Notebooks

STACKIT Notebooks is a fully managed service based on JupyterHub that enables teams to develop, run, and share interactive notebooks in a secure and scalable environment. It provides production-ready Jupyter environments without the operational overhead of managing infrastructure. Notebook servers run in isolated Kubernetes pods and can be centrally governed and monitored.

Get Started

Übersicht

Basics

Understand the basic functionality of Notebooks, learn about key features and how to set up your first environment.

Getting started

Create your first Notebooks instance and write your first notebook.

How-tos

Get familiar with STACKIT Notebooks.

Tutorials

This tutorials section contains notebooks that provide step-by-step guidance on how to use various features and functionalities of our data and AI products. These tutorials are designed to help users understand and implement different techniques and workflows effectively.

Features

STACKIT Notebooks delivers enterprise-grade JupyterHub capabilities with fully managed infrastructure. The service eliminates the need to provision, operate, and scale notebook environments manually. User servers are launched on demand and run in isolated Kubernetes pods to ensure security and resource separation.

Key features include:

Fully managed JupyterHub and JupyterLab environments
Secure by design: Connect your Identity Provider (IdP) via OIDC with Role Based Access Control (RBAC). Templates available for Keycloak, Entra ID, Okta, Google and AWS Cognito.
On-demand notebook servers running in isolated Kubernetes pods
Integration with your own Git repositories for version-controlled development
Seamless STACKIT Observability integration with pre-defined Grafana dashboards

Use cases

Interactive data exploration

Explore, clean, and analyze data interactively using Python and common data science libraries. Combine code, documentation, and visualizations in a single collaborative environment.

Machine learning development

Develop, train, and evaluate machine learning models in isolated notebook environments. Integrate with scalable compute services for heavy workloads and move validated code into production pipelines.

Collaborative analytics

Enable teams to share notebooks, reproduce analyses, and review results in a governed environment with centralized authentication and access control.

Prototyping and experimentation

Quickly prototype ideas, test hypotheses, and iterate on models without infrastructure setup. Move successful experiments into structured repositories and production workflows.

Education and enablement

Provide secure, centrally managed notebook environments for training, workshops, and internal enablement programs with consistent configurations across all users.