This repository provides necessary artefacts to quicky and easily deploy an MLflow Tracking server on Azure.
MLflow is an open source platform for managing the end-to-end machine learning lifecycle.
All deployment options come with an automated deployment script. Select one of the following for deployment instructions/scripts:
- Deploy to Azure Container Instances (ACI)
- Deploy to Azure Kubernetes Service (AKS)
- Azure Ubuntu Virtual Machine - TODO
DISCLAIMER: These deployment scripts do not come with security measures in place. As per recommendation from MLflow documentation:
If running a server in production, we would recommend not exposing the built-in server broadly (as it is unauthenticated and unencrypted), and instead putting it behind a reverse proxy like NGINX or Apache httpd, or connecting over VPN.