Deploying MLflow Open-Source Machine Learning Experiment Tracking on Ubuntu 24.04

Short summary

This tutorial shows how to deploy MLflow, an open-source ML experiment tracker, on Ubuntu using Docker Compose with PostgreSQL, S3 artifact storage, basic auth, and Traefik for automatic HTTPS. It includes complete configuration files and a working scikit-learn example. By the end, you'll have a production-ready MLflow instance running securely at your custom domain with full experiment tracking and model registry.

• •Complete step-by-step guide to deploy MLflow using Docker Compose with PostgreSQL backend and S3-compatible storage
• •Includes authentication, HTTPS via Traefik, and a working scikit-learn ML experiment example
• •Targeted at product and data teams needing production-grade experiment tracking and model registry infrastructure

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