Easily deploy an MLflow tracking server with docker-compose.
MinIO S3 is used as the artifact store and MySQL server is used as the backend store.
Build and run the containers with docker-compose
```
docker network create mlflow
chmod +x wait-for-it.sh
docker-compose up -d --build
```
Access MLflow UI with http://localhost:5000 Access MinIO UI with http://localhost:9000
The MLflow tracking server is composed of 3 docker containers:
- MLflow server
- MinIO object storage server
- MySQL database server
An addiotional Minio/mc container is run in order to set-up an mlflow bucket.
Based on the repo https://github.com/sachua/mlflow-docker-compose.git