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Go High Concurrency Flash Sale

Project Structure

  1. model
  2. repositories
  3. services
  4. controllers
  5. views

Sample Page:

data_flow

Data Flow

data_flow

Improvements

Object-Relationl Mapping

  • Built mapping between relational databases and objects using GORM.

Bidirectional Encryption

  • Use Cookie instead of Session to reduce request consumption under heavy traffic.
  • Encrypt Cookie with Advanced Encryption Standard(AES-128).

Distributed System

  • Server Load Balancer(SLB) - Consistent Hashing
  • Add virtual server node on the hash ring to ensure fairness.
  • Use Binary Search to find the IP address of the corresponding server according to the hash value of key to realize SLB.

RabbitMQ

  • Use RabbitMQ instead of Redis to improve the Queries Per Second(QPS) of each product.

Traffic Control

  1. Front-end
  • Users must log in before shopping.
  • Users can only click the purchase button once every 10 seconds.

    wait

  • Captcha: verification is required when click buy-now-button and refresh captcha frequently.

    captcha


    If verification failed, users cannot buy the product and has to re-try captcha.

    captcha_verification_fail


    If verification succeed and meet other flash sale restriction, it will show

    captcha_success

  1. Back-end
  • Server responds to requests every 10 seconds.
  • Add blacklist.
  • Add Token Bucket:
    "/check" : time/rate, token is generated every millisecond and token bucket size is 1000.
    "/product" : middleware, token is generated every millisecond and token bucket size is 10000.
  • Limited access time: Access to the sale page not within a specific time period will be denied.

    access_deny

Test

Servers

  1. Server Zone: Malaysia (Kuala Lumpur)

  2. Server Image: CentOS 7.6 64 bit, 1vCPU(s) 512 MB memory

  3. Maximum Bandwidth: 100Mbps

  4. IP Addresses

    Server Name Intranet IP Public IP
    Validate1 + SLB 172.26.194.42 47.250.49.25
    Validate2 + SLB 172.26.194.41 47.250.147.115
    Stress Test 172.17.169.89 47.250.131.235
    Quantity Control 172.26.194.43 47.250.144.234
    RabbitMQ Simple 172.17.169.88 47.254.251.25

  5. Cross Compile

GOOS=linux GOARCH=amd64 go build xxx.go

WRK

Set product number 10000, WRK result:

data_flow

RabbitMQ queue information:

data_flow

The 10,000 flash sale products were sold within 10 seconds. Quantity control is functioning properly. The bottleneck of running is the publishing rate of RabbitMQ. When the product number is large, we can set the Rabbitmq queue for every 100 requests.

Environment

Go 1.18.1 arm64
Iris 11.1.1
Gorm 1.25.0
Mysql 8.0.31
RabbitMQ 3.11.11