Quickly spin up Jupyter notebooks in the cloud and scale them according to your needs

Deploy, manage, and scale the PyData stack using Jupyter Notebooks in the cloud

Simplified Setup

 Run your Jupyter Notebook on a VM inside AWS, Azure, or GCP without you having to know how to appropriately set up and use these services.

Custom Environment

 Specify a conda environment, requirements.txt, or docker image in order to standardize environments across all teammates

1-Click Notebook Sharing

Share your Juypter Notebooks with the public or teammates using links, eliminating the need to understand how to work with GitHub for basic data science projects.

Distributed Computing

 Deploy a Spark or Dask cluster with just one click, simplifying issues dealing with very expensive computations.

Automated Version Control

 Automated version control obviating potential issues arising from teammates not committing their newest versions.

Jupyter Instance With an Nvidia GPU

Just as you can spin up a Jupyter instance in Saturn, you can also spin up a GPU enabled instance as well.

When it comes to data science solutions, there’s always a need for fast prototyping. Enter Jupyter Notebooks and our best practices for using them.

Learn how to spin up a GPU enabled instance in Saturn Cloud

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