KALE (Kubeflow Automated pipeLines Engine) is a project that aims at simplifying the Data Science experience of deploying Kubeflow Pipelines workflows. Kubeflow is a great platform for orchestrating complex workflows on top Kubernetes and Kubeflow Pipeline provides the mean to create reusable components that can be executed as part of workflows. The self-service nature of Kubeflow make it extremely appealing for Data Science use, at it provides an easy access to advanced distributed jobs orchestration, re-usability of components, Jupyter Notebooks, rich UIs and more. Still, developing and maintaining Kubeflow workflows can be hard for data scientists, who may not be experts in working orchestration platforms and related SDKs. Additionally, data science often involve processes of data exploration, iterative modelling and interactive environments (mostly Jupyter notebook).

Features

  • The JupyterLab Python package comes with its own yarn wrapper
  • Git Hooks
  • Documentation available
  • Examples available
  • Build images to be used as a NotebookServer in Kubeflow
  • Simplifies the Data Science experience of deploying Kubeflow Pipelines workflows

Project Samples

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License

Apache License V2.0

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Additional Project Details

Programming Language

Python

Related Categories

Python Data Visualization Software

Registered

2023-12-19