Kaggle
The world's largest data science ecosystem for collaborative ML development, competitions, and datasets.
The multi-user hub for Jupyter Notebooks, providing a centralized data science platform for teams and classrooms.
JupyterHub is the industry-standard multi-user platform for project-based data science and interactive computing. In 2026, it remains the backbone of academic and enterprise research environments due to its modular architecture and massive scalability. It functions by managing individual user instances of Jupyter Notebooks, JupyterLab, or VS Code across local hardware, virtual private servers, or Kubernetes clusters. The architecture is composed of a Hub (a Python process), a Proxy (node-http-proxy), and Spawners (plug-ins to start user servers). This allows organizations to centralize compute resources while providing users with isolated, reproducible environments. With the rise of GPU-intensive AI workflows, JupyterHub’s ability to interface with Slurm, Docker, and Kubernetes (via KubeSpawner) makes it indispensable for managing shared expensive hardware. Its security model supports modern standards including OAuth2 and SAML, ensuring it fits into zero-trust enterprise architectures. While the core software is free, its 2026 market position is defined by its role as the substrate for managed services (like 2i2c or cloud-native notebook instances), offering a vendor-neutral alternative to proprietary IDE platforms.
Allows JupyterHub to spawn user servers as pods within a Kubernetes cluster, enabling dynamic scaling across thousands of users.
The world's largest data science ecosystem for collaborative ML development, competitions, and datasets.
Open-source data science meets generative AI for end-to-end workflow automation.
Open-source visual programming for interactive data science and machine learning visualization.
The notebook for reproducible research and collaborative data science.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Supports PAM, LDAP, OAuth2, SAML, and custom authentication scripts for identity management.
A fine-grained permission system that allows specific users to access the API, manage other users, or view shared servers.
Default interface support for JupyterLab, offering a full IDE experience in the browser including terminal access.
A background service that automatically shuts down inactive user notebooks to save compute costs.
Supports over 100 languages including Python, R, Julia, Scala, and C++ within the same hub.
Comprehensive API for programmatic user creation, server management, and resource monitoring.
Managing software installations on 500+ student laptops is impossible due to OS conflicts.
Registry Updated:2/7/2026
Data scientists need shared access to a limited pool of high-end NVIDIA GPUs.
Quickly spinning up environments for a 3-hour hackathon or tutorial.