STACKIT Notebooks delivers ready-to-use JupyterHub/JupyterLab environments for data engineering, interactive analytics, and prototyping.
Service Overview
Section titled “Service Overview”- Zero Administrative Setup: Provision pre-configured Python environments in minutes.
- Isolated Pod Execution: Each session runs inside a secure, dedicated Kubernetes pod.
- Integrated Tooling: Pre-built support for Git integration, Spark jobs, and data science libraries.
Technical Details
Section titled “Technical Details”- Access Control: Role-based authentication integrated via OIDC.
- Persistence: Workspaces mount persistent storage volumes to preserve code and custom packages across sessions.
- Data Sovereignty: Operated inside certified German data centers in accordance with GDPR.
Identity Provider
Section titled “Identity Provider”The values below come from the STACKIT documentation and update themselves.
As for now, Notebooks depends on an external Identity Provider for authentication, authorization and single-sign-on. It uses the OpenID Connect protocol. The following IdPs are supported:
- Azure
- Okta
- AWS Cognito
- Keycloak
To integrate an IdP, you need to provide the Client ID, the Client secret, the Scope and the Discovery Endpoint. You need to get these values from the respective provider.
The values for Scope are in most cases openid email, for EntraID it is openid email User.Read.
The format for a Discovery Endpoint is https://\<provider-domain\>/.well-known/openid-configuration.
What is this?
This section is copied from the STACKIT docs automatically, several times a day. It cannot be changed here. Changes belong in the STACKIT docs.
Limitations & Constraints
Section titled “Limitations & Constraints”- Restart Required for Scaling: Changing instance sizes or attached GPUs requires stopping and restarting the notebook instance.
- Ephemeral Root Storage: Files saved outside the mounted persistent volume directory are erased upon pod restart.
- No Headless Background Execution: Sessions automatically shut down during inactivity, terminating long-running background training scripts.
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