Deploying ClearML as an AWS SageMaker Alternative on Ubuntu

ClearML is an open-source MLOps platform that pairs experiment tracking, pipelines, hyperparameter optimisation, and model serving, a self-hosted alternative to AWS SageMaker. This guide deploys the ClearML server with Docker Compose, fronts the web, API, and file servers with Traefik on three subdomains, registers an agent, runs a sample experiment, builds a pipeline, runs an HPO sweep, and deploys a serving stack. By the end, you'll have ClearML covering the full ML lifecycle securely at your domain.

Prerequisite: Ubuntu host with Docker + Compose installed, DNS A records for app.clearml.example.com, api.clearml.example.com, files.clearml.example.com. NVIDIA Container Toolkit on the host if you plan to run GPU workloads.

Prepare the Host

1. Bump Elasticsearch's virtual memory limit:

$ echo "vm.max_map_count=524288" | sudo tee /etc/sysctl.d/99-clearml.conf