Observability
Full Visibility, Zero Effort
Automatic logging and versioning for truly reproducible ML workflows
Comprehensive automatic logging
Achieve unparalleled observability across your ML pipeline with zero-effort tracking.
- Automate logging of code, data, metadata, and LLM prompts.
- Maintain consistent visibility across development and production environments.
- Streamline debugging and auditing with granular execution insights.
Seamless Version Control
Ensure reproducibility and traceability in your ML/GenAI pipelines.
- Native integration with Git repositories for code versioning.
- Automatic linking of model artifacts to specific code commits.
- Effortless recreation of experiments and model versions.
Automatic Containerization
Guarantee consistency from development to production with automated containerization.
- Auto-generate Docker containers for your ML environments.
- Eliminate "works on my machine" issues across your team.
- Enable anyone to run fully reproducible code without DevOps expertise.
ZenML's automatic logging and containerization have transformed our MLOps pipeline. We've drastically reduced environment inconsistencies and can now reproduce any experiment with just a few clicks. It's like having a DevOps engineer built into our ML framework.
Liza Bykhanova
Data Scientist at Competera
Unify Your ML and LLM Workflows
- Free, powerful MLOps open source foundation
- Works with any infrastructure
- Upgrade to managed Pro features
