de.NBI integration process #28
Unanswered
inesouledelhaj
asked this question in
Resource Provider
Replies: 0 comments
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Uh oh!
There was an error while loading. Please reload this page.
Uh oh!
There was an error while loading. Please reload this page.
🧩 de.NBI Cloud Integration Process
This discussion documents the integration of the de.NBI Cloud into the Jupyter4NFDI infrastructure.
1. Overview
Resource provider: de.NBI Cloud
Goal: Integrate de.NBI Cloud compute resources into the Jupyter4NFDI infrastructure.
Target users: Researchers within NFDI community.
Resource hosting sites: Bielefeld, Berlin, Freiburg, Gießen, Heidelberg, Tübingen.
Responsible admins / contacts: Tim Kreuzer and Ines Ouled Elhaj.
Status: ✅ Integration completed.
2. Integration Tasks & Progress
3. Task Details
Setup Infrastructure
Created network and security group then created the first main node of the RKE2 kubernetes cluster and initiated the cluster with the cloud init file. Added nodes using a script.
Install cluster requirements
Install fleet manually to automate software updates.
Created a dedicated branch containing all GitRepos for the required software components.
For each software package, ccreated a Fleet configuration branch containing the corresponding fleet.yaml file (ingress-nginx, cert-manager, database-operator, openstack-cinder-csi).
Manually created a Fleet GitRepo to automate the installation of all the required software GitRepos.
Install Outpost
Deploy and configure the JupyterHub Outpost component using Helm. Installation guidelines can be found in the documentation.
Configure Offered Options
Configured the system to offer multiple options: custom docker images, repo2docker and a minimal jupyterlab setup.
The system also offers multiple flavors:
Connect to Staging
To connect the Outpost to the Jupyter4NFDI staging instance, key information was exchanged between the outpost and the hub:
Connectivity to the staging JupyterHub instance was tested successfully.
User Storage Integration
Attached a persistent volume to one main node and set up an NFS server to provide shared user storage across all nodes.
Installed Storage Manager to manage user quotas via an XFS volume with xfs_quota, ensuring each user is limited to 30 GB of storage.
Move to Production
Replicated to production Jupyter4NFDI instance after testing the whole setup.
All reactions