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Notebooks

Datalayer Notebooks let you run and share executable analysis workflows with a familiar Jupyter experience, while adding managed runtime operations and collaboration-friendly outputs.

What You Can Do​

  • Open and edit notebook files with code and markdown cells.
  • Execute cells on managed runtimes from your preferred interface.
  • Switch runtimes when you need more CPU/GPU resources.
  • Persist outputs and share reproducible analysis flows.
  • Combine notebooks with AI-assisted chat and tools for faster iteration.

Notebook Workflow in Datalayer​

  1. Create or open a notebook.
  2. Attach a runtime (local, browser, or remote managed runtime).
  3. Run cells interactively and inspect outputs.
  4. Use runtime operations (interrupt, restart, pause/resume, terminate) as needed.
  5. Save and share notebooks for repeatable execution.

Runtime Integration​

Notebooks are tightly integrated with runtime lifecycle features:

  • Resource-aware runtime selection.
  • State and execution controls for long sessions.
  • Credit-aware operations for cost visibility.
  • Snapshot support for pause/resume flows.

For runtime details, see Runtimes and Runtimes Snapshots.

Notebooks + AI​

Notebooks can be used alongside AI interactions for drafting code, refining analysis, and reviewing outputs. Use structured prompts and runtime status indicators to keep execution clear and auditable.

Best Practices​

  • Keep each notebook focused on one business workflow.
  • Use markdown cells to document assumptions and decisions.
  • Validate outputs with evaluation or regression checks for critical workflows.
  • Terminate idle runtimes to optimize credits.

Next Steps​