ClearML
Free tierThe AI Infrastructure Platform for maximizing AI performance and scalability at enterprise scale
Free tier available·Technical·API available·Open source
Key strengths
End-to-end AI infrastructure management from development to productionGPU cluster orchestration across on-premise, cloud, and hybrid environmentsBuilt-in experiment tracking, pipelines, and model repositorySecure multi-tenancy with role-based access control and granular billingOne-click GenAI deployment with LLM serving and access control
Free tier + paid plans
San Jose, USA
Founded 2019
Self-hostable
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Technical Documentation & Integration Guide
Installation
pip install clearml
clearml-init # Configure credentials against your ClearML server
Experiment Tracking (SDK)
from clearml import Task
task = Task.init(project_name="My Project", task_name="Training Run")
# ClearML auto-captures: hyperparameters, metrics, console output, Git diff, installed packages, and artifacts
Key Technical Components
- Infrastructure Control Plane: REST API-driven GPU orchestration supporting Kubernetes, bare-metal, and cloud VMs. Supports dynamic fractional GPU allocation, multi-tenant isolation (separate networks + storage per tenant), priority-based job queues, and chargeback billing by compute hours, storage, and API calls.
- AI Development Center: Provides a cloud-like self-serve workbench with integrated IDE access, data versioning, automated ML pipelines (DAG-based), model registry, hyperparameter optimization (HPO), and CI/CD integration hooks.
- GenAI App Engine: Deploys LLM inference endpoints onto GPU clusters with built-in auth, monitoring, vector DB tooling, and feedback collection APIs. Supports custom models and fine-tuning workflows.
- ClearML Agent: A daemon that pulls tasks from queues and executes them remotely, enabling fully reproducible remote training and experiment orchestration.
- Data Management:
clearml-dataCLI and SDK for versioned dataset management with built-in deduplication and remote storage support (S3, GCS, Azure Blob).
Self-Hosting
Deploy via Docker Compose or Helm chart on Kubernetes. Community and Enterprise server options available with varying SLA and support tiers.