Features

This section provides an overview of Datalayer capabilities. The capabilities can be accessed from the SaaS, JupyterLab, VS Code and CLI interfaces. Refer to the interface documentation of your choice for more details on how to access the features.

📄️ Environments

In the context of Datalayer, an Environment refers to the collection of Python libraries, resources (CPU, GPU, Memory...) and storage requirements that your Jupyter Runtimes utilize to execute your code.

📄️ Runtimes

Datalayer introduces Browser and Remote Jupyter Runtimes aka Managed Kernels on top of the well-known Local Jupyter Kernels to seamlessly scale your Machine Learning and AI workflows.

📄️ Runtimes Snapshots

A Runtime Snapshot is a saved state of a Runtime. It can be used to save the current state of a Runtime, and to restore it later.

📄️ Credits

The usage of Runtimes is based on a credit consumption model. When you open an account, you begin with a set of free credits to get you started.

📄️ Secrets

Secrets are a way to store sensitive information such as passwords, API keys, and other credentials.

🗃️ Storage

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