Deploy a production MLflow tracking server backed by PostgreSQL for run metadata and S3 for artifacts. Includes docker-compose setup, basic auth proxy and Python client configuration.
A hardened redis.conf for production use: disabled commands, maxmemory with LRU eviction, combined RDB + AOF persistence, bind to localhost, and requirepass authentication.