An Educates based Datalab variant — How‑To Guide

This guide explains how to install the Datalab Crossplane package for the Educates runtime, provide cluster‑specific settings, and provision your first lab. The approach is platform‑engineering first: a single CRD abstracts identity, ingress, storage, and content bootstrapping while you choose the runtime stack.

1) Prerequisites

• Kubernetes cluster with kubectl access
• Crossplane v2.0.2 or newer, installed and healthy
• A GitOps mechanism (optional but recommended) to manage Providers/Functions
• DNS/TLS and an ingress controller in your cluster (any implementation)

2) Install the Datalab configuration package

Install the configuration package. Providers and functions are managed separately:

apiVersion: pkg.crossplane.io/v1
kind: Configuration
metadata:
  name: datalab
spec:
  package: ghcr.io/versioneer-tech/provider-datalab/educates:latest
  skipDependencyResolution: true

Apply:

kubectl apply -f configuration-install.yaml
kubectl get configurationrevisions.pkg.crossplane.io

3) Runtime dependencies

This Datalab targets the Educates runtime. See this README for instructions to install Educates and the Crossplane v2 dependencies.

4) Environment configuration

Provide cluster‑specific settings through an EnvironmentConfig. The composition consumes this to render ingress, identity, and storage correctly:

apiVersion: apiextensions.crossplane.io/v1beta1
kind: EnvironmentConfig
metadata:
  name: datalab
data:
  iam:
    realm: demo
  ingress:
    class: nginx
    domain: datalab.demo
    secret: wildcard-tls
  storage:
    endpoint: https://s3.demo
    provider: Other
    region: demo
    force_path_style: "true"
    secretNamespace: datalab
    type: s3

5) Storage credentials

The storage section in the EnvironmentConfig references a Kubernetes Secret — named identically to the Datalab — which must already exist in the cluster.
This Secret must reside in the namespace specified by storage.secretNamespace and include at least:

• AWS_ACCESS_KEY_ID
• AWS_SECRET_ACCESS_KEY

The credentials must provide access to the endpoint/region defined in the environment config. You can create the secret manually, for example:

kubectl -n datalab create secret generic demo   --from-literal=AWS_ACCESS_KEY_ID=<KEY_ID>   --from-literal=AWS_SECRET_ACCESS_KEY=<SECRET>

6) Create a Datalab

The minimal example creates a user‑scoped lab with one session. Sessions are required to start a runtime; if omitted, no runtime is started by default (you may patch sessions later). If spec.files is empty or omitted, no workshop tab is rendered in the Educates UI.

apiVersion: pkg.internal/v1beta1
kind: Datalab
metadata:
  name: demo
  namespace: datalab
spec:
  users:
  - alice
  sessions:
  - default
  vcluster: true
  files: []

For more scenarios, see theseexample manifests, which demonstrates: - labs with multiple users - enabling/disabling spec.vcluster - attaching workshop files from Git, OCI images, or HTTP sources

7) Validate installation

Check that packages, providers, CRDs, and your XRD are healthy:

```bash kubectl get providers.pkg.crossplane.io kubectl get providerrevisions.pkg.crossplane.io

kubectl api-resources --api-group=kubernetes.crossplane.io kubectl api-resources --api-group=helm.crossplane.io kubectl api-resources --api-group=keycloak.crossplane.io

kubectl get managedresourcedefinitions | grep -E 'helm|kubernetes|keycloak'

kubectl get xrd kubectl get datalabs.pkg.internal -A

Key:
- Sessions present → runtime is started; none → no runtime until patched
- Files present → workshop tab enabled; none → no workshop tab
- spec.vcluster: true → vcluster provisioned; false → namespace‑scoped runtime