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Intelligent Tutoring System (ITS)

Description

Intelligent Tutoring System (ITS) is a platform that can provide high-level feedbacks to coding assignment automatically. It aims to alleviate the workload required for grading coding assignments.

Project Structure

This project represents the frontend user interfaces of the ITS platform. We are running microservice architecture on the project:

├── backend
│ ├── assignment-service
│ ├── user-service
| └── grading-service
├── frontend
├── package.json
├── LICENSE
├── docker-compose.yml
├── .gitignore
└── README.md

Prerequisites

Before running the project, make sure you have access to the following:

Local Development

Follow these steps to set up and run the project for local development:

  1. Clone the repository: git clone https://github.com/tryyang2001/CS3213-Frontend-Management-System.git
  2. Copy .env files obtained from the drive into directories: frontend, backend/assignment-service, backend/user-service, and backend/grading-service respectively
  3. At the root directory, run yarn setup to install all dependencies for all microservices. Take note that this process might take longer to finish (< 10 mins)
  4. At the root directory, you may start the development server: yarn dev

To run service individually, you will need to change path directory to the target directory, and follow by yarn dev. For example, to run only assignment-service:

cd backend/assignment-service
yarn dev

Production Build

There are 2 ways to run production build in local environment

Run the project using yarn

Follow these steps to build and run the project in production environment:

  1. Follow steps 1, 2, and 3 in local development for setting up the project
  2. At the root directory, you may start the server by running yarn start

Run the project using Docker Engine:

Follow these steps to build and run the project in production environment:

  1. Clone the repository: git clone https://github.com/tryyang2001/CS3213-Frontend-Management-System.git
  2. Copy .env files obtained from the drive into directories: frontend, backend/assignment-service, backend/user-service, and backend/grading-service respectively
  3. Ensure you have Docker Engine installed, if not check out Docker documentation on how to install Docker Engine. Open Docker Engine
  4. At the root directory run docker-compose up
  5. After all containers are up, run the application at localhost:80

Deployment

We are using Containers as an Application (CaaS) approach for our microservices deployment. We chose Azure as the cloud platform with its Azure Container Registry (ACR) for pushing/storing/pulling build images and Azure Kubernetes Service (AKS) for orchestration between services and setting up API gateway using ingress-nginx. The steps of our deployment:

  1. Authenticate with Azure/ACR/AKS
  2. Build images for each microservices and push them to ACR
  3. Execute kuberenetes manifest files in k8s/startup.yaml to set up services/deployment and ingress-nginx

You can find the similar deploying flow in our Continuous Deployment (CD) in .github/workflows/CD_to_AKS.yml

Contact

If you encountered any problem or need clarification from the developers, kindly contact [email protected].