docs: Add readme

README.md

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 # miaosha
- Personal project
+Miaosha is a product-selling website which can handle the traffic from a million of users. My backend system can reach 20,000 QPS with 8 t3.nano instances and maintain 300,000 WebSocket connections with 6 t3a.small instances.
+
+- Website Link: https://miaosha.click/
+- Explanation Video: https://drive.google.com/file/d/1Y3m75dhT6n5ikO_NZSxNYeaZeiIZEPPO/view?usp=sharing
+
+## Login
+
+- email: [email protected]
+- password: demodemo
+
+## Table of Contents
+
+- [Main Features](#main-features)
+- [Backend Technique](#backend-technique)
+  - [Infrastructure](#infrastructure)
+  - [Environment](#environment)
+  - [Database](#database)
+  - [Cloud Services](#cloud-services)
+  - [Networking](#networking)
+  - [Test](#test)
+  - [Third Party Library](#third-party-library)
+  - [Version Control](#version-control)
+  - [Key Points](#key-points)
+- [Architecture](#architecture)
+- [Database Schema](#database-schema)
+- [Frontend Technique](#frontend-technique)
+  - [React (hook)](#react-hook)
+  - [React Router](#react-router)
+  - [Redux (redux-toolkit)](#redux-redux-toolkit)
+  - [Tailwind CSS, Tailwind UI](#tailwind-css-tailwind-ui)
+  - [Third-Party Modules](#third-party-library-1)
+  - [Cloud Services](#cloud-services-1)
+- [API Doc](#api-doc)
+- [Contact](#contact)
+
+## Main Features
+
+- Actively informed users with WebSocket instead of short polling to decrease API requests
+- Improved API efficiency by processing asynchronously with RabbitMQ
+- Use socket.io for real time co-editing.
+- Achieved high concurrency with distributed system including Publisher, Consumer, MySQL read replica, and Redis cluster
+- Routed high traffic API and general API to different EC2 target groups with Elastic Load Balancer to ensure the stability of other API
+- Prevent overselling with atomic operation in Redis and short-TTL JWT
+- Sent emails asynchronously with SQS and Lambda
+- Complete queuing system with RabbitMQ (Dead letter exchange)
+- Used EventBridge to schedule Lambda to start EC2 before each event
+- Prevented malicious attacks using Nginx’s rate limiter
+- Applied CloudFront as CDN to reduce bandwidth loading and latency
+- Packaged Miaosha system in Docker Compose as development environment, including Node.js, MySQL, Redis cluster, RabbitMQ, and phpMyAdmin
+- Continuously deployed with GitHub Actions and Docker Hub
+- Performed unit test and integration test by Jest and Supertest
+
+
+## Backend Technique
+
+### Environment
+
+- Node.js/Express
+- WebSocket (Socket.IO)
+- PM2
+
+### Server
+- EC2
+- Elastic Load Balancer
+- Auto scaling
+### Web server
+- Nginx
+
+### Serverless
+- Lambda
+- EventBridge
+
+### Database
+
+- RDS (MySQL) with read replica
+- phpMyAdmin
+
+### Cache
+- ElastiCache (Redis cluster)
+
+### Message Broker
+- RabbitMQ
+
+### Container
+- Docker
+- Docker Compose
+
+### Continuous delivery
+- GitHub Action
+- Docker Hub
+
+### CDN
+- CloudFront
+
+### Others
+- S3
+- Route53
+
+### Test
+- Unit test: Jest, Supertest
+
+## System design
+
+## Architecture
+- Server Architecture
+
+## Database Schema
+## How to prevent overselling
+Tools: Redis, JWT token
+
+- Use atomic operation in redis to prevent race condition
+- Prevent .......
+
+## Send email asynchronously
+When an user successfully pays, my backend system 
+would 
+## How to prevent robot attack
+## Decrease API response time with asynchronous processing
+
+## How to ensure the stability of other API (login, checkout) when miaosha activity starts?
+
+## Queuing System
+
+- Limit the number of people visiting the event selling page to prevent server crashes.
+- Apply "queuing psychology" and calculate the estimated waiting time for each user by using **WebSocket** and **Redis** List & Hash.
+
+### How do I implement the queuing system?
+
+Tool: Redis (List & Hash)
+
+1. Use List to record the order of people entering ticket selling page.
+2. Use Hash to record the timestamp of each user entering the ticket selling page.
+3. If the number of people inside the page reaches the limit, another list will record the queuing order.
+4. There is a 10-minute time limit for the purchasing process. Use the index to find the corresponding user that each queuing user should wait for and calculate the estimated waiting time.
+
+## Queuing System
+
+## Continuous Deployment
+
+## Load Test
+Concert ticket selling website must be capable of handling high traffic.
+
+I use WebSocket to confirm if a user is still on the page or in the queue, so I implemented a load test to check the max socket connections with both horizontal and vertical scaling and compared two scaling results & costs.
+
+Code: https://github.com/Claudia-teng/ticket-club-load-test/blob/main/connection-time.js
+
+### Horizontal Scaling
+
+### Vertical Scaling
+
+## How to start 
+
+## Future Features