ConfigsApr 1, 2026·1 min read

ClearML — End-to-End MLOps Platform

ClearML provides experiment tracking, pipeline orchestration, data management, and model serving in one platform. 6.6K+ stars. 2-line integration. Apache 2.0.

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Quick Use

Use it first, then decide how deep to go

This block should tell both the user and the agent what to copy, install, and apply first.

pip install clearml
clearml-init  # Configure credentials

# Add 2 lines to any script
python -c "
from clearml import Task
task = Task.init(project_name=\"my-project\", task_name=\"experiment-1\")
# Everything is now tracked automatically
print(\"ClearML tracking active!\")
"
Intro

ClearML is an MLOps/LLMOps platform providing experiment management, data handling, pipeline orchestration, and model serving in one integrated solution. With 6,600+ GitHub stars and Apache 2.0 license, it requires just 2 lines of code to start tracking experiments. Automatic capture of code, environments, hyperparameters, results, CPU/GPU metrics, artifacts, and TensorBoard logs. Supports PyTorch, TensorFlow, Keras, XGBoost, and more. Deploy on Kubernetes, cloud, or on-premises.

Best for: ML teams wanting zero-friction experiment tracking with full MLOps capabilities Works with: Claude Code, OpenAI Codex, Cursor, Gemini CLI, Windsurf

Key Features

  • 2-line integration for any ML script
  • Auto-tracking of code, params, metrics, artifacts
  • Pipeline orchestration and scheduling
  • Dataset versioning (S3, GCS, Azure, NAS)
  • Model serving with GPU optimization
  • Kubernetes and cloud deployment

FAQ

Q: What is ClearML? A: End-to-end MLOps platform with 6.6K+ stars. 2-line experiment tracking, pipelines, data management, model serving. Apache 2.0.

Q: How do I install ClearML? A: pip install clearml. clearml-init to configure. Task.init() in your script.

🙏

Source & Thanks

clearml/clearml — 6,600+ GitHub stars

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