An example Jupyterhub deployment on EKS.
For full details on configuration options and security best practices, please refer to the Jupyterhub on Kubernetes documentation.
cdk.py includes a Cloud Development Kit (CDK) app that will
create the following resources in your AWS account:
- A VPC
- A Docker image in ECR
- An EFS file system
- An IAM role
- An autoscaling EKS cluster running Jupyterhub on 1-10 nodes
config.yaml contains Jupyterhub helm chart configurations.
In addition to setting up the EFS storage integration, it defines two profiles with different cpu and memory settings
and creates a "shared" directory which all users can access.
Dockerfile defines the custom jupyterlab image used in the deployment. Extending Jupyter's
datascience base image, it installs four common extensions:
jupyterlab-git, ipython-sql,
voila, jupyter-scheduler.
pdm sync -G dev
To deploy the stack to the account your currently authenticated against, run:
cdk deploy -O output.json
View output.json to find the command to add the deployed cluster to your kubeconfig. You're looking for the
output named something like K8sClusterConfigCommand7A4D6E5F. Its value is the command you need to run, something like:
aws eks update-kubeconfig --name K8sClusterA30C4AE4-abcefabcdef1234567812345678 --region us-east-1 --role-arn arn:aws:iam::XXXXXXXXX:role/EksJupyterhub-MastersRole0257C11B-8P2R1A12Q234Q1
Once you've added the cluster to your kubeconfig, you can view your pods.
$ kubectl -n jupyterhub get pods
NAME READY STATUS RESTARTS AGE
continuous-image-puller-xjgw7 1/1 Running 0 8s
hub-7c4ddbf7b4-dwvwf 0/1 ContainerCreating 0 8s
proxy-77dfcb58df-qcst2 1/1 Running 0 8s
user-scheduler-7574d67cdb-f89m2 1/1 Running 0 8s
user-scheduler-7574d67cdb-fgv9n 1/1 Running 0 8s
Once all pods are running, you can view your jupyterhub deployment by going to the address found in your output.json.
Specifically you're looking for the output named JupyterhubEndpoint, it will look something like
abcd12345678fedcba87654321-1044896179.us-east-1.elb.amazonaws.com.
Go to that address in your web browser. E.g. http://abcd12345678fedcba87654321-1044896179.us-east-1.elb.amazonaws.com.
Once there, type in any username and password and you can lauch a user server and start creating notebooks.