ecoai-app

Sample e-commerce microservices app that is used for live project demos and experiments. The app demonstrates a realistic scenario using a polyglot architecture, event-driven design, and common open source back-end services such as RabbitMQ and MongoDB. Additionally, the application uses OpenAI's GPT-3 models to generate product descriptions. This can be done using either Azure OpenAI or OpenAI.

This application is inspired by another demo app called Red Dog.

Note

This is not meant to be an example of perfect code to be used in production, but more about showing a realistic application running in AKS.

Architecture

The application has the following services:

Service	Description
makeline-service	This service handles processing orders from the queue and completing them (Golang)
order-service	This service is used for placing orders (Javascript)
product-service	This service is used to perform CRUD operations on products (Rust)
store-front	Web app for customers to place orders (Vue.js)
store-admin	Web app used by store employees to view orders in queue and manage products (Vue.js)
virtual-customer	Simulates order creation on a scheduled basis (Rust)
virtual-worker	Simulates order completion on a scheduled basis (Rust)
ai-service	Optional service for adding generative text and graphics creation (Python)
mongodb	MongoDB instance for persisted data
rabbitmq	RabbitMQ for an order queue

Run the app locally using Docker

The application is designed to be run in Kubernetes, but can also be run locally using Docker Compose.

Tip

You must have Docker Desktop tool, such as Orbstack or Docker Desktop, installed to run this app locally.

To run this app locally:

1. Configure your Azure OpenAI or OpenAI API keys in docker-compose.yml using the environment variables in the ai-service section:

  ai-service:
    build: src/ai-service
    container_name: 'ai-service'
    ...
    environment:
      - USE_AZURE_OPENAI=True # set to False if you are not using Azure OpenAI
      - AZURE_OPENAI_DEPLOYMENT_NAME= # required if using Azure OpenAI
      - AZURE_OPENAI_ENDPOINT= # required if using Azure OpenAI
      - OPENAI_API_KEY= # always required
      - OPENAI_ORG_ID= # required if using OpenAI
    ...

Alternatively, if you do not have access to Azure OpenAI or OpenAI API keys, you can run the app without the ai-service by commenting out the ai-service section in docker-compose.yml. For example:

#  ai-service:
#    build: src/ai-service
#    container_name: 'ai-service'
...
#    networks:
#      - backend_services

Start the app using docker compose. For example:

docker compose up

If everything goes well, you can access the result containers in your desktop tool. The following screenshots are taken from my local Orbstack:

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To stop the app, you can hit the CTRL+C key combination in the terminal window where the app is running.