ClearML combines experiment and data management, pipelines, scheduling, orchestration, and model serving for AI workloads.
Open source
24 alternativesClearML
ClearML manages AI experiments, data, pipelines, orchestration, scheduling, and model serving in one MLOps platform.
About ClearML
ClearML is an open-source suite for machine learning development and production. It includes modules for experiment management, orchestration and pipelines, data management and versioning, model serving, and reports.
Integration uses the clearml Python package with Task.init, which logs setup, source control info, environment packages, hyperparameters, outputs, and resource use. Data can use S3, GS, Azure, or NAS storage, and jobs can run on Kubernetes, cloud, or bare metal. Experiments sent to the demo server are public.
Key features
- Experiment tracking with two-line Task.init Python integration
- Automatic capture of hyperparameters, environment packages, and source control info
- Resource monitoring for CPU, GPU, temperature, IO, and network use
- Data versioning on S3, GS, Azure, and NAS storage
- Orchestration and pipelines for Kubernetes, cloud, and bare-metal jobs
- Model serving with Nvidia Triton GPU support and monitoring
Best for: Python-based machine learning teams that need to track experiments, version data, and manage orchestration and serving together.
Good for
- Open-source codebase
- Works with PyTorch, TensorFlow, Keras, XGBoost, scikit-learn and others
- Supports self-hosting or use with a hosted server
Watch out for
- Experiments sent to the demo server are public
ClearML at a glance
- Website
- github.com/clearml/clearml
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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ClearML FAQ
How do I start tracking an experiment?
Install with pip install clearml, run clearml-init to connect to a server, then add from clearml import Task and Task.init(project_name='examples', task_name='hello world') to your code.
Can I run ClearML on my own server?
Yes, you can set up your own server instead of using the hosted service.
Is the demo server private?
No, experiments launched to the demo server are public, so do not use it for sensitive experiments.
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