AbhishekRS4 / ML_multi_app_deployment

A project with multi app deployment for ML with docker. A frontend with streamlit and a backend with FastAPI.

ML multi app deployment

Info

• A machine learning project deployment scenario with multiple applications / docker containers
• The main code for training the model can be found in another repo
• The project involves a streamlit application for the frontend and a FastAPI application for the backend / ML service

Backend

• Run the following command to build the container for backend

cd backend/
docker build -t ml_water_potability_backend -f backend.dockerfile .

Frontend

• Run the following command to build the container for frontend

cd frontend/
docker build -t ml_water_potability_frontend -f frontend.dockerfile .

Deployment with docker-compose (locally)

• Run the following command (in the same directory with the docker-compose.yaml file) to deploy and run both the containers

docker-compose up