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Notebook Overview

The Notebook Management module provides an environment for creating and running computational notebooks with custom CPU, GPU, and memory settings, ensuring data scientists or engineers have an environment for experimentation and analysis.

Key Features

  1. On-Demand Notebook Spawning

    • Launch notebook instances quickly, choosing the exact resources (CPU/GPU/memory) required.
    • Adapt to diverse project needs (data analysis, modeling, etc.) with minimal setup time.

  2. Resource Specification

    • Precisely allocate CPU, GPU, and memory for each notebook instance.
    • Optimize performance and prevent resource overuse or underutilization.

  3. Usage Monitoring

    • Track running notebooks and their resource consumption from the Notebooks UI, enabling quick identification of idle instances.

Best Practices

  • Right‑Size Resources – Allocate only the CPU, GPU, and memory necessary for the task to maximize cluster efficiency.
  • Shut Down When Idle – Stop notebooks after use to free resources for other users.
  • Version Control – Store notebooks in Git repositories for collaboration outside the live environment.

Next Steps

  • Notebooks UI – Learn how to create, start, and stop notebook instances.
  • Usage Monitoring – Observe resource consumption across notebooks and other workloads.
  • Resource Allocation – Configure CPU/GPU assignments for large or specialized tasks.