This module deploys JupyterHub environment onto the Amazon EKS Cluster.
This is not a production ready
JupyterHubenvironment, as it currently runs on port 80.
You should be creating JupyterHub user credentials as a secret in AWS Secrets Manager with the below json representation:
{"username": "testadmin", "password": "testpassword"}eks-cluster-name: The EKS Cluster Name obtained from EKS Module metadataeks-cluster-admin-role-arn: The EKS Cluster's Master Role Arn from EKS Module metadataeks-oidc-arn: The EKS Cluster'd OIDC Arn for creating EKS Service Accounts obtained from EKS Module metadatasecrets-manager-name: Name of the JupyterHub secret created in SecretsManager
Then you can query the DNS Name of the JupyterHub ingress using the below command and log into the JupyterHub environment, where you would need to provide the username and password (values configured in the AWS Secrets Manager above):
echo $(kubectl get ing jupyterhub -n jupyter-hub -o jsonpath="{.status.loadBalancer.ingress[0].hostname}")/jupyter"k8s-jupyterh-jupyterh-XXXXXX.us-west-2.elb.amazonaws.com/jupyter"
- The private RestAPI endpoint URL can be obtained from the output of
WebVizCloudFormation stack metadata which will be in the following sample format:
Example: "https://XXXXXXXXX.execute-api.us-west-2.amazonaws.com/get-url?"
-
Then, you would need to have
scene_idandrecord_idhandy which can be obtained from thescene-metadatadynamodb table -
From the logged in environment of JH, open a terminal and run the below command:
wget -qO- "https://f1hdrfo4j2.execute-api.us-west-2.amazonaws.com/get-url?scene_id=<<SCENE_ID>>&record_id=<<RECORD_ID>>"Note:
SCENE_IDandRECORD_IDare the query string parameters which you would need to replace when you run the above command.