive fail-over, heartbeats are sent between the active and the passive server on standby. If the heartbeat is interrupted, the passive server takes over the active's IP address and resumes service.

The length of downtime is determined by whether the passive server is already running in 'hot' standby or whether it needs to start up from 'cold' standby. Only the active server handles traffic.

Active-passive failover can also be referred to as master-slave failover.


In active-active, both servers are managing traffic, spreading the load between them.

If the servers are public-facing, the DNS would need to know about the public IPs of both servers. If the servers are internal-facing, application logic would need to know about both servers.

Active-active failover can also be referred to as master-master failover.

Disadvantage(s): failover


Master-slave and master-master

This topic is further discussed in the Database section:

Availability in numbers

Availability is often quantified by uptime (or downtime) as a percentage of time the service is available. Availability is generally measured in number of 9s--a service with 99.99% availability is described as having four 9s.

99.9% availability - three 9s

Duration Acceptable downtime
Downtime per year 8h 45min 57s
Downtime per month 43m 49.7s
Downtime per week 10m 4.8s
Downtime per day 1m 26.4s

99.99% availability - four 9s

Duration Acceptable downtime
Downtime per year 52min 35.7s
Downtime per month 4m 23s
Downtime per week 1m 5s
Downtime per day 8.6s

Availability in parallel vs in sequence

If a service consists of multiple components prone to failure, the service's overall availability depends on whether the components are in sequence or in parallel.

In sequence

Overall availability decreases when two components with availability < 100% are in sequence:

Availability (Total) = Availability (Foo) * Availability (Bar)

If both Foo and Bar each had 99.9% availability, their total availability in sequence would be 99.8%.

In parallel

Overall availability increases when two components with availability < 100% are in parallel:

Availability (Total) = 1 - (1 - Availability (Foo)) * (1 - Availability (Bar))

If both Foo and Bar each had 99.9% availability, their total availability in parallel would be 99.9999%.

Domain name system

Source: DNS security presentation

A Domain Name System (DNS) translates a domain name such as to an IP address.

DNS is hierarchical, with a few authoritative servers at the top level. Your router or ISP provides information about which DNS server(s) to contact when doing a lookup. Lower level DNS servers cache mappings, which could become stale due to DNS propagation delays. DNS results can also be cached by your browser or OS for a certain period of time, determined by the time to live (TTL).

Services such as CloudFlare and Route 53 provide managed DNS services. Some DNS services can route traffic through various methods:

Disadvantage(s): DNS

Source(s) and further reading

Content delivery network

Source: Why use a CDN

A content delivery network (CDN) is a globally distributed network of proxy servers, serving content from locations closer to the user. Generally, static files such as HTML/CSS/JS, photos, and videos are served from CDN, although some CDNs such as Amazon's CloudFront support dynamic content. The site's DNS resolution will tell clients which server to contact.

Serving content from CDNs can significantly improve performance in two ways:

Push CDNs

Push CDNs receive new content whenever changes occur on your server. You take full responsibility for providing content, uploading directly to the CDN and rewriting URLs to point to the CDN. You can configure when content expires and when it is updated. Content is uploaded only when it is new or changed, minimizing traffic, but maximizing storage.

Sites with a small amount of traffic or sites with content that isn't often updated work well with push CDNs. Content is placed on the CDNs once, instead of being re-pulled at regular intervals.

Pull CDNs

Pull CDNs grab new content from your server when the first user requests the content. You leave the content on your server and rewrite URLs to point to the CDN. This results in a slower request until the content is cached on the CDN.

A time-to-live (TTL) determines how long content is cached. Pull CDNs minimize storage space on the CDN, but can create redundant traffic if files expire and are pulled before they have actually changed.

Sites with heavy traffic work well with pull CDNs, as traffic is spread out more evenly with only recently-requested content remaining on the CDN.

Disadvantage(s): CDN

Source(s) and further reading

Load balancer

Source: Scalable system design patterns

Load balancers distribute incoming client requests to computing resources such as application servers and databases. In each case, the load balancer returns the response from the computing resource to the appropriate client. Load balancers are effective at:

Load balancers can be implemented with hardware (expensive) or with software such as HAProxy.

Additional benefits include:

To protect against failures, it's common to set up multiple load balancers, either in active-passive or active-active mode.

Load balancers can route traffic based on various metrics, including:

Layer 4 load balancing

Layer 4 load balancers look at info at the transport layer to decide how to distribute requests. Generally, this involves the source, destination IP addresses, and ports in the header, but not the contents of the packet. Layer 4 load balancers forward network packets to and from the upstream server, performing Network Address Translation (NAT).

Layer 7 load balancing

Layer 7 load balancers look at the application layer to decide how to distribute requests. This can involve contents of the header, message, and cookies. Layer 7 load balancers terminate network traffic, reads the message, makes a load-balancing decision, then opens a connection to the selected server. For example, a layer 7 load balancer can direct video traffic to servers that host videos while directing more sensitive user billing traffic to security-hardened servers.

At the cost of flexibility, layer 4 load balancing requires less time and computing resources than Layer 7, although the performance impact can be minimal on modern commodity hardware.

Horizontal scaling

Load balancers can also help with horizontal scaling, improving performance and availability. Scaling out using commodity machines is more cost efficient and results in higher availability than scaling up a single server on more expensive hardware, called Vertical Scaling. It is also easier to hire for talent working on commodity hardware than it is for specialized enterprise systems.

Disadvantage(s): horizontal scaling

Disadvantage(s): load balancer

Source(s) and further reading

Reverse proxy (web server)

Source: Wikipedia

A reverse proxy is a web server that centralizes internal services and provides unified interfaces to the public. Requests from clients are forwarded to a server that can fulfill it before the reverse proxy returns the server's response to the client.

Additional benefits include:

Load balancer vs reverse proxy

Disadvantage(s): reverse proxy

Source(s) and further reading

Application layer

Source: Intro to architecting systems for scale

Separating out the web layer from the application layer (also known as platform layer) allows you to scale and configure both layers independently. Adding a new API results in adding application servers without necessarily adding additional web servers. The single responsibility principle advocates for small and autonomous services that work together. Small teams with small services can plan more aggressively for rapid growth.

Workers in the application layer also help enable asynchronism.


Related to this discussion are microservices, which can be described as a suite of independently deployable, small, modular services. Each service runs a unique process and communicates through a well-defined, lightweight mechanism to serve a business goal. 1

Pinterest, for example, could have the following microservices: user profile, follower, feed, search, photo upload, etc.

Service Discovery

Systems such as Consul, Etcd, and Zookeeper can help services find each other by keeping track of registered names, addresses, and ports. Health checks help verify service integrity and are often done using an HTTP endpoint. Both Consul and Etcd have a built in key-value store that can be useful for storing config values and other shared data.

Disadvantage(s): application layer

Source(s) and further reading


Source: Scaling up to your first 10 million users

Relational database management system (RDBMS)

A relational database like SQL is a collection of data items organized in tables.

ACID is a set of properties of relational database transactions.

There are many techniques to scale a relational database: master-slave replication, master-master replication, federation, sharding, denormalization, and SQL tuning.

Master-slave replication

The master serves reads and writes, replicating writes to one or more slaves, which serve only reads. Slaves can also replicate to additional slaves in a tree-like fashion. If the master goes offline, the system can continue to operate in read-only mode until a slave is promoted to a master or a new master is provisioned.

Source: Scalability, availability, stability, patterns

Disadvantage(s): master-slave replication

Master-master replication

Both masters serve reads and writes and coordinate with each other on writes. If either master goes down, the system can continue to operate with both reads and writes.

Source: Scalability, availability, stability, patterns

Disadvantage(s): master-master replication
Disadvantage(s): replication
Source(s) and further reading: replication


Source: Scaling up to your first 10 million users

Federation (or functional partitioning) splits up databases by function. For example, instead of a single, monolithic database, you could have three databases: forums, users, and products, resulting in less read and write traffic to each database and therefore less replication lag. Smaller databases result in more data that can fit in memory, which in turn results in more cache hits due to improved cache locality. With no single central master serializing writes you can write in parallel, increasing throughput.

Disadvantage(s): federation
Source(s) and further reading: federation


Source: Scalability, availability, stability, patterns

Sharding distributes data across different databases such that each database can only manage a subset of the data. Taking a users database as an example, as the number of users increases, more shards are added to the cluster.

Similar to the advantages of federation, sharding results in less read and write traffic, less replication, and more cache hits. Index size is also reduced, which generally improves performance with faster queries. If one shard goes down, the other shards are still operational, although you'll want to add some form of replication to avoid data loss. Like federation, there is no single central master serializing writes, allowing you to write in parallel with increased throughput.

Common ways to shard a table of users is either through the user's last name initial or the user's geographic location.

Disadvantage(s): sharding
Source(s) and further reading: sharding


Denormalization attempts to improve read performance at the expense of some write performance. Redundant copies of the data are written in multiple tables to avoid expensive joins. Some RDBMS such as PostgreSQL and Oracle support materialized views which handle the work of storing redundant information and keeping redundant copies consistent.

Once data becomes distributed with techniques such as federation and sharding, managing joins across data centers further increases complexity. Denormalization might circumvent the need for such complex joins.

In most systems, reads can heavily outnumber writes 100:1 or even 1000:1. A read resulting in a complex database join can be very expensive, spending a significant amount of time on disk operations.

Disadvantage(s): denormalization
Source(s) and further reading: denormalization

SQL tuning

SQL tuning is a broad topic and many books have been written as reference.

It's important to benchmark and profile to simulate and uncover bottlenecks.

Benchmarking and profiling might point you to the following optimizations.

Tighten up the schema
Use good indices
Avoid expensive joins
Partition tables
Tune the query cache
Source(s) and further reading: SQL tuning


NoSQL is a collection of data items represented in a key-value store, document store, wide column store, or a graph database. Data is denormalized, and joins are generally done in the application code. Most NoSQL stores lack true ACID transactions and favor eventual consistency.

BASE is often used to describe the properties of NoSQL databases. In comparison with the CAP Theorem, BASE chooses availability over consistency.

In addition to choosing between SQL or NoSQL, it is helpful to understand which type of NoSQL database best fits your use case(s). We'll review key-value stores, document stores, wide column stores, and graph databases in the next section.

Key-value store

Abstraction: hash table

A key-value store generally allows for O(1) reads and writes and is often backed by memory or SSD. Data stores can maintain keys in lexicographic order, allowing efficient retrieval of key ranges. Key-value stores can allow for storing of metadata with a value.

Key-value stores provide high performance and are often used for simple data models or for rapidly-changing data, such as an in-memory cache layer. Since they offer only a limited set of operations, complexity is shifted to the application layer if additional operations are needed.

A key-value store is the basis for more complex systems such as a document store, and in some cases, a graph database.

Source(s) and further reading: key-value store

Document store

Abstraction: key-value store with documents stored as values

A document store is centered around documents (XML, JSON, binary, etc), where a document stores all information for a given object. Document stores provide APIs or a query language to query based on the internal structure of the document itself. Note, many key-value stores include features for working with a value's metadata, blurring the lines between these two storage types.

Based on the underlying implementation, documents are organized by collections, tags, metadata, or directories. Although documents can be organized or grouped together, documents may have fields that are completely different from each other.

Some document stores like MongoDB and CouchDB also provide a SQL-like language to perform complex queries. DynamoDB supports both key-values and documents.

Document stores provide high flexibility and are often used for working with occasionally changing data.

Source(s) and further reading: document store

Wide column store

Source: SQL & NoSQL, a brief history

Abstraction: nested map ColumnFamily<RowKey, Columns<ColKey, Value, Timestamp>>

A wide column store's basic unit of data is a column (name/value pair). A column can be grouped in column families (analogous to a SQL table). Super column families further group column families. You can access each column independently with a row key, and columns with the same row key form a row. Each value contains a timestamp for versioning and for conflict resolution.

Google introduced Bigtable as the first wide column store, which influenced the open-source HBase often-used in the Hadoop ecosystem, and Cassandra from Facebook. Stores such as BigTable, HBase, and Cassandra maintain keys in lexicographic order, allowing efficient retrieval of selective key ranges.

Wide column stores offer high availability and high scalability. They are often used for very large data sets.

Source(s) and further reading: wide column store

Graph database

Source: Graph database

Abstraction: graph

In a graph database, each node is a record and each arc is a relationship between two nodes. Graph databases are optimized to represent complex relationships with many foreign keys or many-to-many relationships.

Graphs databases offer high performance for data models with complex relationships, such as a social network. They are relatively new and are not yet widely-used; it might be more difficult to find development tools and resources. Many graphs can only be accessed with REST APIs.

Source(s) and further reading: graph

Source(s) and further reading: NoSQL


Source: Transitioning from RDBMS to NoSQL

Reasons for SQL:

Reasons for NoSQL:

Sample data well-suited for NoSQL:

Source(s) and further reading: SQL or NoSQL


Source: Scalable system design patterns

Caching improves page load times and can reduce the load on your servers and databases. In this model, the dispatcher will first lookup if the request has been made before and try to find the previous result to return, in order to save the actual execution.

Databases often benefit from a uniform distribution of reads and writes across its partitions. Popular items can skew the distribution, causing bottlenecks. Putting a cache in front of a database can help absorb uneven loads and spikes in traffic.

Client caching

Caches can be located on the client side (OS or browser), server side, or in a distinct cache layer.

CDN caching

CDNs are considered a type of cache.

Web server caching

Reverse proxies and caches such as Varnish can serve static and dynamic content directly. Web servers can also cache requests, returning responses without having to contact application servers.

Database caching

Your database usually includes some level of caching in a default configuration, optimized for a generic use case. Tweaking these settings for specific usage patterns can further boost performance.

Application caching

In-memory caches such as Memcached and Redis are key-value stores between your application and your data storage. Since the data is held in RAM, it is much faster than typical databases where data is stored on disk. RAM is more limited than disk, so cache invalidation algorithms such as least recently used (LRU) can help invalidate 'cold' entries and keep 'hot' data in RAM.

Redis has the following additional features:

There are multiple levels you can cache that fall into two general categories: database queries and objects:

Generally, you should try to avoid file-based caching, as it makes cloning and auto-scaling more difficult.

Caching at the database query level

Whenever you query the database, hash the query as a key and store the result to the cache. This approach suffers from expiration issues:

Caching at the object level

See your data as an object, similar to what you do with your application code. Have your application assemble the dataset from the database into a class instance or a data structure(s):

Suggestions of what to cache:

When to update the cache

Since you can only store a limited amount of data in cache, you'll need to determine which cache update strategy works best for your use case.


Source: From cache to in-memory data grid

The application is responsible for reading and writing from storage. The cache does not interact with storage directly. The application does the following:

def get_user(self, user_id):
    user = cache.get("user.{0}", user_id)
    if user is None:
        user = db.query("SELECT * FROM users WHERE user_id = {0}", user_id)
        if user is not None:
            key = "user.{0}".format(user_id)
            cache.set(key, json.dumps(user))
    return user

Memcached is generally used in this manner.

Subsequent reads of data added to cache are fast. Cache-aside is also referred to as lazy loading. Only requested data is cached, which avoids filling up the cache with data that isn't requested.

Disadvantage(s): cache-aside


Source: Scalability, availability, stability, patterns

The application uses the cache as the main data store, reading and writing data to it, while the cache is responsible for reading and writing to the database:

Application code:

set_user(12345, {"foo":"bar"})

Cache code:

def set_user(user_id, values):
    user = db.query("UPDATE Users WHERE id = {0}", user_id, values)
    cache.set(user_id, user)

Write-through is a slow overall operation due to the write operation, but subsequent reads of just written data are fast. Users are generally more tolerant of latency when updating data than reading data. Data in the cache is not stale.

Disadvantage(s): write through

Write-behind (write-back)

Source: Scalability, availability, stability, patterns

In write-behind, the application does the following:

Disadvantage(s): write-behind


Source: From cache to in-memory data grid

You can configure the cache to automatically refresh any recently accessed cache entry prior to its expiration.

Refresh-ahead can result in reduced latency vs read-through if the cache can accurately predict which items are likely to be needed in the future.

Disadvantage(s): refresh-ahead

Disadvantage(s): cache

Source(s) and further reading


Source: Intro to architecting systems for scale

Asynchronous workflows help reduce request times for expensive operations that would otherwise be performed in-line. They can also help by doing time-consuming work in advance, such as periodic aggregation of data.

Message queues

Message queues receive, hold, and deliver messages. If an operation is too slow to perform inline, you can use a message queue with the following workflow:

The user is not blocked and the job is processed in the background. During this time, the client might optionally do a small amount of processing to make it seem like the task has completed. For example, if posting a tweet, the tweet could be instantly posted to your timeline, but it could take some time before your tweet is actually delivered to all of your followers.

Redis is useful as a simple message broker but messages can be lost.

RabbitMQ is popular but requires you to adapt to the 'AMQP' protocol and manage your own nodes.

Amazon SQS is hosted but can have high latency and has the possibility of messages being delivered twice.

Task queues

Tasks queues receive tasks and their related data, runs them, then delivers their results. They can support scheduling and can be used to run computationally-intensive jobs in the background.

Celery has support for scheduling and primarily has python support.

Back pressure

If queues start to grow significantly, the queue size can become larger than memory, resulting in cache misses, disk reads, and even slower performance. Back pressure can help by limiting the queue size, thereby maintaining a high throughput rate and good response times for jobs already in the queue. Once the queue fills up, clients get a server busy or HTTP 503 status code to try again later. Clients can retry the request at a later time, perhaps with exponential backoff.

Disadvantage(s): asynchronism

Source(s) and further reading


Source: OSI 7 layer model

Hypertext transfer protocol (HTTP)

HTTP is a method for encoding and transporting data between a client and a server. It is a request/response protocol: clients issue requests and servers issue responses with relevant content and completion status info about the request. HTTP is self-contained, allowing requests and responses to flow through many intermediate routers and servers that perform load balancing, caching, encryption, and compression.

A basic HTTP request consists of a verb (method) and a resource (endpoint). Below are common HTTP verbs:

Verb Description Idempotent* Safe Cacheable
GET Reads a resource Yes Yes Yes
POST Creates a resource or trigger a process that handles data No No Yes if response contains freshness info
PUT Creates or replace a resource Yes No No
PATCH Partially updates a resource No No Yes if response contains freshness info
DELETE Deletes a resource Yes No No

*Can be called many times without different outcomes.

HTTP is an application layer protocol relying on lower-level protocols such as TCP and UDP.

Source(s) and further reading: HTTP

Transmission control protocol (TCP)

Source: How to make a multiplayer game

TCP is a connection-oriented protocol over an IP network. Connection is established and terminated using a handshake. All packets sent are guaranteed to reach the destination in the original order and without corruption through:

If the sender does not receive a correct response, it will resend the packets. If there are multiple timeouts, the connection is dropped. TCP also implements flow control and congestion control. These guarantees cause delays and generally result in less efficient transmission than UDP.

To ensure high throughput, web servers can keep a large number of TCP connections open, resulting in high memory usage. It can be expensive to have a large number of open connections between web server threads and say, a memcached server. Connection pooling can help in addition to switching to UDP where applicable.

TCP is useful for applications that require high reliability but are less time critical. Some examples include web servers, database info, SMTP, FTP, and SSH.

Use TCP over UDP when:

User datagram protocol (UDP)

Source: How to make a multiplayer game

UDP is connectionless. Datagrams (analogous to packets) are guaranteed only at the datagram level. Datagrams might reach their destination out of order or not at all. UDP does not support congestion control. Without the guarantees that TCP support, UDP is generally more efficient.

UDP can broadcast, sending datagrams to all devices on the subnet. This is useful with DHCP because the client has not yet received an IP address, thus preventing a way for TCP to stream without the IP address.

UDP is less reliable but works well in real time use cases such as VoIP, video chat, streaming, and realtime multiplayer games.

Use UDP over TCP when:

Source(s) and further reading: TCP and UDP

Remote procedure call (RPC)

Source: Crack the system design interview

In an RPC, a client causes a procedure to execute on a different address space, usually a remote server. The procedure is coded as if it were a local procedure call, abstracting away the details of how to communicate with the server from the client program. Remote calls are usually slower and less reliable than local calls so it is helpful to distinguish RPC calls from local calls. Popular RPC frameworks include Protobuf, Thrift, and Avro.

RPC is a request-response protocol:

Sample RPC calls:

GET /someoperation?data=anId

POST /anotheroperation
  "anotherdata": "another value"

RPC is focused on exposing behaviors. RPCs are often used for performance reasons with internal communications, as you can hand-craft native calls to better fit your use cases.

Choose a native library (aka SDK) when:

HTTP APIs following REST tend to be used more often for public APIs.

Disadvantage(s): RPC

Representational state transfer (REST)

REST is an architectural style enforcing a client/server model where the client acts on a set of resources managed by the server. The server provides a representation of resources and actions that can either manipulate or get a new representation of resources. All communication must be stateless and cacheable.

There are four qualities of a RESTful interface:

Sample REST calls:

GET /someresources/anId

PUT /someresources/anId
{"anotherdata": "another value"}

REST is focused on exposing data. It minimizes the coupling between client/server and is often used for public HTTP APIs. REST uses a more generic and uniform method of exposing resources through URIs, representation through headers, and actions through verbs such as GET, POST, PUT, DELETE, and PATCH. Being stateless, REST is great for horizontal scaling and partitioning.

Disadvantage(s): REST

RPC and REST calls comparison

Operation RPC REST
Signup POST /signup POST /persons
Resign POST /resign
"personid": "1234"
DELETE /persons/1234
Read a person GET /readPerson?personid=1234 GET /persons/1234
Read a person’s items list GET /readUsersItemsList?personid=1234 GET /persons/1234/items
Add an item to a person’s items POST /addItemToUsersItemsList
"personid": "1234";
"itemid": "456"
POST /persons/1234/items
"itemid": "456"
Update an item POST /modifyItem
"itemid": "456";
"key": "value"
PUT /items/456
"key": "value"
Delete an item POST /removeItem
"itemid": "456"
DELETE /items/456

Source: Do you really know why you prefer REST over RPC

Source(s) and further reading: REST and RPC


This section could use some updates. Consider contributing!

Security is a broad topic. Unless you have considerable experience, a security background, or are applying for a position that requires knowledge of security, you probably won't need to know more than the basics:

Source(s) and further reading


You'll sometimes be asked to do 'back-of-the-envelope' estimates. For example, you might need to determine how long it will take to generate 100 image thumbnails from disk or how much memory a data structure will take. The Powers of two table and Latency numbers every programmer should know are handy references.

Powers of two table

Power           Exact Value         Approx Value        Bytes
7                             128
8                             256
10                           1024   1 thousand           1 KB
16                         65,536                       64 KB
20                      1,048,576   1 million            1 MB
30                  1,073,741,824   1 billion            1 GB
32                  4,294,967,296                        4 GB
40              1,099,511,627,776   1 trillion           1 TB

Source(s) and further reading

Latency numbers every programmer should know

Latency Comparison Numbers
L1 cache reference                           0.5 ns
Branch mispredict                            5   ns
L2 cache reference                           7   ns                      14x L1 cache
Mutex lock/unlock                           25   ns
Main memory reference                      100   ns                      20x L2 cache, 200x L1 cache
Compress 1K bytes with Zippy            10,000   ns       10 us
Send 1 KB bytes over 1 Gbps network     10,000   ns       10 us
Read 4 KB randomly from SSD*           150,000   ns      150 us          ~1GB/sec SSD
Read 1 MB sequentially from memory     250,000   ns      250 us
Round trip within same datacenter      500,000   ns      500 us
Read 1 MB sequentially from SSD*     1,000,000   ns    1,000 us    1 ms  ~1GB/sec SSD, 4X memory
Disk seek                           10,000,000   ns   10,000 us   10 ms  20x datacenter roundtrip
Read 1 MB sequentially from 1 Gbps  10,000,000   ns   10,000 us   10 ms  40x memory, 10X SSD
Read 1 MB sequentially from disk    30,000,000   ns   30,000 us   30 ms 120x memory, 30X SSD
Send packet CA->Netherlands->CA    150,000,000   ns  150,000 us  150 ms

1 ns = 10^-9 seconds
1 us = 10^-6 seconds = 1,000 ns
1 ms = 10^-3 seconds = 1,000 us = 1,000,000 ns

Handy metrics based on numbers above:

Latency numbers visualized

Source(s) and further reading

Additional system design interview questions

Common system design interview questions, with links to resources on how to solve each.

Question Reference(s)
Design a file sync service like Dropbox
Design a search engine like Google
Design a scalable web crawler like Google
Design Google docs
Design a key-value store like Redis
Design a cache system like Memcached
Design a recommendation system like Amazon's
Design a tinyurl system like Bitly
Design a chat app like WhatsApp
Design a picture sharing system like Instagram
Design the Facebook news feed function
Design the Facebook timeline function
Design the Facebook chat function
Design a graph search function like Facebook's
Design a content delivery network like CloudFlare
Design a trending topic system like Twitter's
Design a random ID generation system
Return the top k requests during a time interval
Design a system that serves data from multiple data centers
Design an online multiplayer card game
Design a garbage collection system
Design an API rate limiter
Add a system design question Contribute

Real world architectures

Articles on how real world systems are designed.

Source: Twitter timelines at scale

Don't focus on nitty gritty details for the following articles, instead:

Type System Reference(s)
Data processing MapReduce - Distributed data processing from Google
Data processing Spark - Distributed data processing from Databricks
Data processing Storm - Distributed data processing from Twitter
Data store Bigtable - Distributed column-oriented database from Google
Data store HBase - Open source implementation of Bigtable
Data store Cassandra - Distributed column-oriented database from Facebook
Data store DynamoDB - Document-oriented database from Amazon
Data store MongoDB - Document-oriented database
Data store Spanner - Globally-distributed database from Google
Data store Memcached - Distributed memory caching system
Data store Redis - Distributed memory caching system with persistence and value types
File system Google File System (GFS) - Distributed file system
File system Hadoop File System (HDFS) - Open source implementation of GFS
Misc Chubby - Lock service for loosely-coupled distributed systems from Google
Misc Dapper - Distributed systems tracing infrastructure
Misc Kafka - Pub/sub message queue from LinkedIn
Misc Zookeeper - Centralized infrastructure and services enabling synchronization
Add an architecture Contribute

Company architectures

Company Reference(s)
Amazon Amazon architecture
Cinchcast Producing 1,500 hours of audio every day
DataSift Realtime datamining At 120,000 tweets per second
DropBox How we've scaled Dropbox
ESPN Operating At 100,000 duh nuh nuhs per second
Google Google architecture
Instagram 14 million users, terabytes of photos
What powers Instagram Justin.Tv's live video broadcasting architecture
Facebook Scaling memcached at Facebook
TAO: Facebook’s distributed data store for the social graph
Facebook’s photo storage
How Facebook Live Streams To 800,000 Simultaneous Viewers
Flickr Flickr architecture
Mailbox From 0 to one million users in 6 weeks
Netflix A 360 Degree View Of The Entire Netflix Stack
Netflix: What Happens When You Press Play?
Pinterest From 0 To 10s of billions of page views a month
18 million visitors, 10x growth, 12 employees
Playfish 50 million monthly users and growing
PlentyOfFish PlentyOfFish architecture
Salesforce How they handle 1.3 billion transactions a day
Stack Overflow Stack Overflow architecture
TripAdvisor 40M visitors, 200M dynamic page views, 30TB data
Tumblr 15 billion page views a month
Twitter Making Twitter 10000 percent faster
Storing 250 million tweets a day using MySQL
150M active users, 300K QPS, a 22 MB/S firehose
Timelines at scale
Big and small data at Twitter
Operations at Twitter: scaling beyond 100 million users
How Twitter Handles 3,000 Images Per Second
Uber How Uber scales their real-time market platform
Lessons Learned From Scaling Uber To 2000 Engineers, 1000 Services, And 8000 Git Repositories
WhatsApp The WhatsApp architecture Facebook bought for $19 billion
YouTube YouTube scalability
YouTube architecture

Company engineering blogs

Architectures for companies you are interviewing with.

Questions you encounter might be from the same domain.

Source(s) and further reading

Looking to add a blog? To avoid duplicating work, consider adding your company blog to the following repo:

Under development

Interested in adding a section or helping complete one in-progress? Contribute!


Credits and sources are provided throughout this repo.

Special thanks to:

Contact info

Feel free to contact me to discuss any issues, questions, or comments.

My contact info can be found on my GitHub page.


I am providing code and resources in this repository to you under an open source license. Because this is my personal repository, the license you receive to my code and resources is from me and not my employer (Facebook).

Copyright 2017 Donne Martin

Creative Commons Attribution 4.0 International License (CC BY 4.0)