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Jupyter is a free, open-source, interactive web tool known as a computational notebook, which researchers can use to combine software code, computational output, explanatory text, and multimedia resources in a single document. For data scientists and machine learning engineers, Jupyter has emerged as a de facto standard. At the same time, there has been growing criticism that the way notebooks are being used leads to low resource utilization. GPU and other hardware resources will be bound to the specified notebooks even if the data scientists do not need them currently. This project proposes some Kubernetes CRDs to solve these problems.
Features
- Provide users the out-of-box Jupyter notebooks on Kubernetes
- Autoscale Jupyter kernels when the kernels are not used within the given time frame to increase the resource utilization
- Customize the kernel configuration in runtime without restarting the notebook
- Elastic Jupyter Notebooks on Kubernetes
- API Documentation
- Examples available
Project Samples
Categories
Operating System KernelsLicense
Apache License V2.0Follow elastic-jupyter-operator
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