Sandboxes

Sandboxes provide on-demand, interactive compute environments for custom data exploration, scripting, and visualization. They allow you to work directly with your project's assets using familiar IDEs in a pre-configured cloud environment.

Launching a New Sandbox

To spin up an interactive environment, click the New sandbox button. The configuration process requires the following details:

Environment Configuration

• Name and Description: Provide a title and optional context for your sandbox session.
• Editor: Choose your preferred interactive development environment:
  • VS Code: A versatile editor for general-purpose scripting and development.
  • JupyterLab: Optimized for interactive data science and notebook-based workflows.
• Environment Profile: Select a pre-configured software stack:
  • Base: A minimal environment containing standard tools like git, curl, and wget.
  • Bioinformatician: Includes specialized tools such as samtools, bwa, R, and DESeq2.
  • Data Scientist: Pre-loaded with data analysis libraries like pandas, numpy, scikit-learn, and the tidyverse.

Data Attachment

You can attach project Datasets, Cohorts, or Workflow Outputs to your sandbox. When attached, these assets are mounted as local files, making them accessible for post-analysis.

Working with Attached Data

Once your sandbox is active, all attached datasets and cohorts are organized within a dedicated root directory:

• The /inputs Folder: Attached assets are mounted under the /inputs directory.
• Accessing Files: Within your chosen IDE (JupyterLab or VS Code), you can navigate this folder to read data directly into your scripts, notebooks, or terminal sessions.

Sandbox Lifecycle

After clicking Create sandbox, the platform begins allocating resources.

• Provisioning: You will see a "Please wait while we allocate your sandbox" screen while the cloud instance is prepared and the editor is initialized.
• Active Session: Once ready, click Open editor to launch the IDE in a new tab. The sandbox details view will display the environment type and exact expiry timestamp.
• Auto-Termination: To optimize resources, sandboxes are temporary and have a fixed lifespan (typically one hour). The remaining time is clearly displayed as the expiry date.

Management

From the Sandboxes list, you can track the status of all current and previous environments. Active sessions can be Edited to update their metadata or Deleted manually if you finish your work before the auto-expiry.

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Finished your documentation journey? Check the Reference section below for more tips!