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Creating a Project

Projects are created within an organization and provide compute resources for running Jupyter notebooks.

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Project Properties

When creating a project, you configure:
  • Name: Display name for the project
  • Slug: URL identifier (e.g., my-project)
  • Compute Type: CPU/GPU configuration
  • Docker Image: Python environment and pre-installed packages

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Compute Type Selection

Choose based on your workload: Micro
  • 0.5 CPU core, 1GB RAM
  • Low hourly rate
  • Good for testing and light analysis
Small
  • 2 CPU cores, 4GB RAM
  • Medium hourly rate
  • Suitable for data analysis and ML
GPU
  • 4 CPU cores, 16GB RAM, T4 GPU
  • Higher hourly rate
  • For deep learning and computer vision

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Project Status

Projects have the following states:
  • ready: Project created and available
  • active: Project running with compute resources
  • stopped: Project paused, no compute charges

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Accessing Your Project

Once created, your project is accessible at: 
https://runalph.ai/{org-slug}/{project-slug}
From here you can:
  • Open IDE for coding
  • Access terminals
  • Manage kernels
  • View hosted applications
  • Configure settings

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Project Settings

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General

  • Update name and slug
  • Change avatar
  • View creation date

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Environment Variables

  • Set API keys and secrets
  • Configure application settings

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Compute

  • View current compute type
  • Check hourly rate
  • Monitor usage

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Usage Tracking

All project compute time is tracked and billed hourly based on the compute type. View usage in your organization’s billing dashboard.

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Next Steps

Web Apps

Deploy applications in your project

Connect Notebooks

Link notebooks to your project

Usage & Billing

Monitor compute costs