MLflow On-Premise Deployment using Docker Compose

Easily deploy an MLflow tracking server with 1 command.

MinIO S3 is used as the artifact store and PostgreSQL server is used as the backend store.

How to run

1. Clone this repository

   git clone https://github.com/rihal-om/mlflow-server.git
   

2. cd into the mlflow-server directory

3. Build and run the containers with docker-compose

   docker-compose up -d --build
   

4. Access MLflow UI with http://localhost:5000

5. Access MinIO UI with http://localhost:9002

6. Access FastAPI docs with http://localhost:8008/docs

Containerization

The MLflow tracking server is composed of 5 docker containers:

• MLflow server
• MLflow server config
• MinIO object storage server
• MinIO create bucket
• PostgreSQL database server
• FastAPI server