Migrate 2i2c/temple to temple/prod (#7156)

* feat: enable temple prod

* feat: temporarily use next.temple

* feat: grow prod disk

* fix: add 2GB profile, add node selector

* feat: revert hostname

* fix: new CILogon clients

We don't need a new one for the advanced hub, but creating a new one
lets us ensure the name matches

* feat!: remove 2i2c/temple

* fix: remove profile selector from teaching hub

* docs: initial pass

* docs: fix formatting error

* docs: improve flow

* docs: fix missing reference target

* docs: add missing label

Author: agoose77

config/clusters/2i2c/cluster.yaml

@@ -34,14 +34,6 @@ hubs:
   - daskhub-common.values.yaml
   - dask-staging.values.yaml
   - enc-dask-staging.secret.values.yaml
-- name: temple
-  display_name: Temple University
-  domain: temple.2i2c.cloud
-  helm_chart: basehub
-  helm_chart_values_files:
-  - basehub-common.values.yaml
-  - temple.values.yaml
-  - enc-temple.secret.values.yaml
   # Temporary deploy a staging hub for UCMerced
   # to help them transition to new user images
   # ref: https://github.com/2i2c-org/infrastructure/issues/3188

config/clusters/2i2c/enc-temple.secret.values.yaml

@@ -20,16 +20,26 @@ hubs:
   helm_chart: basehub
   helm_chart_values_files:
   - common.values.yaml
-  - enc-common.secret.values.yaml
+  - common-teaching.values.yaml
   - staging.values.yaml
   - enc-staging.secret.values.yaml
+- name: prod
+  display_name: Temple University
+  domain: temple.2i2c.cloud
+  helm_chart: basehub
+  helm_chart_values_files:
+  - common.values.yaml
+  - common-teaching.values.yaml
+  - prod.values.yaml
+  - enc-prod.secret.values.yaml
 - name: advanced
   display_name: Temple University (Advanced)
   domain: advanced.temple.2i2c.cloud
   helm_chart: basehub
   helm_chart_values_files:
   - common.values.yaml
-  - enc-common.secret.values.yaml
+  - common-non-teaching.values.yaml
+  - enc-common-non-teaching.secret.values.yaml
   - advanced.values.yaml
   - enc-advanced.secret.values.yaml
 - name: research
@@ -38,6 +48,7 @@ hubs:
   helm_chart: basehub
   helm_chart_values_files:
   - common.values.yaml
-  - enc-common.secret.values.yaml
+  - common-non-teaching.values.yaml
+  - enc-common-non-teaching.secret.values.yaml
   - research.values.yaml
   - enc-research.secret.values.yaml

config/clusters/2i2c/temple.values.yaml

@@ -0,0 +1,85 @@
+jupyterhub:
+  singleuser:
+    profileList:
+    - display_name: Default
+      description: Choose image and resource allocation
+      default: true
+      profile_options:
+        image:
+          display_name: Image
+          dynamic_image_building:
+            enabled: true
+          unlisted_choice:
+            enabled: true
+            display_name: Custom image
+            validation_regex: ^.+:.+$
+            validation_message: Must be a publicly available docker image, of form <image-name>:<tag>
+            kubespawner_override:
+              image: '{value}'
+          choices:
+            datascience:
+              display_name: Data Science
+              slug: regular-profile
+              kubespawner_override:
+                image: docker.io/laserchemist/datascience:v13
+        requests:
+          display_name: Resource Allocation
+          choices:
+            mem_4_gb:
+              default: true
+              display_name: ~4 GB RAM, ~0.5 CPUs
+              description: Up to ~4 CPUs when available
+              kubespawner_override:
+                mem_guarantee: 3902839759
+                mem_limit: 3902839759
+                cpu_guarantee: 0.4563125
+                cpu_limit: 3.6505
+                node_selector:
+                  node.kubernetes.io/instance-type: r5.xlarge
+            mem_7_gb:
+              display_name: ~7 GB RAM, ~0.9 CPUs
+              description: Up to ~4 CPUs when available
+              kubespawner_override:
+                mem_guarantee: 7805679519
+                mem_limit: 7805679519
+                cpu_guarantee: 0.912625
+                cpu_limit: 3.6505
+                node_selector:
+                  node.kubernetes.io/instance-type: r5.xlarge
+            mem_15_gb:
+              display_name: ~15 GB RAM, ~1.8 CPUs
+              description: Up to ~4 CPUs when available
+              kubespawner_override:
+                mem_guarantee: 15611359038
+                mem_limit: 15611359038
+                cpu_guarantee: 1.82525
+                cpu_limit: 3.6505
+                node_selector:
+                  node.kubernetes.io/instance-type: r5.xlarge
+            mem_29_gb:
+              display_name: ~29 GB RAM, ~4 CPUs
+              description: ~4 CPUs always available
+              kubespawner_override:
+                mem_guarantee: 31222718077
+                mem_limit: 31222718077
+                cpu_guarantee: 3.6505
+                cpu_limit: 3.6505
+binderhub-service:
+  enabled: true
+    # Explicitly specify what nodes we want for our builds
+    # Otherwise we may scale up a larger node than needed
+  networkPolicy:
+    enabled: true
+  dockerApi:
+    nodeSelector:
+      node.kubernetes.io/instance-type: r5.xlarge
+  config:
+    KubernetesBuildExecutor:
+      node_selector:
+        node.kubernetes.io/instance-type: r5.xlarge
+    DockerRegistry:
+      url: &url https://quay.io
+      username: &username imagebuilding-non-gcp-hubs+image_builder
+  buildPodsRegistryCredentials:
+    server: *url
+    username: *username

config/clusters/temple/cluster.yaml

@@ -0,0 +1,14 @@
+jupyterhub:
+  singleuser:
+    image:
+      name: laserchemist/datascience
+      tag: v13
+    # Taken from `deployer generate resource-allocation choices r5.xlarge:5`
+    memory:
+      guarantee: 1951419879
+      limit: 1951419879
+    cpu:
+      guarantee: 0.22815625
+      limit: 3.6505
+    nodeSelector:
+      node.kubernetes.io/instance-type: r5.xlarge

config/clusters/temple/common-non-teaching.values.yaml

@@ -58,90 +58,6 @@ jupyterhub:
         allow_existing_users: true
   singleuser:
     defaultUrl: /lab
-    profileList:
-    - display_name: Default
-      description: Choose image and resource allocation
-      default: true
-      profile_options:
-        image:
-          display_name: Image
-          dynamic_image_building:
-            enabled: true
-          unlisted_choice:
-            enabled: true
-            display_name: Custom image
-            validation_regex: ^.+:.+$
-            validation_message: Must be a publicly available docker image, of form <image-name>:<tag>
-            kubespawner_override:
-              image: '{value}'
-          choices:
-            datascience:
-              display_name: Data Science
-              slug: regular-profile
-              kubespawner_override:
-                image: docker.io/laserchemist/datascience:v13
-        requests:
-          display_name: Resource Allocation
-          choices:
-            mem_4_gb:
-              display_name: ~4 GB RAM, ~0.5 CPUs
-              description: Up to ~4 CPUs when available
-              default: true
-              kubespawner_override:
-                mem_guarantee: 3902839759
-                mem_limit: 3902839759
-                cpu_guarantee: 0.4563125
-                cpu_limit: 3.6505
-                node_selector:
-                  node.kubernetes.io/instance-type: r5.xlarge
-            mem_7_gb:
-              display_name: ~7 GB RAM, ~0.9 CPUs
-              description: Up to ~4 CPUs when available
-              kubespawner_override:
-                mem_guarantee: 7805679519
-                mem_limit: 7805679519
-                cpu_guarantee: 0.912625
-                cpu_limit: 3.6505
-                node_selector:
-                  node.kubernetes.io/instance-type: r5.xlarge
-            mem_15_gb:
-              display_name: ~15 GB RAM, ~1.8 CPUs
-              description: Up to ~4 CPUs when available
-              kubespawner_override:
-                mem_guarantee: 15611359038
-                mem_limit: 15611359038
-                cpu_guarantee: 1.82525
-                cpu_limit: 3.6505
-                node_selector:
-                  node.kubernetes.io/instance-type: r5.xlarge
-            mem_29_gb:
-              display_name: ~29 GB RAM, ~4 CPUs
-              description: ~4 CPUs always available
-              kubespawner_override:
-                mem_guarantee: 31222718077
-                mem_limit: 31222718077
-                cpu_guarantee: 3.6505
-                cpu_limit: 3.6505
   scheduling:
     userScheduler:
       enabled: true
-
-binderhub-service:
-  enabled: true
-    # Explicitly specify what nodes we want for our builds
-    # Otherwise we may scale up a larger node than needed
-  networkPolicy:
-    enabled: true
-  dockerApi:
-    nodeSelector:
-      node.kubernetes.io/instance-type: r5.xlarge
-  config:
-    KubernetesBuildExecutor:
-      node_selector:
-        node.kubernetes.io/instance-type: r5.xlarge
-    DockerRegistry:
-      url: &url https://quay.io
-      username: &username imagebuilding-non-gcp-hubs+image_builder
-  buildPodsRegistryCredentials:
-    server: *url
-    username: *username

config/clusters/temple/common-teaching.values.yaml

@@ -1,19 +1,19 @@
-jupyterhub-home-nfs:
-  quotaEnforcer:
-    extraConfig:
-      secret-quota-overrides: ENC[AES256_GCM,data:QjlnlksOhgEfYQDZDvfJyJki6XhvIMIJ/0izVvuKFJft1IXhC+NtRbheBn2X9MF1YtZ+fMKKoQ==,iv:2Q/mNdrVI/cU4f5aoIU/T0hbjWrOCUYNnGp9Dz5NxTc=,tag:vmVVwcMP+hY3XMFZXaRPRw==,type:str]
 jupyterhub:
   hub:
     config:
       CILogonOAuthenticator:
-        client_id: ENC[AES256_GCM,data:krzjCyDwZojV6A0jJtO9XnvjlytIkG0L60nRecSvlzTPnsFpuVvKhgdCGiSCaurjxb6u,iv:AlWllQU1vWjoZnBlfqrHXu9iVdLQok0Y2we+gUf7L4I=,tag:vhHvv9WLz9MJlzWylF4qxA==,type:str]
-        client_secret: ENC[AES256_GCM,data:Tf7dJ5fhiB8H+wPbtYmJjQxRhtBUjo0TXlPRUTxuu4okKNWJuMH1Z33YOs6M28duN/kRwJ5g1unZKzRaADwrvjl7AhxXY82dPJjD6mfNIAyLtqo4S9w=,iv:28uevnHKfq8eqBMG8oM18yyawS+45YnVoSeJY5jTdAs=,tag:XiEZcENmvPXGiOoqW/Or0A==,type:str]
+        client_id: ENC[AES256_GCM,data:QLHfGqsfiYXNYE1kN+M6BHWA56MtoYjfRFzSrCFCmnCXsEY5oylqGquBPwj1nEvgipC/,iv:eIcJkNjzUJhT84qYcO7u+/urhzcvIA7vzd1uBVVVsyA=,tag:vwvLNRzW3gEYo117AV7WiA==,type:str]
+        client_secret: ENC[AES256_GCM,data:b0q+TIghWKDSVrctFpQuhRzPZfawfI/Q9KEeio4x6OqFH/iWvB9tmnaQc9aBFVovAJEuTNpji+1uoRFBwxLN0s/aKNEA6win/9M/FKUSDKFvfjZjbeY=,iv:6bGBvpQ/cffZSSP8Ay2ltmyG5tB6yI8Co3h4r7zo67I=,tag:J1kAMV4gu5TSowpZBYh5bA==,type:str]
+jupyterhub-home-nfs:
+  quotaEnforcer:
+    extraConfig:
+      secret-quota-overrides: ENC[AES256_GCM,data:4oYpjDEFZ+XchWcwGMJNCHomSKIciTDlUCS7uoLPGTq2ZXmrSc0d75JIcLYkoJQldlTNK8Il+w==,iv:m/q8Vcotz7ik6oFkSkhoxkv6s0ca+dJAbLuXfiZ4V5M=,tag:grUz0GtzbTVDU+4o6rl50w==,type:str]
 sops:
   gcp_kms:
   - resource_id: projects/two-eye-two-see/locations/global/keyRings/sops-keys/cryptoKeys/similar-hubs
-    created_at: '2025-08-21T12:41:58Z'
-    enc: CiUA4OM7eLQmbuwHl3C1D1pnJNKW5QG0tlnQ4OXd/0zv9mJOsRqSEkkAXpa10JXyOgSU/pVlI7HwffT7L2cpHk35xZManciCWjkuK4YvIelcq2Um8FJcFMmDJ2zX1xJbvP0Zak4yaf1jrImv2oaQH5nH
-  lastmodified: '2025-10-20T12:08:26Z'
-  mac: ENC[AES256_GCM,data:GCSObYQavtgLPAn4p2NA71gdc/6pdMydJdkDxsRNzLTCdedlDL+C4+/HecCaW3BMiyoMCB7lAf+rzhrmb8YtrNKJdULDovdTLw1H94II/HPWAQshyys09OBzYxj67ejRq8kBVUckFwi8botx+sNBkQVt2cmgz6qD+Oyz7dKCoPE=,iv:cM+4g1Z+W+xWYIt/9s2Yn1pkaVSva6BAvR97Gi5k5hI=,tag:5fDlNjlix2f4j4dXFMBNsw==,type:str]
+    created_at: '2025-11-24T12:58:01Z'
+    enc: CiUA4OM7eBxqftkBWE/moPT8gQxgQLALCGKI2BHGvbtpp6kLIh7NEkkAZoeZpmSfVbNyrl/oRjb8DvhttZKZKltIixCIq+0q+4qZ/bkMJHOd1y3Ndmn4DQ7f4jlWtD9GnH8DhCI1K59NqUkZZ45MlEyT
+  lastmodified: '2025-11-24T12:58:01Z'
+  mac: ENC[AES256_GCM,data:KE+LURCZ7hfTGpZRpRYaqAB3JXcYwE6B24NTnDwiwAQGmJ5bgZAKAa6LoxYtMwjUEUYXQfdhaEajieLx4y2fFw+5g7ODJPMO+T25oZRfeb+0G02mGoO6fugoSzxdAG78WnPKJh1xtSlUpU3n5G5ReS8hviKS6xM3o+6naPZMd1E=,iv:iA5RPUA5asicNHoI/RsHZDFMEm5NIDgY8/l7b05Y0B4=,tag:hSsgulVV1K4hUnrVskq86g==,type:str]
   unencrypted_suffix: _unencrypted
   version: 3.10.2

config/clusters/temple/common.values.yaml

@@ -0,0 +1,19 @@
+jupyterhub:
+  hub:
+    config:
+      CILogonOAuthenticator:
+        client_id: ENC[AES256_GCM,data:YG8dMcdhs0xGVpKQrOLGH+MYx4hpnoPT2to/U6kjuEEZI/MnPD+ewOlGQd3EOSU2J8gv,iv:AWi+oImq/dAKa0BAAXctuII2DZlluM437OCoGAdPZP8=,tag:j+v9sfc+jEosXCc1eMAMpw==,type:str]
+        client_secret: ENC[AES256_GCM,data:wbotT8c7pyfc345s85idVGoupPiTECwT4lLf8IA40/KummzpIcawR82ZZuZmeCOsaYQ4InX95wi4WV11/VxHodWJqXrRO6gb29zazERP1J6dHr5SnG4=,iv:Y492YqhIihZF9Px0EZGfKm4uRcXOcL3PVzipJZ34yZI=,tag:eBev95btt2VLHC6j000RKg==,type:str]
+jupyterhub-home-nfs:
+  quotaEnforcer:
+    extraConfig:
+      secret-quota-overrides: ENC[AES256_GCM,data:O6qT1VOCqWL/kJN6GWGzP1MADxN6jOTR7gA5WFg81KpTSGBAsgfGk5JpRVNz1I0yXftAhAAy,iv:IsNz7wXZq5UoJMnDlFDNyCNpU1wWJIQEvwXgI3eBgjY=,tag:Bhtq1toYAUY/Ej2lJuhOQg==,type:str]
+sops:
+  gcp_kms:
+  - resource_id: projects/two-eye-two-see/locations/global/keyRings/sops-keys/cryptoKeys/similar-hubs
+    created_at: '2025-11-24T12:57:13Z'
+    enc: CiUA4OM7eFwBAnVGsAP7LHN57SxQGCwug6LPuZwe0y2y78049NcLEkkAZoeZpmSEkuTMPiJ5TTVTZCdQdWcPB6hS5wxAmGuBWT0ZTmGqRnXXSQe2jdjv8gv3WdTGn1l1TFVDxrsyppZweWPjLTHzPVVH
+  lastmodified: '2025-11-24T12:57:13Z'
+  mac: ENC[AES256_GCM,data:gKPGJsu+OZndNwqjwa1YvcLtOiYY0IXD9VvFo9W8D61+bX5CweNQs01fbu3Yl7ITy+rSj/LKHE6mKBZ1Pm5JqCqrnjPOthWAMWG0+HgUC1NmaMWjKkL9w9S1ZsoJsUaDmVNmuIwEsgy5ZCThtcKsFy8A70eIf6+B/HiBucvKMSM=,iv:GSuCTYOYrDmnYN5UW+AvZyoCtgONZUiwZrY2EpGM/Ys=,tag:QRqEC//kdC47Gpw/u8CLGA==,type:str]
+  unencrypted_suffix: _unencrypted
+  version: 3.10.2