diff --git a/notebook/vm-hub-deployments.json b/notebook/vm-hub-deployments.json
index 800a924..784f64b 100644
--- a/notebook/vm-hub-deployments.json
+++ b/notebook/vm-hub-deployments.json
@@ -20,7 +20,7 @@
 				"spark.dynamicAllocation.enabled": "true",
 				"spark.dynamicAllocation.minExecutors": "1",
 				"spark.dynamicAllocation.maxExecutors": "5",
-				"spark.autotune.trackingId": "d7703b70-8d43-4558-9f11-178ad4c7e2d1"
+				"spark.autotune.trackingId": "73d3940e-03d6-472f-bfd7-1a97688cb4b3"
 			}
 		},
 		"metadata": {
@@ -77,7 +77,7 @@
 					"import pyspark.sql.window as W\r\n",
 					"from pyspark.sql import Row"
 				],
-				"execution_count": 103
+				"execution_count": 102
 			},
 			{
 				"cell_type": "code",
@@ -98,7 +98,7 @@
 				"source": [
 					"storageAccount = 's037costmgmt'"
 				],
-				"execution_count": 76
+				"execution_count": 103
 			},
 			{
 				"cell_type": "code",
@@ -122,7 +122,7 @@
 					"LINKED_SERVICE_NAME = 'ACM_Toolkit_kv'\r\n",
 					"hubAutomationConnectionString = mssparkutils.credentials.getSecret(KEY_VAULT_NAME , 'hubautomation-sa-connectionstring', LINKED_SERVICE_NAME)"
 				],
-				"execution_count": 77
+				"execution_count": 104
 			},
 			{
 				"cell_type": "code",
@@ -146,7 +146,7 @@
 					"    'RG-TERMINAL_SERVERS-SCUS'\r\n",
 					"]"
 				],
-				"execution_count": 100
+				"execution_count": 105
 			},
 			{
 				"cell_type": "markdown",
@@ -179,7 +179,7 @@
 					"pricesheet_source_path = f'abfss://usage@{storageAccount}.dfs.core.windows.net/pricesheet/portal-export/pricesheet-latest'\r\n",
 					"pricesheet_df = spark.read.format('parquet').load(pricesheet_source_path)"
 				],
-				"execution_count": 89
+				"execution_count": 106
 			},
 			{
 				"cell_type": "code",
@@ -281,7 +281,7 @@
 					"# Hourly cost of license per vCPU\r\n",
 					"hourly_vcpu_cost = yearly_license_cost / (license_count * HOURS_PER_YEAR * VCPUS_PER_LICENSE)"
 				],
-				"execution_count": 91
+				"execution_count": 93
 			},
 			{
 				"cell_type": "markdown",
@@ -356,7 +356,7 @@
 					"cost_path = monthly_path = f'abfss://usage@{storageAccount}.dfs.core.windows.net/exports/monthly/ACMMonthlyActualCost/*/Extended_v3_ACMMonthlyActualCost_*.parquet'\r\n",
 					"cost_df = spark.read.format('parquet').load(cost_path)"
 				],
-				"execution_count": 93
+				"execution_count": 112
 			},
 			{
 				"cell_type": "code",