An extensible MLOps framework that decouples machine learning code from infrastructure. It enables reproducible pipelines that transition seamlessly from local development to production cloud environments.
Tech Stack
PythonAI, ML & Data
Why zenml?
• Infrastructure-agnostic design
• Strong versioning for data and models
• Easy integration with existing tools
Limitations
• Learning curve for pipeline abstractions
• Requires setup of metadata stores
• Documentation can be dense
3/5/2026
Last Update
582
Forks
122
Issues
Apache-2.0
License
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