How to Deploy ClearML as a Self-Hosted Alternative to Azure Machine Learning

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ClearML is an open-source MLOps platform that replicates Azure Machine Learning's core capabilities—including experiment tracking, pipelines, model serving, and hyperparameter optimization—without vendor lock-in or managed-compute costs. A detailed technical guide outlines how to deploy ClearML Server on any Linux machine using Docker Compose and the Traefik reverse proxy for SSL-terminated routing across three subdomains. The server stack consists of an API server, web UI, and file server backed by MongoDB, Elasticsearch, and Redis, while lightweight agent daemons handle remote task execution from any Python-capable machine. Traefik manages automatic TLS certificate provisioning via Let's Encrypt, replacing direct port exposure for the ClearML services. Optional GPU support is available through the NVIDIA Container Toolkit, and the setup can scale to include Triton-based model serving once the core stack is running.

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