Aim self-hosted ML experiment tracking on Ubuntu 24.04 LTS by cloudimg. Log training runs, metrics and hyperparameters from your Python training code and compare them in a fast web UI, a self-hosted alternative to hosted experiment trackers. nginx on port 80 with a per-VM web UI password on first boot; the durable repository lives on a dedicated data disk. A demo experiment is seeded on first boot. Apache-2.0 licensed.
Aim is an open source ML experiment tracker. Your training code logs metrics, hyperparameters and other artifacts as it runs, and Aim's fast web UI lets you browse, filter and compare those runs afterwards, a self-hosted alternative to hosted experiment trackers. The cloudimg image installs the pinned official Aim 3.29.1 pip package into a dedicated virtual environment and runs the built in web UI and API server as a dedicated aim systemd service. Aim itself is bound to loopback only; nginx does all customer facing work on port 80, behind a per-VM HTTP Basic Auth gate whose password is generated uniquely on first boot. An unauthenticated healthz endpoint on port 80 supports Azure Load Balancer probes. A small demo experiment with three runs and varying hyperparameters and metric curves is seeded on first boot so the runs table, metrics chart, run detail and hyperparameters views all show real data immediately. The Aim repository lives on a dedicated 20 GiB Azure data disk and is genuinely durable, RocksDB backed, surviving service restarts and VM reboots, unlike an in memory store. Apache-2.0 licensed, free of per-run or per-seat fees. The cloudimg charge covers packaging, security patching, image maintenance and 24/7 expert support.