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Merge branch 'develop' into update-production
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2025-HPCIC/infrastructure/dry-run/README.md

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# Deploy hpcic-2025-tutorial to AWS Elastic Kubernetes Service (EKS)
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# Deploy perftools-hpcic-2025-dry-run to AWS Elastic Kubernetes Service (EKS)
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These config files and scripts can be used to deploy the hpcic-2025-tutorial tutorial to EKS.
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These config files and scripts can be used to deploy the perftools-hpcic-2025-dry-run tutorial to EKS.
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The sections below walk you through the steps to deploying your cluster. All commands in these
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sections should be run from the same directory as this README.
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```
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After cleaning everything up, you can verify that everything has been cleaned up by going to the AWS web consle
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and ensuring nothing from your tutorial still exists in CloudFormation and EKS.
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and ensuring nothing from your tutorial still exists in CloudFormation and EKS.

2025-HPCIC/infrastructure/dry-run/cleanup.sh

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# if the JupyterHub deployment failed or was previously torn down
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set +e
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echo "Tearing down JupyterHub and uninstalling everything related to Helm:"
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helm uninstall hpcic-2025-tutorial-jupyter
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helm uninstall perftools-hpcic-2025-dry-run-jupyter
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set -e
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echo ""
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eksctl delete cluster --config-file ./eksctl-config.yaml --wait
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echo ""
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echo "Everything is now cleaned up!"
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echo "Everything is now cleaned up!"

2025-HPCIC/infrastructure/dry-run/cluster-autoscaler.yaml

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- --cloud-provider=aws
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- --skip-nodes-with-local-storage=false
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- --expander=least-waste
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- --node-group-auto-discovery=asg:tag=k8s.io/cluster-autoscaler/enabled,k8s.io/cluster-autoscaler/hpcic-2025-tutorial
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- --node-group-auto-discovery=asg:tag=k8s.io/cluster-autoscaler/enabled,k8s.io/cluster-autoscaler/perftools-hpcic-2025-dry-run
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volumeMounts:
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# Mount the CA SSL/TLS certificates into the container
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- name: ssl-certs
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volumes:
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- name: ssl-certs
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hostPath:
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path: "/etc/ssl/certs/ca-bundle.crt"
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path: "/etc/ssl/certs/ca-bundle.crt"

2025-HPCIC/infrastructure/dry-run/config.toml

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tutorial_name = "hpcic-2025-dry-run"
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tutorial_name = "perftools-hpcic-2025-dry-run"
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[aws.eksctl]
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cluster_name = "hpcic-2025-dry-run"
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cluster_name = "perftools-hpcic-2025-dry-run"
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cluster_deployment_region = "us-west-1"
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cluster_availability_zones = [
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"us-west-1a",

2025-HPCIC/infrastructure/dry-run/deploy_jupyterhub.sh

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@@ -14,7 +14,7 @@ helm repo add jupyterhub https://hub.jupyter.org/helm-chart/
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helm repo update
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echo ""
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echo "Installing the Helm chart and deploying JupyterHub to EKS:"
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helm install hpcic-2025-tutorial-jupyter jupyterhub/jupyterhub --version 4.2.0 --values ./helm-config.yaml
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helm install perftools-hpcic-2025-dry-run-jupyter jupyterhub/jupyterhub --version 4.2.0 --values ./helm-config.yaml
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echo ""
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echo "Done deploying JupyterHub!"
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echo " share the same pod."
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echo ""
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echo "After you are done with your tutorial, you should finally run cleanup.sh to bring down"
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echo "the EKS cluster and all associated resources."
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echo "the EKS cluster and all associated resources."

2025-HPCIC/infrastructure/dry-run/eksctl-config.yaml

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kind: ClusterConfig
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# Define the name of the cluster and the deployment region
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metadata:
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name: hpcic-2025-tutorial
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region: us-east-1
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name: perftools-hpcic-2025-dry-run
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region: us-west-1
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# Create the IAM policies needed to enable the autoscaler and storage
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iam:
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# Specify the availability zone from which nodes will be obtained
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availabilityZones:
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- "us-east-1a"
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- "us-east-1b"
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- "us-west-1a"
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- "us-west-1c"
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# Define rules for nodegroups for each availability zone
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managedNodeGroups:
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- name: node-group-us-east-1a
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- name: node-group-us-west-1a
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# Set policies/permissions to autoscale
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iam:
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withAddonPolicies:
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# Size of storage volume for the availability zone, in gigabytes
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volumeSize: 30
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# Number of nodes to start with in this availability zone
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desiredCapacity: 15
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desiredCapacity: 2
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# Minimum number of nodes that will always be allocated in this availability zone
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minSize: 15
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minSize: 2
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# Maximum number of nodes that will every be allocated in this availability zone
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maxSize: 100
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maxSize: 8
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privateNetworking: true
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availabilityZones:
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- us-east-1a
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- us-west-1a
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tags:
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k8s.io/cluster-autoscaler/enabled: "true"
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k8s.io/cluster-autoscaler/jupyterhub: "owned"
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- name: node-group-us-east-1b
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- name: node-group-us-west-1c
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# Set policies/permissions to autoscale
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iam:
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withAddonPolicies:
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# Size of storage volume for the availability zone, in gigabytes
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volumeSize: 30
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# Number of nodes to start with in this availability zone
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desiredCapacity: 15
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desiredCapacity: 2
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# Minimum number of nodes that will always be allocated in this availability zone
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minSize: 15
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minSize: 2
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# Maximum number of nodes that will every be allocated in this availability zone
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maxSize: 100
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maxSize: 8
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privateNetworking: true
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availabilityZones:
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- us-east-1b
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- us-west-1c
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tags:
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k8s.io/cluster-autoscaler/enabled: "true"
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k8s.io/cluster-autoscaler/jupyterhub: "owned"

2025-HPCIC/infrastructure/dry-run/helm-config.yaml

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hub:
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# Maximum number of users with spawned JupyterLab environments (i.e., pods) at a time
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concurrentSpawnLimit: 30
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concurrentSpawnLimit: 14
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config:
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# Define a password for login
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DummyAuthenticator:
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extraVolumeMounts:
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- name: shm-volume
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mountPath: /dev/shm
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2025-HPCIC/infrastructure/dry-run/tear_down_jupyterhub.sh

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exit 1
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fi
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helm uninstall hpcic-2025-tutorial-jupyter
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helm uninstall perftools-hpcic-2025-dry-run-jupyter
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echo "Helm's JupyterHub deployment is torn down."
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echo "If any attendee pods are remaining, you can delete them with 'kubectl delete pod <pod_name>'"
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echo ""
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echo "To recreate the JupyterHub deployment, just run deploy_jupyterhub.sh again."
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echo "To recreate the JupyterHub deployment, just run deploy_jupyterhub.sh again."

2025-HPCIC/infrastructure/dry-run/update_jupyterhub_deployment.sh

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fi
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helm upgrade hpcic-2025-tutorial-jupyter jupyterhub/jupyterhub --values ./helm-config.yaml
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helm upgrade perftools-hpcic-2025-dry-run-jupyter jupyterhub/jupyterhub --values ./helm-config.yaml
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echo "The JupyterHub deployment is updated!"
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echo "The JupyterHub deployment is updated!"

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