diff --git a/cgpu101/config.yaml b/cgpu101/config.yaml
index 5c675dd..6a921ee 100644
--- a/cgpu101/config.yaml
+++ b/cgpu101/config.yaml
@@ -7,9 +7,8 @@ jupyterhub::jupyterhub_config_hash:
       max: 55000
       def: 55000
     gpus:
-      def: gpu:1
-      choices:
-        - gpu:1
+      def: 'gpu:1'
+      choices: ['gpu:1']
 
 jupyterhub::kernel::venv::packages:
   - cupy==12.2.0
diff --git a/cgpu101/main.tf b/cgpu101/main.tf
index a63ac2b..f091b48 100644
--- a/cgpu101/main.tf
+++ b/cgpu101/main.tf
@@ -11,9 +11,5 @@ locals {
     mig = {
       gpupool = { "3g.20gb" = 2 }
     }
-    config_git_url = "https://github.com/computecanada/puppet-magic_castle.git"
-    config_version = "a3c80de"
-    image_cpu = "snapshot-cpunode-2026-A9.7-2"
-    image_gpu = "snapshot-cpunode-2026-A9.7-2"
   }
 }
diff --git a/cip101/config.yaml b/cip101/config.yaml
index 34ad16a..b22022a 100644
--- a/cip101/config.yaml
+++ b/cip101/config.yaml
@@ -4,7 +4,7 @@ jupyterhub::jupyterhub_config_hash:
             max: 1024
             def: 1024
         partition:
-            def: 'nodecpupool'
+            def: 'cpupool'
         ui:
             def: 'terminal'
 
diff --git a/cip201/config.yaml b/cip201/config.yaml
index fcc770c..44287b6 100644
--- a/cip201/config.yaml
+++ b/cip201/config.yaml
@@ -4,7 +4,7 @@ jupyterhub::jupyterhub_config_hash:
             max: 1024
             def: 1024
         partition:
-            def: 'nodecpupool'
+            def: 'cpu'
         ui:
             def: 'terminal'
 
diff --git a/cip202/config.yaml b/cip202/config.yaml
index 03bdee1..c46706e 100644
--- a/cip202/config.yaml
+++ b/cip202/config.yaml
@@ -4,7 +4,7 @@ jupyterhub::jupyterhub_config_hash:
             max: 1024
             def: 1024
         partition:
-            def: 'nodecpupool'
+            def: 'cpupool'
         ui:
             def: 'terminal'
 
diff --git a/ciq102/config.yaml b/ciq102/config.yaml
index f042d2b..025cc09 100644
--- a/ciq102/config.yaml
+++ b/ciq102/config.yaml
@@ -1,8 +1,8 @@
 jupyterhub::jupyterhub_config_hash:
-    SbatchForm:
-        memory:
-            max: 4098
-            def: 4098
+  SbatchForm:
+    memory:
+      max: 4098
+      def: 4098
 
 jupyterhub::kernel::venv::packages:
   - aiohttp
@@ -20,13 +20,11 @@ jupyterhub::kernel::venv::packages:
   - mthree
   - ply
   - pylatexenc
-  
 
 profile::software_stack::lmod_default_modules: ['StdEnv/2023', 'python/3.11', 'jupyterlab-apps/1.0']
 
 profile::accounts::skel_archives:
-    - filename: ciq102-main.zip
-      source: https://github.com/calculquebec/ciq102/archive/refs/heads/main.zip
-    - filename: mnq101-main.zip
-      source: https://github.com/calculquebec/mnq101/archive/refs/heads/main.zip
-
+  - filename: ciq102-main.zip
+    source: https://github.com/calculquebec/ciq102/archive/refs/heads/main.zip
+  - filename: mnq101-main.zip
+    source: https://github.com/calculquebec/mnq101/archive/refs/heads/main.zip
diff --git a/common/common.tf b/common/common.tf
index 8bf939c..8a942c8 100644
--- a/common/common.tf
+++ b/common/common.tf
@@ -51,23 +51,21 @@ data "tfe_workspace" "current" {
 locals {
   default_pod = {
     image = "AlmaLinux-9"
-    image_cpu = "snapshot-cpunode-2025.3-A9.6"
-    image_gpu = "snapshot-gpunode-2025.3-A9.6"
+    image_compute = "snapshot-cpunode-2026-A9.8-1"
+    image_map = {
+      cpupool = "snapshot-cpunode-2026-A9.8-1"
+      gpupool = "snapshot-gpunode-2026-A9.8-1"
+    }
     nb_users = 0
 
     nnodes = {
       cpu = 2
-      compute_node = 0
-      gpu = 0
-      cpupool = 0
-      gpupool = 0
-      jupyter = 0
       login = 1
-      gpupool12 = 0
-      gpupool16 = 0
-      gpupool80 = 0
-      gpupool16-cq = 0
-      gpupool12-j = 0
+    }
+    
+    features = {
+      gpu = ["gpu"],
+      gpupool = ["gpu"],
     }
 
     home_size = 80
@@ -86,9 +84,18 @@ locals {
     }
 
     cluster_purpose = "formation"
-    config_git_url = "https://github.com/calculquebec/puppet-magic_castle_formation.git"
-    config_version = "e2d4f36"
+    config_git_url = "https://github.com/computecanada/puppet-magic_castle.git"
+    config_version = "15.6.1"
 
+    node_flavors = {
+      arbutus = ["cpu", "compute-node", "cpupool", "gpu", "gpupool"],
+      beluga = ["cpu", "compute-node", "cpupool"]
+      juno = ["cpu", "cpupool", "gpu", "gpupool"]
+    }
+    tags = {
+      cpu = ["node"]
+      gpu = ["node"]
+    }
     instances_type_map = {
       arbutus = {
         mgmt = "p8-12gb"
@@ -96,7 +103,7 @@ locals {
         jupyter = "p4-6gb"
         cpu = "c8-30gb-186-avx2"
         cpupool = "c8-30gb-186-avx2"
-        compute_node = "p8-12gb"
+        compute-node = "p8-12gb"
         gpu = "g1-8gb-c4-22gb"
         gpupool = "g1-8gb-c4-22gb"
       }
@@ -106,44 +113,33 @@ locals {
         jupyter = "p4-7.5gb"
         cpu = "c8-60gb"
         cpupool = "c8-60gb"
-        compute_node = "p8-15gb"
+        compute-node = "p8-15gb"
       }
       juno = {
         mgmt = "ha4-15gb"
-        login = "c4-15gb"
+        login = "ha4-15gb"
         jupyter = "c4-15gb"
         cpu = "c8-30gb"
         cpupool = "c8-30gb"
 	gpu = "gpu16-240-3450gb-a100x1_cq"
         gpupool = "gpu12-120-850gb-a100x1_MC"
-        gpupool16 = "gpu16-240-3375gb-a100x1"
-        gpupool80 = "gpu13-240-2500gb-a100-80gx1"
-        gpupool12 = "gpu12-120-850gb-a100x1"
-	gpupool16-cq = "gpu16-240-3450gb-a100x1_cq"
-	gpupool12-j = "gpu12-120-850gb-a100x1_j"
       }
     }
 
+    disk_size = {
+      gpu = 50
+      gpupool = 50
+    }
+    
     mig = {
       gpu = { "1g.5gb" = 7 }
       gpupool = { "1g.5gb" = 7 }
-      gpupool16 = { "1g.5gb" = 7 }
-      gpupool80 = { "1g.10gb" = 7 }
-      gpupool12 = { "1g.5gb" = 7 }
-      gpupool16-cq = { "1g.5gb" = 7 }
-      gpupool12-j = { "1g.5gb" = 7 }
     }
 
     shard = {
       gpu = null
       gpupool = null
-      gpupool16 = null
-      gpupool80 = null
-      gpupool12 = null
-      gpupool16-cq = null
-      gpupool12-j = null
     }
-
   }
 
   user_quotas = {
@@ -168,198 +164,39 @@ locals {
   }
 
   default = {
-    instances_map = {
-      arbutus = {
-        mgmt = {
-          type = try(local.custom.instances_type_map.arbutus.mgmt, local.default_pod.instances_type_map.arbutus.mgmt),
-          tags = ["puppet", "mgmt", "nfs", "formation_extra", "cron"],
-          disk_size = 20,
-          count = 1
-        }
-        login = {
-          type = try(local.custom.instances_type_map.arbutus.login, local.default_pod.instances_type_map.arbutus.login),
-          tags = try(local.custom.nnodes.jupyter, local.default_pod.nnodes.jupyter) == 0 ? ["login", "public", "proxy"] : ["login", "public"],
-          disk_size = 20,
-          count = try(local.custom.nnodes.login, local.default_pod.nnodes.login)
-        }
-        jupyter = {
-          type = try(local.custom.instances_type_map.arbutus.jupyter, local.default_pod.instances_type_map.arbutus.jupyter),
-          tags = ["public", "proxy"],
-          disk_size = 20,
-          count = try(local.custom.nnodes.jupyter, local.default_pod.nnodes.jupyter)
-        }
-        nodecpu = {
-          type = try(local.custom.instances_type_map.arbutus.cpu, local.default_pod.instances_type_map.arbutus.cpu),
-          tags = ["node"],
-          count = try(local.custom.nnodes.cpu, local.default_pod.nnodes.cpu),
-          image = try(local.custom.image_cpu, local.default_pod.image_cpu),
-        }
-        compute-node = {
-          type = try(local.custom.instances_type_map.arbutus.compute_node, local.default_pod.instances_type_map.arbutus.compute_node),
-          tags = ["node"],
-          count = try(local.custom.nnodes.compute_node, local.default_pod.nnodes.compute_node),
-          image = try(local.custom.image_cpu, local.default_pod.image_cpu),
-        }
-        nodecpupool = {
-          type = try(local.custom.instances_type_map.arbutus.cpupool, local.default_pod.instances_type_map.arbutus.cpupool),
-          tags = ["node", "pool"],
-          count = try(local.custom.nnodes.cpupool, local.default_pod.nnodes.cpupool),
-          image = try(local.custom.image_cpu, local.default_pod.image_cpu),
-        }
-        nodegpu = {
-          type = try(local.custom.instances_type_map.arbutus.gpu, local.default_pod.instances_type_map.arbutus.gpu),
-          tags = ["node"],
-          count = try(local.custom.nnodes.gpu, local.default_pod.nnodes.gpu),
-          image = try(local.custom.image_gpu, local.default_pod.image_gpu),
-	  shard = try(local.custom.shard.gpu, local.default_pod.shard.gpu),
-        }
-        nodegpupool = {
-          type = try(local.custom.instances_type_map.arbutus.gpupool, local.default_pod.instances_type_map.arbutus.gpupool),
-          tags = ["node", "pool"],
-          count = try(local.custom.nnodes.gpupool, local.default_pod.nnodes.gpupool),
-          image = try(local.custom.image_gpu, local.default_pod.image_gpu),
-	  shard = try(local.custom.shard.gpupool, local.default_pod.shard.gpupool),
-        }
+    mgmt_instances = {
+      mgmt = {
+        type = try(local.custom.instances_type_map[var.cloud_name]["mgmt"], local.default_pod.instances_type_map[var.cloud_name]["mgmt"]),
+	tags = ["puppet", "mgmt", "nfs", "formation_extra", "cron"],
+	disk_size = 20,
+	count = 1
       }
-      beluga = {
-        mgmt = {
-          type = try(local.custom.instances_type_map.beluga.mgmt, local.default_pod.instances_type_map.beluga.mgmt),
-          tags = ["puppet", "mgmt", "nfs", "formation_extra", "cron"],
-          disk_size = 20,
-          count = 1
-        }
-        login = {
-          type = try(local.custom.instances_type_map.beluga.login, local.default_pod.instances_type_map.beluga.login),
-          tags = try(local.custom.nnodes.jupyter, local.default_pod.nnodes.jupyter) == 0 ? ["login", "public", "proxy"] : ["login", "public"],
-          disk_size = 20,
-          count = try(local.custom.nnodes.login, local.default_pod.nnodes.login)
-        }
-        jupyter = {
-          type = try(local.custom.instances_type_map.beluga.jupyter, local.default_pod.instances_type_map.beluga.jupyter),
-          tags = ["public", "proxy"],
-          disk_size = 20,
-          count = try(local.custom.nnodes.jupyter, local.default_pod.nnodes.jupyter)
-        }
-        nodecpu = {
-          type = try(local.custom.instances_type_map.beluga.cpu, local.default_pod.instances_type_map.beluga.cpu),
-          disk_size = 20
-          tags = ["node"],
-          count = try(local.custom.nnodes.cpu, local.default_pod.nnodes.cpu),
-          image = try(local.custom.image_cpu, local.default_pod.image_cpu),
-        }
-        compute-node = {
-          type = try(local.custom.instances_type_map.beluga.compute_node, local.default_pod.instances_type_map.beluga.compute_node),
-          disk_size = 20
-          tags = ["node"],
-          count = try(local.custom.nnodes.compute_node, local.default_pod.nnodes.compute_node),
-          image = try(local.custom.image_cpu, local.default_pod.image_cpu),
-        }
-        nodecpupool = {
-          type = try(local.custom.instances_type_map.beluga.cpupool, local.default_pod.instances_type_map.beluga.cpupool),
-          disk_size = 20
-          tags = ["node", "pool"],
-          count = try(local.custom.nnodes.cpupool, local.default_pod.nnodes.cpupool),
-          image = try(local.custom.image_cpu, local.default_pod.image_cpu),
-        }
+      login = {
+        type = try(local.custom.instances_type_map[var.cloud_name]["login"], local.default_pod.instances_type_map[var.cloud_name]["login"]),
+	tags = try(local.custom.nnodes.jupyter, 0) == 0 ? ["login", "public", "proxy"] : ["login", "public"],
+	disk_size = 20,
+	count = try(local.custom.nnodes.login, 1)
       }
-      juno = {
-        mgmt = {
-          type = try(local.custom.instances_type_map.juno.mgmt, local.default_pod.instances_type_map.juno.mgmt),
-          tags = ["puppet", "mgmt", "nfs", "formation_extra", "cron"],
-          disk_size = 20,
-          count = 1
-        }
-        login = {
-          type = try(local.custom.instances_type_map.juno.login, local.default_pod.instances_type_map.juno.login),
-          tags = try(local.custom.nnodes.jupyter, local.default_pod.nnodes.jupyter) == 0 ? ["login", "public", "proxy"] : ["login", "public"],
-          disk_size = 20,
-          count = try(local.custom.nnodes.login, local.default_pod.nnodes.login)
-        }
-        jupyter = {
-          type = try(local.custom.instances_type_map.juno.jupyter, local.default_pod.instances_type_map.juno.jupyter),
-          tags = ["public", "proxy"],
-          disk_size = 20,
-          count = try(local.custom.nnodes.jupyter, local.default_pod.nnodes.jupyter)
-        }
-        nodecpu = {
-          type = try(local.custom.instances_type_map.juno.cpu, local.default_pod.instances_type_map.juno.cpu),
-          disk_size = 20
-          tags = ["node"],
-          count = try(local.custom.nnodes.cpu, local.default_pod.nnodes.cpu),
-          image = try(local.custom.image_cpu, local.default_pod.image_cpu),
-        }
-        nodecpupool = {
-          type = try(local.custom.instances_type_map.juno.cpupool, local.default_pod.instances_type_map.juno.cpupool),
-          disk_size = 20
-          tags = ["node", "pool"],
-          count = try(local.custom.nnodes.cpupool, local.default_pod.nnodes.cpupool),
-          image = try(local.custom.image_cpu, local.default_pod.image_cpu),
-        }
-        nodegpu = {
-          type = try(local.custom.instances_type_map.juno.gpu, local.default_pod.instances_type_map.juno.gpu),
-          tags = ["node"],
-          count = try(local.custom.nnodes.gpu, local.default_pod.nnodes.gpu),
-          mig = try(local.custom.mig.gpu, local.default_pod.mig.gpu)
-          image = try(local.custom.image_gpu, local.default_pod.image_gpu),
-	  shard = try(local.custom.shard.gpu, local.default_pod.shard.gpu),
-          disk_size = "50"
-        }
-        nodegpupool = {
-          type = try(local.custom.instances_type_map.juno.gpupool, local.default_pod.instances_type_map.juno.gpupool),
-          tags = ["node", "pool"],
-          count = try(local.custom.nnodes.gpupool, 0),
-          mig = try(local.custom.mig.gpupool, local.default_pod.mig.gpupool)
-          image = try(local.custom.image_gpu, local.default_pod.image_gpu),
-	  shard = try(local.custom.shard.gpupool, local.default_pod.shard.gpupool),
-          disk_size = "50"
-        }
-        nodegpupool16 = {
-          type = try(local.custom.instances_type_map.juno.gpupool16, local.default_pod.instances_type_map.juno.gpupool16),
-          tags = ["node", "pool"],
-          count = try(local.custom.nnodes.gpupool16, 0),
-          mig = try(local.custom.mig.gpupool16, local.default_pod.mig.gpupool16)
-          image = try(local.custom.image_gpu, local.default_pod.image_gpu),
-	  shard = try(local.custom.shard.gpupool16, local.default_pod.shard.gpupool16),
-          disk_size = "50"
-        }
-        nodegpupool16-cq = {
-          type = try(local.custom.instances_type_map.juno.gpupool16-cq, local.default_pod.instances_type_map.juno.gpupool16-cq),
-          tags = ["node", "pool"],
-          count = try(local.custom.nnodes.gpupool16-cq, 0),
-          mig = try(local.custom.mig.gpupool16-cq, local.default_pod.mig.gpupool16-cq)
-          image = try(local.custom.image_gpu, local.default_pod.image_gpu),
-	  shard = try(local.custom.shard.gpupool16-cq, local.default_pod.shard.gpupool16-cq),
-          disk_size = "50"
-        }
-        nodegpupool12 = {
-          type = try(local.custom.instances_type_map.juno.gpupool12, local.default_pod.instances_type_map.juno.gpupool12),
-          tags = ["node", "pool"],
-          count = try(local.custom.nnodes.gpupool12, 0),
-          mig = try(local.custom.mig.gpupool12, local.default_pod.mig.gpupool12)
-          image = try(local.custom.image_gpu, local.default_pod.image_gpu),
-	  shard = try(local.custom.shard.gpupool12, local.default_pod.shard.gpupool12),
-          disk_size = "50"
-        }
-        nodegpupool12-j = {
-          type = try(local.custom.instances_type_map.juno.gpupool12-j, local.default_pod.instances_type_map.juno.gpupool12-j),
-          tags = ["node", "pool"],
-          count = try(local.custom.nnodes.gpupool12-j, 0),
-          mig = try(local.custom.mig.gpupool12-j, local.default_pod.mig.gpupool12-j)
-          image = try(local.custom.image_gpu, local.default_pod.image_gpu),
-	  shard = try(local.custom.shard.gpupool12-j, local.default_pod.shard.gpupool12-j),
-          disk_size = "50"
-        }
-        nodegpupool80 = {
-          type = try(local.custom.instances_type_map.juno.gpupool80, local.default_pod.instances_type_map.juno.gpupool80),
-          tags = ["node", "pool"],
-          count = try(local.custom.nnodes.gpupool80, 0),
-          mig = try(local.custom.mig.gpupool80, local.default_pod.mig.gpupool80)
-          image = try(local.custom.image_gpu, local.default_pod.image_gpu),
-	  shard = try(local.custom.shard.gpupool80, local.default_pod.shard.gpupool80),
-          disk_size = "50"
-        }
+      jupyter = {
+        type = try(local.custom.instances_type_map[var.cloud_name]["jupyter"], local.default_pod.instances_type_map[var.cloud_name]["jupyter"]),
+	tags = ["public", "proxy"],
+	disk_size = 20,
+	count = try(local.custom.nnodes.jupyter, 0)
       }
     }
+    compute_instances = {
+      for flavor in try(local.custom.node_flavors[var.cloud_name], local.custom.node_flavors, local.default_pod.node_flavors[var.cloud_name]):
+        flavor => {
+	  type = try(local.custom.instances_type_map[var.cloud_name][flavor], local.custom.instances_type_map[flavor], local.default_pod.instances_type_map[var.cloud_name][flavor])
+	  tags = try(local.custom.tags[flavor], local.default_pod.tags[flavor], ["node", "pool"])
+	  disk_size = try(local.custom.disk_size[flavor], local.default_pod.disk_size[flavor], 20)
+	  count = try(local.custom.nnodes[flavor], local.default_pod.nnodes[flavor], 0)
+	  image = try(local.custom.image_map[flavor], local.custom.image_compute, local.default_pod.image_map[flavor], local.default_pod.image_compute)
+	  mig = try(local.custom.mig[var.cloud_name][flavor], local.custom.mig[flavor], local.default_pod.mig[var.cloud_name][flavor], local.default_pod.mig[flavor], null)
+	  shard = try(local.custom.shard[flavor], local.default_pod.shard[flavor], null)
+	  features = try(local.custom.features[flavor], local.default_pod.features[flavor], ["cpu"])
+	}
+    }
     volumes_map = {
       arbutus = {
         nfs = {
@@ -385,7 +222,7 @@ locals {
     }
   }
 
-  instances = try(local.custom.instances, local.default.instances_map[var.cloud_name])
+  instances = try(local.custom.instances, merge(local.default.mgmt_instances, local.default.compute_instances))
   volumes = try(local.custom.volumes, local.default.volumes_map[var.cloud_name])
   cluster_purpose = try(local.custom.cluster_purpose, local.default_pod.cluster_purpose)
   nb_users = try(local.custom.nb_users, local.default_pod.nb_users)
@@ -407,7 +244,7 @@ locals {
 }
 
 module "openstack" {
-  source         = "git::https://github.com/calculquebec/magic_castle_formation.git//openstack?ref=formation"
+  source         = "git::https://github.com/computecanada/magic_castle.git//openstack?ref=15.6.0"
   config_git_url = try(local.custom.config_git_url, local.default_pod.config_git_url)
   config_version = try(local.custom.config_version, local.default_pod.config_version)
 
@@ -452,7 +289,7 @@ output "public_ip" {
 
 # Uncomment to register your domain name with CloudFlare
 module "dns" {
-  source           = "git::https://github.com/calculquebec/magic_castle_formation.git//dns/cloudflare?ref=formation"
+  source           = "git::https://github.com/computecanada/magic_castle.git//dns/cloudflare?ref=15.6.0"
   name             = module.openstack.cluster_name
   domain           = module.openstack.domain
   public_instances = module.openstack.public_instances
diff --git a/common/config.yaml b/common/config.yaml
index 0a701d3..f60aedd 100644
--- a/common/config.yaml
+++ b/common/config.yaml
@@ -48,6 +48,9 @@ jupyterhub::jupyterhub_config_hash:
       lock: true
     ui:
       def: 'lab'
+    feature:
+      lock: true
+
   SlurmFormSpawner:
     disable_form: true
     start_timeout: 900
@@ -87,12 +90,14 @@ profile::users::ldap::users:
 profile::freeipa::mokey::enable_user_signup: false
 profile::nfs::server::enable_client_quotas: true
 
-profile::slurm::base::slurm_version: '24.11'
 profile::slurm::base::suspend_time: 7200
 profile::slurm::base::resume_timeout: 7200
 profile::slurm::base::suspend_rate: 80
 profile::slurm::base::resume_rate: 80
 
+prometheus::storage_retention: '14d'
+
+
 jupyterhub::kernel::venv::pip_environment:
   PIP_NO_INDEX: 1
 
diff --git a/ecole/config.yaml b/ecole/config.yaml
index 8e65964..5b09413 100644
--- a/ecole/config.yaml
+++ b/ecole/config.yaml
@@ -1,3 +1,4 @@
+jupyterhub::kernel::venv::python: /cvmfs/soft.computecanada.ca/easybuild/software/2023/x86-64-v3/Compiler/gcccore/python/3.13.2/bin/python
 jupyterhub::jupyterhub_config_hash:
   SbatchForm:
     runtime:
@@ -23,6 +24,9 @@ jupyterhub::jupyterhub_config_hash:
       lock: true
     reservation:
       lock: true
+    partition:
+      def: 'cpubase_bycore_b1'
+      lock: true
   SlurmFormSpawner:
     disable_form: false
     start_timeout: 900
@@ -38,77 +42,60 @@ jupyterhub::jupyterhub_config_hash:
           runtime: 4
           memory: '2048'
           ui: 'lab'
-          partition: 'cpu'
+          gpus: 'gpu:0'
+          feature: ['gpu']
       IA_GPU:
         name: 'Séquence IA - GPU'
         params:
           nprocs: 2
           runtime: 4
-          memory: '2048'
+          memory: '4096'
           oversubscribe: false
           ui: 'lab'
-          partition: 'gpu'
           gpus: 'gpu:1'
+          feature: ['gpu']
       PYT:
         name: 'Séquence intro python'
         params:
           nprocs: 1
           runtime: 4
-          memory: '1024'
+          memory: '2560'
           oversubscribe: false
           ui: 'lab'
-          partition: 'cpu'
-
-profile::software_stack::lmod_default_modules: ['StdEnv/2023', 'gcc', 'cuda/12.2', 'mpi4py/4.0.3', 'jupyterlab-apps/1.0']
-jupyterhub::kernel::venv::packages:
-  - numpy>2
-  - pandas==2.2.3
-  - matplotlib==3.10.0
-  - plotnine==0.14.1
-  - altair==5.4.1
-  - vega_datasets
-  - vl_convert_python
-  - dask[array,distributed,diagnostics]==2025.2.0
-  - graphviz
-  - sparse
-  - scipy==1.15.1
-  - numba==0.61.2
-  - torch==2.6.0
-  - scikit-learn
-  - pillow
-  - pycuda==2025.1
-  - torchvision
+          gpus: 'gpu:0'
+          feature: ['cpu']
 
 profile::freeipa::mokey::enable_user_signup: true
-profile::freeipa::mokey::require_verify_admin: false
+profile::freeipa::mokey::require_verify_admin: true
+profile::slurm::base::suspend_time: 14400
 
 profile::accounts::skel_archives:
-  - filename: cip101.zip
-    source: https://github.com/calculquebec/cip101/archive/refs/heads/main.zip
   - filename: shell-lesson-data.zip
     source: https://swcarpentry.github.io/shell-novice/data/shell-lesson-data.zip
-  - filename: dat201.zip
-    source: https://github.com/calculquebec/dat201/archive/refs/heads/main.zip
-  - filename: intro-machine-learning.zip
-    source: https://github.com/calculquebec/intro-machine-learning/archive/refs/heads/master.zip
+  - filename: cip101.zip
+    source: https://github.com/calculquebec/cip101/archive/refs/heads/main.zip
   - filename: pyt101.zip
-    source: https://github.com/calculquebec/pyt101/archive/refs/heads/main.zip
+    source: https://github.com/calculquebec/pyt101/archive/refs/heads/ecole.zip
   - filename: pyt102.zip
     source: https://github.com/calculquebec/pyt102/archive/refs/heads/main.zip
+  - filename: dat201.zip
+    source: https://github.com/calculquebec/dat201/archive/refs/heads/main.zip
   - filename: dat203.zip
     source: https://github.com/calculquebec/dat203/archive/refs/heads/main.zip
-  - filename: ia101.zip
-    source: https://github.com/calculquebec/ia102/archive/refs/heads/master.zip
+  - filename: ia102.zip
+    source: https://github.com/calculquebec/ia102_ecole2026/archive/refs/heads/main.zip
   - filename: ia103.zip
-    source: https://github.com/calculquebec/ia103/archive/refs/heads/master.zip
+    source: https://github.com/calculquebec/ia103/archive/refs/heads/main.zip
+  - filename: intro-apprentissage-IA.zip
+    source: https://github.com/calculquebec/intro-apprentissage-IA/archive/refs/heads/main.zip
 
 cron::job:
   spawn_cpu_nodes:
-    command: "/opt/software/slurm/bin/scontrol update node=nodecpupool[1-15] state=power_up"
+    command: "/opt/software/slurm/bin/scontrol update node=cpupool[1-15] state=power_up"
     minute: '0'
     hour: '8'
-    date: '19,20,21'
-    month: '5'
+    date: '1,2,3,4,5'
+    month: '6'
     weekday: '*'
     user: 'root'
     description: 'spawn cpu nodes'
@@ -117,8 +104,8 @@ cron::job:
     command: "/opt/software/slurm/bin/scontrol update node=ALL state=power_up"
     minute: '0'
     hour: '8'
-    date: '22,23'
-    month: '5'
+    date: '1,2,3,4,5'
+    month: '6'
     weekday: '*'
     user: 'root'
     description: 'spawn all nodes'
diff --git a/ecole/main.tf b/ecole/main.tf
index 8d4a5e0..6d40705 100644
--- a/ecole/main.tf
+++ b/ecole/main.tf
@@ -3,37 +3,33 @@ locals {
  
   custom = {
     nnodes = {
-      cpu = 1
-      gpu = 1
+      cpu = 0
+      gpu = 0
       compute_node = 0
-      cpupool = 15
-      gpupool = 15
+      cpupool = 10
+      gpupool = 6
       # instance jupyter séparée
       jupyter = 1
 
-      # update git config
-      config_git_url = "https://github.com/computecanada/puppet-magic_castle.git"
-      config_version = "15.2.1"
     }
 
-    instances_type_map = {
-      juno = {
-        login = "ha4-15gb"
-      }
+    image_map = {
+      gpupool = "snapshot-gpunode-2026-A9.7-ecole"
+      cpupool = "snapshot-cpunode-2026-A9.7-ecole"
     }
-
     mig = {
       gpupool = { "1g.5gb" = 7 }
     }
 
-    image_cpu = "AlmaLinux-9"
-    image_gpu = "AlmaLinux-9"
-#    image_cpu = "snapshot-cpunode-2025-A9.4-ecole"
-#    image_gpu = "snapshot-gpunode-2025-A9.4-ecole"
-
     # taille des systèmes de fichiers. Les valeurs par défaut sont celles ci-dessous
     home_size = 250
     project_size = 200
     scratch_size = 100
+
+    user_quotas_sizes = {
+      home = "5g"
+      project = "4g"
+      scratch = "5g"
+    }
   }
 }
diff --git a/ecole/prefixes/cpupool/config.yaml b/ecole/prefixes/cpupool/config.yaml
new file mode 100644
index 0000000..4365800
--- /dev/null
+++ b/ecole/prefixes/cpupool/config.yaml
@@ -0,0 +1,20 @@
+profile::software_stack::lmod_default_modules: ['StdEnv/2023', 'gcc', 'jupyterlab-apps/1.0', 'python/3.13', 'ipython-kernel/3.13']
+jupyterhub::kernel::venv::packages:
+  - numpy>2
+  - pandas==3.0.0
+  - matplotlib==3.10.8
+  - plotnine==0.15.0
+  - altair==5.5.0
+  - vega_datasets
+  - vl_convert_python
+  - graphviz
+  - sparse
+  - scipy==1.17.0
+  - pillow
+  - shap
+  - umap-learn
+  - tqdm
+  - optuna
+  - xgboost
+  - imblearn
+  - seaborn
diff --git a/ecole/prefixes/gpupool/config.yaml b/ecole/prefixes/gpupool/config.yaml
new file mode 100644
index 0000000..3d40841
--- /dev/null
+++ b/ecole/prefixes/gpupool/config.yaml
@@ -0,0 +1,33 @@
+jupyterhub::kernel::venv::python: /cvmfs/soft.computecanada.ca/easybuild/software/2023/x86-64-v3/Compiler/gcccore/python/3.12.4/bin/python
+profile::software_stack::lmod_default_modules: ['StdEnv/2023', 'gcc', 'cuda/12.2', 'mpi4py/4.0.3', 'opencv/4.13.0', 'jupyterlab-apps/1.0', 'python/3.12', 'ipython-kernel/3.12']
+jupyterhub::kernel::venv::packages:
+  - numpy>2
+  - pandas==3.0.0
+  - matplotlib==3.10.8
+  - dask[array,distributed,diagnostics]==2026.1.2
+  - graphviz
+  - sparse
+  - scipy==1.17.0
+  - numba==0.65.0
+  - torch==2.11.0
+  - scikit-learn
+  - pillow
+  - pycuda==2025.1
+  - torchvision
+  - torch
+  - transformers
+  - vllm==0.21.0
+  - seaborn
+  - shap
+  - imblearn
+  - xgboost
+  - optuna
+  - tqdm
+  - umap-learn
+  - imageio
+  - hdbscan
+
+jupyterhub::kernel::venv::pip_environment:
+  PIP_NO_INDEX: 1
+  PYTHONPATH: /cvmfs/soft.computecanada.ca/easybuild/python/site-packages:/cvmfs/soft.computecanada.ca/custom/python/site-packages
+  EBPYTHONPREFIXES: /cvmfs/soft.computecanada.ca/easybuild/software/2023/x86-64-v3/Compiler/gcccore/scipy-stack/2026a:/cvmfs/soft.computecanada.ca/easybuild/software/2023/x86-64-v3/Compiler/gcc12/opencv/4.13.0:/cvmfs/soft.computecanada.ca/easybuild/software/2023/x86-64-v3/Compiler/gcc12/opencv/4.13.0:/cvmfs/soft.computecanada.ca/easybuild/software/2023/x86-64-v3/MPI/gcc12/openmpi4/mpi4py/4.0.3:/cvmfs/soft.computecanada.ca/easybuild/software/2023/x86-64-v3/Compiler/gcccore/ipykernel/2026a