ClearML

An open-source MLOps platform providing experiment tracking, dataset versioning, pipeline orchestration, and model deployment in a single integrated system. ClearML's experiment tracking logs everything automatically: code snapshots, environment details, parameters, metrics, and artifacts for every training run without requiring explicit logging code in most frameworks. A Data Management module versions datasets and tracks data lineage, addressing reproducibility challenges that come from using unversioned data. ClearML Pipelines build multi-step ML workflows with dependency tracking and automated triggering. A built-in Hyperparameter Optimization module runs parallel experiments to find the best model configuration. ClearML can be self-hosted on-premises or used as a managed cloud service. Open source under Apache 2.0 on GitHub. Popular with teams that need MLflow-style experiment tracking combined with stronger data versioning and pipeline orchestration in a single tool.

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