An open-source command line interface (CLI) to deploy interactive applications to the Cloud.
- Cloud Deployments Made Simple — Get started with three simple commands:
jd init,jd config,jd up. No Cloud knowledge required. - Unlock The Power of the Cloud — Access GPUs, scale compute, and expand storage on demand with simple commands.
- Extensible Template-Based Architecture — Pick a deployment template that fits your use case. Can't find what you need? Adding a template is simple!
- Multi-Application Support — Deploy JupyterLab, Jupyter notebooks, or other interactive apps such as CodeEditor or StreamLit.
- Multi-User Support — Grant users and teams access to your apps securely via their OIDC identity, then collaborate in real-time.
- Vendor Neutral — Compatible with any cloud provider and any infrastructure-as-code engine.
https://jupyter-deploy.readthedocs.io
We recommend using uv for dependency management.
# create a uv project with a virtual environment
uv init . --bare
uv venv
source .venv/bin/activate
# install the CLI and the AWS Base Template
uv add jupyter-deploy[aws]
uv add jupyter-deploy-tf-aws-ec2-baseTo get started, run from your virtual environment:
jd --help- jupyter-deploy: Core package providing the command line interface tool (CLI).
- jupyter-deploy-tf-aws-ec2-base: The AWS Base Template to deploy a JupyterLab to an EC2 instance, serve it on your own domain and control access with GitHub OIDC.
- jupyter-infra-tf-aws-iam-ci: The template to configure the AWS resources for the CI.
- pytest-jupyter-deploy: The pytest plugin for E2E tests that integrates with Playwright.
Refer to the Contributing guide.
This project is licensed under the MIT License.