diff --git a/.github/workflows/sdk-jobs-spark-automation-run_interactive_session_notebook.yml b/.github/workflows/sdk-jobs-spark-automation-run_interactive_session_notebook.yml
new file mode 100644
index 0000000000..8a2aa179ee
--- /dev/null
+++ b/.github/workflows/sdk-jobs-spark-automation-run_interactive_session_notebook.yml
@@ -0,0 +1,80 @@
+# This code is autogenerated.
+# Code is generated by running custom script: python3 readme.py
+# Any manual changes to this file may cause incorrect behavior.
+# Any manual changes will be overwritten if the code is regenerated.
+
+name: sdk-jobs-spark-automation-run_interactive_session_notebook
+# This file is created by sdk/python/readme.py.
+# Please do not edit directly.
+on:
+  workflow_dispatch:
+  schedule:
+    - cron: "30 11/12 * * *"
+  pull_request:
+    branches:
+      - main
+    paths:
+      - sdk/python/jobs/spark/automation/**
+      - .github/workflows/sdk-jobs-spark-automation-run_interactive_session_notebook.yml
+      - sdk/python/dev-requirements.txt
+      - infra/bootstrapping/**
+      - sdk/python/setup.sh
+concurrency:
+  group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
+  cancel-in-progress: true
+jobs:
+  build:
+    runs-on: ubuntu-latest
+    steps:
+    - name: check out repo
+      uses: actions/checkout@v2
+    - name: setup python
+      uses: actions/setup-python@v2
+      with:
+        python-version: "3.8"
+    - name: pip install notebook reqs
+      run: pip install -r sdk/python/dev-requirements.txt
+    - name: azure login
+      uses: azure/login@v1
+      with:
+        creds: ${{secrets.AZUREML_CREDENTIALS}}
+    - name: bootstrap resources
+      run: |
+          echo '${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}';
+          bash bootstrap.sh
+      working-directory: infra/bootstrapping
+      continue-on-error: false
+    - name: setup SDK
+      run: |
+          source "${{ github.workspace }}/infra/bootstrapping/sdk_helpers.sh";
+          source "${{ github.workspace }}/infra/bootstrapping/init_environment.sh";
+          bash setup.sh
+      working-directory: sdk/python
+      continue-on-error: true
+    - name: setup-cli
+      run: |
+          source "${{ github.workspace }}/infra/bootstrapping/sdk_helpers.sh";
+          source "${{ github.workspace }}/infra/bootstrapping/init_environment.sh";
+          bash setup.sh
+      working-directory: cli
+      continue-on-error: true
+    - name: setup spark resources
+      run: |
+          bash -x jobs/spark/setup_spark.sh jobs/spark/ jobs/spark/automation/run_interactive_session_notebook.ipynb
+      working-directory: sdk/python
+      continue-on-error: true
+    - name: run jobs/spark/automation/run_interactive_session_notebook.ipynb
+      run: |
+          source "${{ github.workspace }}/infra/bootstrapping/sdk_helpers.sh";
+          source "${{ github.workspace }}/infra/bootstrapping/init_environment.sh";
+          bash "${{ github.workspace }}/infra/bootstrapping/sdk_helpers.sh" generate_workspace_config "../../.azureml/config.json";
+          bash "${{ github.workspace }}/infra/bootstrapping/sdk_helpers.sh" replace_template_values "run_interactive_session_notebook.ipynb";
+          [ -f "../../.azureml/config" ] && cat "../../.azureml/config";
+          papermill -k python run_interactive_session_notebook.ipynb run_interactive_session_notebook.output.ipynb
+      working-directory: sdk/python/jobs/spark/automation
+    - name: upload notebook's working folder as an artifact
+      if: ${{ always() }}
+      uses: actions/upload-artifact@v2
+      with:
+        name: run_interactive_session_notebook
+        path: sdk/python/jobs/spark/automation
diff --git a/.github/workflows/sdk-jobs-spark-submit_spark_standalone_jobs_managed_vnet.yml b/.github/workflows/sdk-jobs-spark-submit_spark_standalone_jobs_managed_vnet.yml
new file mode 100644
index 0000000000..89d7aa0dc6
--- /dev/null
+++ b/.github/workflows/sdk-jobs-spark-submit_spark_standalone_jobs_managed_vnet.yml
@@ -0,0 +1,80 @@
+# This code is autogenerated.
+# Code is generated by running custom script: python3 readme.py
+# Any manual changes to this file may cause incorrect behavior.
+# Any manual changes will be overwritten if the code is regenerated.
+
+name: sdk-jobs-spark-submit_spark_standalone_jobs_managed_vnet
+# This file is created by sdk/python/readme.py.
+# Please do not edit directly.
+on:
+  workflow_dispatch:
+  schedule:
+    - cron: "14 1/12 * * *"
+  pull_request:
+    branches:
+      - main
+    paths:
+      - sdk/python/jobs/spark/**
+      - .github/workflows/sdk-jobs-spark-submit_spark_standalone_jobs_managed_vnet.yml
+      - sdk/python/dev-requirements.txt
+      - infra/bootstrapping/**
+      - sdk/python/setup.sh
+concurrency:
+  group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
+  cancel-in-progress: true
+jobs:
+  build:
+    runs-on: ubuntu-latest
+    steps:
+    - name: check out repo
+      uses: actions/checkout@v2
+    - name: setup python
+      uses: actions/setup-python@v2
+      with:
+        python-version: "3.8"
+    - name: pip install notebook reqs
+      run: pip install -r sdk/python/dev-requirements.txt
+    - name: azure login
+      uses: azure/login@v1
+      with:
+        creds: ${{secrets.AZUREML_CREDENTIALS}}
+    - name: bootstrap resources
+      run: |
+          echo '${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}';
+          bash bootstrap.sh
+      working-directory: infra/bootstrapping
+      continue-on-error: false
+    - name: setup SDK
+      run: |
+          source "${{ github.workspace }}/infra/bootstrapping/sdk_helpers.sh";
+          source "${{ github.workspace }}/infra/bootstrapping/init_environment.sh";
+          bash setup.sh
+      working-directory: sdk/python
+      continue-on-error: true
+    - name: setup-cli
+      run: |
+          source "${{ github.workspace }}/infra/bootstrapping/sdk_helpers.sh";
+          source "${{ github.workspace }}/infra/bootstrapping/init_environment.sh";
+          bash setup.sh
+      working-directory: cli
+      continue-on-error: true
+    - name: setup spark resources
+      run: |
+          bash -x jobs/spark/setup_spark.sh jobs/spark/ jobs/spark/submit_spark_standalone_jobs_managed_vnet.ipynb
+      working-directory: sdk/python
+      continue-on-error: true
+    - name: run jobs/spark/submit_spark_standalone_jobs_managed_vnet.ipynb
+      run: |
+          source "${{ github.workspace }}/infra/bootstrapping/sdk_helpers.sh";
+          source "${{ github.workspace }}/infra/bootstrapping/init_environment.sh";
+          bash "${{ github.workspace }}/infra/bootstrapping/sdk_helpers.sh" generate_workspace_config "../../.azureml/config.json";
+          bash "${{ github.workspace }}/infra/bootstrapping/sdk_helpers.sh" replace_template_values "submit_spark_standalone_jobs_managed_vnet.ipynb";
+          [ -f "../../.azureml/config" ] && cat "../../.azureml/config";
+          papermill -k python submit_spark_standalone_jobs_managed_vnet.ipynb submit_spark_standalone_jobs_managed_vnet.output.ipynb
+      working-directory: sdk/python/jobs/spark
+    - name: upload notebook's working folder as an artifact
+      if: ${{ always() }}
+      uses: actions/upload-artifact@v2
+      with:
+        name: submit_spark_standalone_jobs_managed_vnet
+        path: sdk/python/jobs/spark
diff --git a/sdk/python/data-wrangling/interactive_data_wrangling.ipynb b/sdk/python/data-wrangling/interactive_data_wrangling.ipynb
index f5939089b2..14e34f4b68 100644
--- a/sdk/python/data-wrangling/interactive_data_wrangling.ipynb
+++ b/sdk/python/data-wrangling/interactive_data_wrangling.ipynb
@@ -49,11 +49,15 @@
    "source": [
     "from pyspark.sql import SparkSession\n",
     "\n",
+    "key_vault_name = \"<KEY_VAULT_NAME>\"\n",
+    "access_key_secret_name = \"<ACCESS_KEY_SECRET_NAME>\"\n",
+    "storage_account_name = \"<STORAGE_ACCOUNT_NAME>\"\n",
+    "\n",
     "sc = SparkSession.builder.getOrCreate()\n",
     "token_library = sc._jvm.com.microsoft.azure.synapse.tokenlibrary.TokenLibrary\n",
-    "access_key = token_library.getSecret(\"<KEY_VAULT_NAME>\", \"<ACCESS_KEY_SECRET_NAME>\")\n",
+    "access_key = token_library.getSecret(key_vault_name, access_key_secret_name)\n",
     "sc._jsc.hadoopConfiguration().set(\n",
-    "    \"fs.azure.account.key.<STORAGE_ACCOUNT_NAME>.blob.core.windows.net\", access_key\n",
+    "    f\"fs.azure.account.key.{storage_account_name}.blob.core.windows.net\", access_key\n",
     ")"
    ]
   },
@@ -84,8 +88,11 @@
     "import pyspark.pandas as pd\n",
     "from pyspark.ml.feature import Imputer\n",
     "\n",
+    "blob_container_name = \"<BLOB_CONTAINER_NAME>\"\n",
+    "storage_account_name = \"<STORAGE_ACCOUNT_NAME>\"\n",
+    "\n",
     "df = pd.read_csv(\n",
-    "    \"wasbs://<BLOB_CONTAINER_NAME>@<STORAGE_ACCOUNT_NAME>.blob.core.windows.net/data/titanic.csv\",\n",
+    "    f\"wasbs://{blob_container_name}@{storage_account_name}.blob.core.windows.net/data/titanic.csv\",\n",
     "    index_col=\"PassengerId\",\n",
     ")\n",
     "imputer = Imputer(inputCols=[\"Age\"], outputCol=\"Age\").setStrategy(\n",
@@ -96,7 +103,7 @@
     ")  # Fill Cabin column with value \"None\" if missing\n",
     "df.dropna(inplace=True)  # Drop the rows which still have any missing value\n",
     "df.to_csv(\n",
-    "    \"wasbs://<BLOB_CONTAINER_NAME>@<STORAGE_ACCOUNT_NAME>.blob.core.windows.net/data/wrangled\",\n",
+    "    f\"wasbs://{blob_container_name}@{storage_account_name}.blob.core.windows.net/data/wrangled\",\n",
     "    index_col=\"PassengerId\",\n",
     ")"
    ]
@@ -141,11 +148,16 @@
    "source": [
     "from pyspark.sql import SparkSession\n",
     "\n",
+    "key_vault_name = \"<KEY_VAULT_NAME>\"\n",
+    "sas_token_secret_name = \"<SAS_TOKEN_SECRET_NAME>\"\n",
+    "blob_container_name = \"<BLOB_CONTAINER_NAME>\"\n",
+    "storage_account_name = \"<STORAGE_ACCOUNT_NAME>\"\n",
+    "\n",
     "sc = SparkSession.builder.getOrCreate()\n",
     "token_library = sc._jvm.com.microsoft.azure.synapse.tokenlibrary.TokenLibrary\n",
-    "sas_token = token_library.getSecret(\"<KEY_VAULT_NAME>\", \"<SAS_TOKEN_SECRET_NAME>\")\n",
+    "sas_token = token_library.getSecret(key_vault_name, sas_token_secret_name)\n",
     "sc._jsc.hadoopConfiguration().set(\n",
-    "    \"fs.azure.sas.<BLOB_CONTAINER_NAME>.<STORAGE_ACCOUNT_NAME>.blob.core.windows.net\",\n",
+    "    f\"fs.azure.sas.{blob_container_name}.{storage_account_name}.blob.core.windows.net\",\n",
     "    sas_token,\n",
     ")"
    ]
@@ -177,8 +189,11 @@
     "import pyspark.pandas as pd\n",
     "from pyspark.ml.feature import Imputer\n",
     "\n",
+    "blob_container_name = \"<BLOB_CONTAINER_NAME>\"\n",
+    "storage_account_name = \"<STORAGE_ACCOUNT_NAME>\"\n",
+    "\n",
     "df = pd.read_csv(\n",
-    "    \"wasbs://<BLOB_CONTAINER_NAME>@<STORAGE_ACCOUNT_NAME>.blob.core.windows.net/data/titanic.csv\",\n",
+    "    f\"wasbs://{blob_container_name}@{storage_account_name}.blob.core.windows.net/data/titanic.csv\",\n",
     "    index_col=\"PassengerId\",\n",
     ")\n",
     "imputer = Imputer(inputCols=[\"Age\"], outputCol=\"Age\").setStrategy(\n",
@@ -189,7 +204,7 @@
     ")  # Fill Cabin column with value \"None\" if missing\n",
     "df.dropna(inplace=True)  # Drop the rows which still have any missing value\n",
     "df.to_csv(\n",
-    "    \"wasbs://<BLOB_CONTAINER_NAME>@<STORAGE_ACCOUNT_NAME>.blob.core.windows.net/data/wrangled\",\n",
+    "    f\"wasbs://{blob_container_name}@{storage_account_name}.blob.core.windows.net/data/wrangled\",\n",
     "    index_col=\"PassengerId\",\n",
     ")"
    ]
@@ -236,8 +251,11 @@
     "import pyspark.pandas as pd\n",
     "from pyspark.ml.feature import Imputer\n",
     "\n",
+    "file_system_name = \"<FILE_SYSTEM_NAME>\"\n",
+    "gen2_storage_account_name = \"<GEN2_STORAGE_ACCOUNT_NAME>\"\n",
+    "\n",
     "df = pd.read_csv(\n",
-    "    \"abfss://<FILE_SYSTEM_NAME>@<STORAGE_ACCOUNT_NAME>.dfs.core.windows.net/data/titanic.csv\",\n",
+    "    f\"abfss://{file_system_name}@{gen2_storage_account_name}.dfs.core.windows.net/data/titanic.csv\",\n",
     "    index_col=\"PassengerId\",\n",
     ")\n",
     "imputer = Imputer(inputCols=[\"Age\"], outputCol=\"Age\").setStrategy(\n",
@@ -248,7 +266,7 @@
     ")  # Fill Cabin column with value \"None\" if missing\n",
     "df.dropna(inplace=True)  # Drop the rows which still have any missing value\n",
     "df.to_csv(\n",
-    "    \"abfss://<FILE_SYSTEM_NAME>@<STORAGE_ACCOUNT_NAME>.dfs.core.windows.net/data/wrangled\",\n",
+    "    f\"abfss://{file_system_name}@{gen2_storage_account_name}.dfs.core.windows.net/data/wrangled\",\n",
     "    index_col=\"PassengerId\",\n",
     ")"
    ]
@@ -272,7 +290,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "- To enable read and write access, assign **Contributor** and **Storage Blob Data Contributor** roles to the user identity.\n",
+    "- To enable read and write access, assign **Contributor** and **Storage Blob Data Contributor** roles to the Service Principal.\n",
     "- Set configuration properties as follows:\n",
     "    - Client ID property: `fs.azure.account.oauth2.client.id.<STORAGE_ACCOUNT_NAME>.dfs.core.windows.net`\n",
     "    - Client secret property: `fs.azure.account.oauth2.client.secret.<STORAGE_ACCOUNT_NAME>.dfs.core.windows.net`\n",
@@ -298,32 +316,39 @@
    "source": [
     "from pyspark.sql import SparkSession\n",
     "\n",
+    "key_vault_name = \"<KEY_VAULT_NAME>\"\n",
+    "client_id_secret_name = \"<CLIENT_ID_SECRET_NAME>\"\n",
+    "tenant_id_secret_name = \"<TENANT_ID_SECRET_NAME>\"\n",
+    "client_secret_name = \"<CLIENT_SECRET_NAME>\"\n",
+    "gen2_storage_account_name = \"<GEN2_STORAGE_ACCOUNT_NAME>\"\n",
+    "\n",
     "sc = SparkSession.builder.getOrCreate()\n",
     "token_library = sc._jvm.com.microsoft.azure.synapse.tokenlibrary.TokenLibrary\n",
     "\n",
     "# Set up service principal tenant ID, client ID and secret from Azure Key Vault\n",
-    "client_id = token_library.getSecret(\"<KEY_VAULT_NAME>\", \"<CLIENT_ID_SECRET_NAME>\")\n",
-    "tenant_id = token_library.getSecret(\"<KEY_VAULT_NAME>\", \"<TENANT_ID_SECRET_NAME>\")\n",
-    "client_secret = token_library.getSecret(\"<KEY_VAULT_NAME>\", \"<CLIENT_SECRET_NAME>\")\n",
+    "client_id = token_library.getSecret(key_vault_name, client_id_secret_name)\n",
+    "tenant_id = token_library.getSecret(key_vault_name, tenant_id_secret_name)\n",
+    "client_secret = token_library.getSecret(key_vault_name, client_secret_name)\n",
     "\n",
     "# Set up service principal which has access of the data\n",
     "sc._jsc.hadoopConfiguration().set(\n",
-    "    \"fs.azure.account.auth.type.<STORAGE_ACCOUNT_NAME>.dfs.core.windows.net\", \"OAuth\"\n",
+    "    f\"fs.azure.account.auth.type.{gen2_storage_account_name}.dfs.core.windows.net\",\n",
+    "    \"OAuth\",\n",
     ")\n",
     "sc._jsc.hadoopConfiguration().set(\n",
-    "    \"fs.azure.account.oauth.provider.type.<STORAGE_ACCOUNT_NAME>.dfs.core.windows.net\",\n",
+    "    f\"fs.azure.account.oauth.provider.type.{gen2_storage_account_name}.dfs.core.windows.net\",\n",
     "    \"org.apache.hadoop.fs.azurebfs.oauth2.ClientCredsTokenProvider\",\n",
     ")\n",
     "sc._jsc.hadoopConfiguration().set(\n",
-    "    \"fs.azure.account.oauth2.client.id.<STORAGE_ACCOUNT_NAME>.dfs.core.windows.net\",\n",
+    "    f\"fs.azure.account.oauth2.client.id.{gen2_storage_account_name}.dfs.core.windows.net\",\n",
     "    client_id,\n",
     ")\n",
     "sc._jsc.hadoopConfiguration().set(\n",
-    "    \"fs.azure.account.oauth2.client.secret.<STORAGE_ACCOUNT_NAME>.dfs.core.windows.net\",\n",
+    "    f\"fs.azure.account.oauth2.client.secret.{gen2_storage_account_name}.dfs.core.windows.net\",\n",
     "    client_secret,\n",
     ")\n",
     "sc._jsc.hadoopConfiguration().set(\n",
-    "    \"fs.azure.account.oauth2.client.endpoint.<STORAGE_ACCOUNT_NAME>.dfs.core.windows.net\",\n",
+    "    f\"fs.azure.account.oauth2.client.endpoint.{gen2_storage_account_name}.dfs.core.windows.net\",\n",
     "    \"https://login.microsoftonline.com/\" + tenant_id + \"/oauth2/token\",\n",
     ")"
    ]
@@ -355,8 +380,11 @@
     "import pyspark.pandas as pd\n",
     "from pyspark.ml.feature import Imputer\n",
     "\n",
+    "file_system_name = \"<FILE_SYSTEM_NAME>\"\n",
+    "gen2_storage_account_name = \"<GEN2_STORAGE_ACCOUNT_NAME>\"\n",
+    "\n",
     "df = pd.read_csv(\n",
-    "    \"abfss://<FILE_SYSTEM_NAME>@<STORAGE_ACCOUNT_NAME>.dfs.core.windows.net/data/titanic.csv\",\n",
+    "    f\"abfss://{file_system_name}@{gen2_storage_account_name}.dfs.core.windows.net/data/titanic.csv\",\n",
     "    index_col=\"PassengerId\",\n",
     ")\n",
     "imputer = Imputer(inputCols=[\"Age\"], outputCol=\"Age\").setStrategy(\n",
@@ -367,7 +395,7 @@
     ")  # Fill Cabin column with value \"None\" if missing\n",
     "df.dropna(inplace=True)  # Drop the rows which still have any missing value\n",
     "df.to_csv(\n",
-    "    \"abfss://<FILE_SYSTEM_NAME>@<STORAGE_ACCOUNT_NAME>.dfs.core.windows.net/data/wrangled\",\n",
+    "    f\"abfss://{file_system_name}@{gen2_storage_account_name}.dfs.core.windows.net/data/wrangled\",\n",
     "    index_col=\"PassengerId\",\n",
     ")"
    ]
diff --git a/sdk/python/data-wrangling/interactive_data_wrangling.py b/sdk/python/data-wrangling/interactive_data_wrangling.py
new file mode 100644
index 0000000000..6d30261ef8
--- /dev/null
+++ b/sdk/python/data-wrangling/interactive_data_wrangling.py
@@ -0,0 +1,152 @@
+## Interactive Data Wrangling using Apache Spark in Azure Machine Learning. Before executing these sample codes in an Azure Machine Learning Notebook, select **Serverless Spark Compute** under **Azure Machine Learning Serverless Spark** or select an attached Synapse Spark pool under **Synapse Spark pools** from the **Compute** selection menu. It is highly recommened to follow the documentation page: [Interactive data wrangling with Apache Spark in Azure Machine Learning](https://learn.microsoft.com/azure/machine-learning/interactive-data-wrangling-with-apache-spark-azure-ml) for more details related to the code samples provided in this notebook.
+
+### Access and wrangle Azure Blob storage data using Access Key
+
+#### First, Set the access key as configuration property `fs.azure.account.key.<STORAGE_ACCOUNT_NAME>.blob.core.windows.net`.
+
+from pyspark.sql import SparkSession
+
+key_vault_name = "<KEY_VAULT_NAME>"
+access_key_secret_name = "<ACCESS_KEY_SECRET_NAME>"
+storage_account_name = "<STORAGE_ACCOUNT_NAME>"
+
+sc = SparkSession.builder.getOrCreate()
+token_library = sc._jvm.com.microsoft.azure.synapse.tokenlibrary.TokenLibrary
+access_key = token_library.getSecret(key_vault_name, access_key_secret_name)
+sc._jsc.hadoopConfiguration().set(
+    f"fs.azure.account.key.{storage_account_name}.blob.core.windows.net", access_key
+)
+
+#### Access data using `wasbs://` URI and perform data wrangling.
+import pyspark.pandas as pd
+from pyspark.ml.feature import Imputer
+
+blob_container_name = "<BLOB_CONTAINER_NAME>"
+storage_account_name = "<STORAGE_ACCOUNT_NAME>"
+
+df = pd.read_csv(
+    f"wasbs://{blob_container_name}@{storage_account_name}.blob.core.windows.net/data/titanic.csv",
+    index_col="PassengerId",
+)
+imputer = Imputer(inputCols=["Age"], outputCol="Age").setStrategy(
+    "mean"
+)  # Replace missing values in Age column with the mean value
+df.fillna(
+    value={"Cabin": "None"}, inplace=True
+)  # Fill Cabin column with value "None" if missing
+df.dropna(inplace=True)  # Drop the rows which still have any missing value
+df.to_csv(
+    f"wasbs://{blob_container_name}@{storage_account_name}.blob.core.windows.net/data/wrangled",
+    index_col="PassengerId",
+)
+
+### Access and wrangle Azure Blob storage data using SAS token
+
+#### First, set the SAS token as configuration property `fs.azure.sas.<BLOB_CONTAINER_NAME>.<STORAGE_ACCOUNT_NAME>.blob.core.windows.net`.
+from pyspark.sql import SparkSession
+
+key_vault_name = "<KEY_VAULT_NAME>"
+sas_token_secret_name = "<SAS_TOKEN_SECRET_NAME>"
+blob_container_name = "<BLOB_CONTAINER_NAME>"
+storage_account_name = "<STORAGE_ACCOUNT_NAME>"
+
+sc = SparkSession.builder.getOrCreate()
+token_library = sc._jvm.com.microsoft.azure.synapse.tokenlibrary.TokenLibrary
+sas_token = token_library.getSecret(key_vault_name, sas_token_secret_name)
+sc._jsc.hadoopConfiguration().set(
+    f"fs.azure.sas.{blob_container_name}.{storage_account_name}.blob.core.windows.net",
+    sas_token,
+)
+
+#### Access data using `wasbs://` URI and perform data wrangling.
+import pyspark.pandas as pd
+from pyspark.ml.feature import Imputer
+
+blob_container_name = "<BLOB_CONTAINER_NAME>"
+storage_account_name = "<STORAGE_ACCOUNT_NAME>"
+
+df = pd.read_csv(
+    f"wasbs://{blob_container_name}@{storage_account_name}.blob.core.windows.net/data/titanic.csv",
+    index_col="PassengerId",
+)
+imputer = Imputer(inputCols=["Age"], outputCol="Age").setStrategy(
+    "mean"
+)  # Replace missing values in Age column with the mean value
+df.fillna(
+    value={"Cabin": "None"}, inplace=True
+)  # Fill Cabin column with value "None" if missing
+df.dropna(inplace=True)  # Drop the rows which still have any missing value
+df.to_csv(
+    f"wasbs://{blob_container_name}@{storage_account_name}.blob.core.windows.net/data/wrangled",
+    index_col="PassengerId",
+)
+
+### Access and wrangle ADLS Gen 2 data using User Identity passthrough
+
+#### - To enable read and write access, assign **Contributor** and **Storage Blob Data Contributor** roles to the user identity.
+#### - Access data using `abfss://` URI and perform data wrangling.
+import pyspark.pandas as pd
+from pyspark.ml.feature import Imputer
+
+file_system_name = "<FILE_SYSTEM_NAME>"
+gen2_storage_account_name = "<GEN2_STORAGE_ACCOUNT_NAME>"
+
+df = pd.read_csv(
+    f"abfss://{file_system_name}@{gen2_storage_account_name}.dfs.core.windows.net/data/titanic.csv",
+    index_col="PassengerId",
+)
+imputer = Imputer(inputCols=["Age"], outputCol="Age").setStrategy(
+    "mean"
+)  # Replace missing values in Age column with the mean value
+df.fillna(
+    value={"Cabin": "None"}, inplace=True
+)  # Fill Cabin column with value "None" if missing
+df.dropna(inplace=True)  # Drop the rows which still have any missing value
+df.to_csv(
+    f"abfss://{file_system_name}@{gen2_storage_account_name}.dfs.core.windows.net/data/wrangled",
+    index_col="PassengerId",
+)
+
+
+### Access and wrangle data using credentialed AzureML Blob Datastore
+#### - Access data using `azureml://` URI and perform data wrangling.
+import pyspark.pandas as pd
+from pyspark.ml.feature import Imputer
+
+df = pd.read_csv(
+    "azureml://datastores/workspaceblobstore/paths/data/titanic.csv",
+    index_col="PassengerId",
+)
+imputer = Imputer(inputCols=["Age"], outputCol="Age").setStrategy(
+    "mean"
+)  # Replace missing values in Age column with the mean value
+df.fillna(
+    value={"Cabin": "None"}, inplace=True
+)  # Fill Cabin column with value "None" if missing
+df.dropna(inplace=True)  # Drop the rows which still have any missing value
+df.to_csv(
+    "azureml://datastores/workspaceblobstore/paths/data/wrangled",
+    index_col="PassengerId",
+)
+
+### Access and wrangle data using credentialless AzureML Blob Datastore
+#### - To enable read and write access, assign **Contributor** and **Storage Blob Data Contributor** roles to the user identity on the Azure Blob storage account that the datastore points to.
+#### - Access data using `azureml://` URI and perform data wrangling.
+import pyspark.pandas as pd
+from pyspark.ml.feature import Imputer
+
+df = pd.read_csv(
+    "azureml://datastores/credlessblobdatastore/paths/data/titanic.csv",
+    index_col="PassengerId",
+)
+imputer = Imputer(inputCols=["Age"], outputCol="Age").setStrategy(
+    "mean"
+)  # Replace missing values in Age column with the mean value
+df.fillna(
+    value={"Cabin": "None"}, inplace=True
+)  # Fill Cabin column with value "None" if missing
+df.dropna(inplace=True)  # Drop the rows which still have any missing value
+df.to_csv(
+    "azureml://datastores/credlessblobdatastore/paths/data/wrangled",
+    index_col="PassengerId",
+)
diff --git a/sdk/python/jobs/spark/automation/create_credential_less_data_store.yml b/sdk/python/jobs/spark/automation/create_credential_less_data_store.yml
new file mode 100644
index 0000000000..4c56659dcb
--- /dev/null
+++ b/sdk/python/jobs/spark/automation/create_credential_less_data_store.yml
@@ -0,0 +1,6 @@
+$schema: https://azuremlschemas.azureedge.net/latest/azureBlob.schema.json
+name: <CREDENTIAL_LESS_DATA_STORE_NAME>
+type: azure_blob
+description: Credential-less datastore pointing to a blob container.
+account_name: <STORAGE_ACCOUNT_NAME>
+container_name: <BLOB_CONTAINER_NAME>
\ No newline at end of file
diff --git a/sdk/python/jobs/spark/automation/run_interactive_session_notebook.ipynb b/sdk/python/jobs/spark/automation/run_interactive_session_notebook.ipynb
new file mode 100644
index 0000000000..1d87178f33
--- /dev/null
+++ b/sdk/python/jobs/spark/automation/run_interactive_session_notebook.ipynb
@@ -0,0 +1,79 @@
+{
+ "cells": [
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Use a serverless Spark compute"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "You should have an attached Synapse Spark pool available in your workspace. Please see documentation page: [Attach and manage a Synapse Spark pool in Azure Machine Learning (preview)](https://learn.microsoft.com/azure/machine-learning/how-to-manage-synapse-spark-pool) for more details.\n",
+    "\n",
+    "**Note** - To ensure successful execution of Spark job, the identity being used for the Spark job should be assigned **Contributor** and **Storage Blob Data Contributor** roles on the Azure storage account used for data input and output."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from azure.ai.ml import MLClient, spark, Input, Output\n",
+    "from azure.identity import DefaultAzureCredential\n",
+    "\n",
+    "subscription_id = \"<SUBSCRIPTION_ID>\"\n",
+    "resource_group = \"<RESOURCE_GROUP>\"\n",
+    "workspace = \"<AML_WORKSPACE_NAME>\"\n",
+    "ml_client = MLClient(\n",
+    "    DefaultAzureCredential(), subscription_id, resource_group, workspace\n",
+    ")\n",
+    "\n",
+    "spark_job = spark(\n",
+    "    display_name=\"interactive_data_wrangling\",\n",
+    "    code=\"../../../data-wrangling\",\n",
+    "    entry={\"file\": \"interactive_data_wrangling.py\"},\n",
+    "    driver_cores=1,\n",
+    "    driver_memory=\"2g\",\n",
+    "    executor_cores=2,\n",
+    "    executor_memory=\"2g\",\n",
+    "    executor_instances=2,\n",
+    "    resources={\n",
+    "        \"instance_type\": \"Standard_E8S_V3\",\n",
+    "        \"runtime_version\": \"3.2.0\",\n",
+    "    },\n",
+    ")\n",
+    "\n",
+    "returned_spark_job = ml_client.jobs.create_or_update(spark_job)\n",
+    "\n",
+    "print(returned_spark_job.id)\n",
+    "# Wait until the job completes\n",
+    "ml_client.jobs.stream(returned_spark_job.name)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3.10 - SDK V2",
+   "language": "python",
+   "name": "python310-sdkv2"
+  },
+  "language_info": {
+   "name": "python",
+   "version": "3.7.10"
+  },
+  "orig_nbformat": 4,
+  "vscode": {
+   "interpreter": {
+    "hash": "6aeff17a1aa7735c2f7cb3a6d691fe1b4d4c3b8d2d650f644ad0f24e1b8e3f3f"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/sdk/python/jobs/spark/user-assigned-identity.yml b/sdk/python/jobs/spark/automation/user-assigned-identity.yml
similarity index 100%
rename from sdk/python/jobs/spark/user-assigned-identity.yml
rename to sdk/python/jobs/spark/automation/user-assigned-identity.yml
diff --git a/sdk/python/jobs/spark/setup_spark.sh b/sdk/python/jobs/spark/setup_spark.sh
index f03786ceac..4c9c98ddca 100644
--- a/sdk/python/jobs/spark/setup_spark.sh
+++ b/sdk/python/jobs/spark/setup_spark.sh
@@ -16,10 +16,10 @@ SQL_ADMIN_LOGIN_USER="automation"
 SQL_ADMIN_LOGIN_PASSWORD="auto123!"
 SPARK_POOL_NAME="automationpool"
 SPARK_POOL_ADMIN_ROLE_ID="6e4bf58a-b8e1-4cc3-bbf9-d73143322b78"
-USER_IDENTITY_YML="jobs/spark/user-assigned-identity.yml"
-#OUTBOUND_RULE_NAME="automationtestrule"
-#KEY_VAULT_NAME=$(az ml workspace show --query key_vault -o tsv | cut -d'/' -f9-)
-#ACCESS_KEY_SECRET_NAME="automationsecret"
+USER_IDENTITY_YML=$1"automation/user-assigned-identity.yml"
+CREAT_CREDENTIAL_LESS_DS_YML=$1"automation/create_credential_less_data_store.yml"
+AZURE_REGION_NAME=${LOCATION}
+OUTBOUND_RULE_NAME="automationtestrule"
 #</create_variables>
 
 if [[ "$2" == *"resources/compute"* ]]
@@ -44,25 +44,123 @@ az identity create --name $AML_USER_MANAGED_ID --resource-group $RESOURCE_GROUP
 AML_USER_MANAGED_ID_OID=$(az identity show --resource-group $RESOURCE_GROUP -n $AML_USER_MANAGED_ID --query principalId -o tsv)
 #</create_uai>
 
-#<create_attached_resources>
-az storage account create --name $GEN2_STORAGE_NAME --resource-group $RESOURCE_GROUP --location $LOCATION --sku Standard_LRS --kind StorageV2 --enable-hierarchical-namespace true
-az storage fs create -n $GEN2_FILE_SYSTEM --account-name $GEN2_STORAGE_NAME
-az synapse workspace create --name $SYNAPSE_WORKSPACE_NAME --resource-group $RESOURCE_GROUP --storage-account $GEN2_STORAGE_NAME --file-system $GEN2_FILE_SYSTEM --sql-admin-login-user $SQL_ADMIN_LOGIN_USER --sql-admin-login-password $SQL_ADMIN_LOGIN_PASSWORD --location $LOCATION
-az role assignment create --role "Storage Blob Data Owner" --assignee $AML_USER_MANAGED_ID_OID --scope /subscriptions/$SUBSCRIPTION_ID/resourceGroups/$RESOURCE_GROUP/providers/Microsoft.Storage/storageAccounts/$GEN2_STORAGE_NAME/blobServices/default/containers/$GEN2_FILE_SYSTEM
-az synapse spark pool create --name $SPARK_POOL_NAME --workspace-name $SYNAPSE_WORKSPACE_NAME --resource-group $RESOURCE_GROUP --spark-version 3.2 --node-count 3 --node-size Medium --min-node-count 3 --max-node-count 10 --enable-auto-scale true
-az synapse workspace firewall-rule create --name allowAll --workspace-name $SYNAPSE_WORKSPACE_NAME --resource-group $RESOURCE_GROUP --start-ip-address 0.0.0.0 --end-ip-address 255.255.255.255
-#</create_attached_resources>
+#<setup_vnet_resources>
+if [[ "$2" == *"managed_vnet"* ]]
+then
+	AML_WORKSPACE_NAME=${AML_WORKSPACE_NAME}-vnet
+	AZURE_STORAGE_ACCOUNT="blobstoragevnet"
+	BLOB_CONTAINER_NAME="blobstoragevnetcontainer"
+	GEN2_STORAGE_ACCOUNT_NAME="gen2storagevnet"
+	ADLS_CONTAINER_NAME="gen2containervnet"
+	az storage account create -n $AZURE_STORAGE_ACCOUNT -g $RESOURCE_GROUP -l $LOCATION --sku Standard_LRS
+	az storage container create -n $BLOB_CONTAINER_NAME --account-name $AZURE_STORAGE_ACCOUNT
+
+	az storage account create --name $GEN2_STORAGE_ACCOUNT_NAME --resource-group $RESOURCE_GROUP --location $LOCATION --sku Standard_LRS --kind StorageV2 --enable-hierarchical-namespace true
+	az storage container create -n $ADLS_CONTAINER_NAME --account-name $GEN2_STORAGE_ACCOUNT_NAME
+
+	ACCOUNT_KEY=$(az storage account keys list --account-name $AZURE_STORAGE_ACCOUNT --query "[0].value" -o tsv)
+	ACCESS_KEY_SECRET_NAME="autotestaccountkey"
+	KEY_VAULT=$(az ml workspace show -g $RESOURCE_GROUP -n $AML_WORKSPACE_NAME --query key_vault -o tsv)
+	KEY_VAULT_NAME=$(basename "$KEY_VAULT")
+	az keyvault secret set --name $ACCESS_KEY_SECRET_NAME --vault-name $KEY_VAULT_NAME --value $ACCOUNT_KEY
+
+	#<replace_template_values>
+	sed -i "s/<SUBSCRIPTION_ID>/$SUBSCRIPTION_ID/g;
+		s/<RESOURCE_GROUP>/$RESOURCE_GROUP/g;
+		s/<AML_WORKSPACE_NAME>/$AML_WORKSPACE_NAME/g;
+		s/<AZURE_REGION_NAME>/$AZURE_REGION_NAME/g;
+		s/<STORAGE_ACCOUNT_NAME>/$AZURE_STORAGE_ACCOUNT/g;
+		s/<OUTBOUND_RULE_NAME>/$OUTBOUND_RULE_NAME/g;
+		s/<KEY_VAULT_NAME>/$KEY_VAULT_NAME/g;
+		s/<ACCESS_KEY_SECRET_NAME>/$ACCESS_KEY_SECRET_NAME/g;
+		s/<BLOB_CONTAINER_NAME>/$BLOB_CONTAINER_NAME/g;
+		s/<GEN2_STORAGE_ACCOUNT_NAME>/$GEN2_STORAGE_ACCOUNT_NAME/g;
+		s/<ADLS_CONTAINER_NAME>/$ADLS_CONTAINER_NAME/g;" $2
+#</setup_vnet_resources>
+#<setup_interactive_session_resources>
+elif [[ "$2" == *"run_interactive_session_notebook"* ]]
+then
+	#NOTEBOOK_TO_CONVERT="../../data-wrangling/interactive_data_wrangling.ipynb"
+	#ipython nbconvert $NOTEBOOK_TO_CONVERT --to script
+
+	ACCOUNT_KEY=$(az storage account keys list --account-name $AZURE_STORAGE_ACCOUNT --query "[0].value" -o tsv)
+	ACCESS_KEY_SECRET_NAME="autotestaccountkey"
+
+	KEY_VAULT_NAME="autotestsparkkv"
+	az keyvault create -n $KEY_VAULT_NAME -g $RESOURCE_GROUP
+
+	NOTEBOOK_PY="./data-wrangling/interactive_data_wrangling.py"
+	az keyvault secret set --name $ACCESS_KEY_SECRET_NAME --vault-name $KEY_VAULT_NAME --value $ACCOUNT_KEY
+
+	END_TIME=`date -u -d "60 minutes" '+%Y-%m-%dT%H:%MZ'`
+	SAS_TOKEN=`az storage container generate-sas -n $AZUREML_DEFAULT_CONTAINER --account-name $AZURE_STORAGE_ACCOUNT --https-only --permissions dlrw --expiry $END_TIME -o tsv`
+	SAS_TOKEN_SECRET_NAME="autotestsastoken"
+	az keyvault secret set --name $SAS_TOKEN_SECRET_NAME --vault-name $KEY_VAULT_NAME --value $SAS_TOKEN
 
-sed -i "s/<SUBSCRIPTION_ID>/$SUBSCRIPTION_ID/g;
+	GEN2_STORAGE_ACCOUNT_NAME=${RESOURCE_GROUP}gen2
+	FILE_SYSTEM_NAME=${RESOURCE_GROUP}file
+	az storage account create --name $GEN2_STORAGE_ACCOUNT_NAME --resource-group $RESOURCE_GROUP --location $LOCATION --sku Standard_LRS --kind StorageV2 --enable-hierarchical-namespace true
+	az storage fs create -n $FILE_SYSTEM_NAME --account-name $GEN2_STORAGE_ACCOUNT_NAME
+	az role assignment create --role "Storage Blob Data Contributor" --assignee $AML_USER_MANAGED_ID_OID --scope /subscriptions/$SUBSCRIPTION_ID/resourceGroups/$RESOURCE_GROUP/providers/Microsoft.Storage/storageAccounts/$GEN2_STORAGE_ACCOUNT_NAME/blobServices/default/containers/$FILE_SYSTEM_NAME
+
+	TITANIC_DATA_FILE="titanic.csv"
+	az storage fs file upload --file-system $FILE_SYSTEM_NAME --source ./data-wrangling/data/$TITANIC_DATA_FILE --path data/$TITANIC_DATA_FILE --account-name $GEN2_STORAGE_ACCOUNT_NAME
+
+	# SERVICE_PRINCIPAL_NAME="${RESOURCE_GROUP}sp"
+	# az ad sp create-for-rbac --name $SERVICE_PRINCIPAL_NAME
+	# LIST_SP_DETAILS=$(az ad sp list --display-name $SERVICE_PRINCIPAL_NAME)
+	# SP_APPID=$(echo $LIST_SP_DETAILS | jq -r '[0].appId')
+	# SP_OBJECTID=$(echo $LIST_SP_DETAILS | jq -r '[0].id')
+	# SP_TENANTID=$(echo $LIST_SP_DETAILS | jq -r '[0].appOwnerOrganizationId')
+	# SPA_SP_SECRET=$(az ad sp credential reset --id $SP_OBJECTID --query "password")
+
+	# CLIENT_ID_SECRET_NAME="autotestspsecretclient"
+	# TENANT_ID_SECRET_NAME="autotestspsecrettenant"
+	# CLIENT_SECRET_NAME="autotestspsecret"
+	# az keyvault secret set --name $CLIENT_ID_SECRET_NAME --vault-name $KEY_VAULT_NAME --value $SP_APPID
+	# az keyvault secret set --name $TENANT_ID_SECRET_NAME --vault-name $KEY_VAULT_NAME --value $SP_TENANTID
+	# az keyvault secret set --name $CLIENT_SECRET_NAME --vault-name $KEY_VAULT_NAME --value $SPA_SP_SECRET
+	# az role assignment create --role "Storage Blob Data Contributor" --assignee $SP_APPID --scope /subscriptions/$SUBSCRIPTION_ID/resourceGroups/$RESOURCE_GROUP/providers/Microsoft.Storage/storageAccounts/$GEN2_STORAGE_ACCOUNT_NAME/blobServices/default/containers/$FILE_SYSTEM_NAME
+	# az role assignment create --role "Contributor" --assignee $SP_APPID --scope /subscriptions/$SUBSCRIPTION_ID/resourceGroups/$RESOURCE_GROUP/providers/Microsoft.Storage/storageAccounts/$GEN2_STORAGE_ACCOUNT_NAME/blobServices/default/containers/$FILE_SYSTEM_NAME
+
+	CREDENTIAL_LESS_DATA_STORE_NAME="credlessblobdatastore"
+	sed -i "s/<STORAGE_ACCOUNT_NAME>/$AZURE_STORAGE_ACCOUNT/g;
+		s/<BLOB_CONTAINER_NAME>/$AZUREML_DEFAULT_CONTAINER/g
+		s/<CREDENTIAL_LESS_DATA_STORE_NAME>/$CREDENTIAL_LESS_DATA_STORE_NAME/g;" $CREAT_CREDENTIAL_LESS_DS_YML
+	az ml datastore create --file  $CREAT_CREDENTIAL_LESS_DS_YML --resource-group $RESOURCE_GROUP --workspace-name $AML_WORKSPACE_NAME
+	# USER="azuremlsdk"
+	sed -i "s/<KEY_VAULT_NAME>/$KEY_VAULT_NAME/g;
+		s/<ACCESS_KEY_SECRET_NAME>/$ACCESS_KEY_SECRET_NAME/g;
+		s/<STORAGE_ACCOUNT_NAME>/$AZURE_STORAGE_ACCOUNT/g;
+		s/<BLOB_CONTAINER_NAME>/$AZUREML_DEFAULT_CONTAINER/g
+		s/<SAS_TOKEN_SECRET_NAME>/$SAS_TOKEN_SECRET_NAME/g;
+		s/<GEN2_STORAGE_ACCOUNT_NAME>/$GEN2_STORAGE_ACCOUNT_NAME/g
+		s/<FILE_SYSTEM_NAME>/$FILE_SYSTEM_NAME/g;" $NOTEBOOK_PY
+
+	sed -i "s/<SUBSCRIPTION_ID>/$SUBSCRIPTION_ID/g;
 		s/<RESOURCE_GROUP>/$RESOURCE_GROUP/g;
-		s/<AML_USER_MANAGED_ID>/$AML_USER_MANAGED_ID/g;" $USER_IDENTITY_YML
+		s/<AML_WORKSPACE_NAME>/$AML_WORKSPACE_NAME/g;" $2
+#</setup_interactive_session_resources>
+else
+	#<create_attached_resources>
+	az storage account create --name $GEN2_STORAGE_NAME --resource-group $RESOURCE_GROUP --location $LOCATION --sku Standard_LRS --kind StorageV2 --enable-hierarchical-namespace true
+	az storage fs create -n $GEN2_FILE_SYSTEM --account-name $GEN2_STORAGE_NAME
+	az synapse workspace create --name $SYNAPSE_WORKSPACE_NAME --resource-group $RESOURCE_GROUP --storage-account $GEN2_STORAGE_NAME --file-system $GEN2_FILE_SYSTEM --sql-admin-login-user $SQL_ADMIN_LOGIN_USER --sql-admin-login-password $SQL_ADMIN_LOGIN_PASSWORD --location $LOCATION
+	az role assignment create --role "Storage Blob Data Owner" --assignee $AML_USER_MANAGED_ID_OID --scope /subscriptions/$SUBSCRIPTION_ID/resourceGroups/$RESOURCE_GROUP/providers/Microsoft.Storage/storageAccounts/$GEN2_STORAGE_NAME/blobServices/default/containers/$GEN2_FILE_SYSTEM
+	az synapse spark pool create --name $SPARK_POOL_NAME --workspace-name $SYNAPSE_WORKSPACE_NAME --resource-group $RESOURCE_GROUP --spark-version 3.2 --node-count 3 --node-size Medium --min-node-count 3 --max-node-count 10 --enable-auto-scale true
+	az synapse workspace firewall-rule create --name allowAll --workspace-name $SYNAPSE_WORKSPACE_NAME --resource-group $RESOURCE_GROUP --start-ip-address 0.0.0.0 --end-ip-address 255.255.255.255
+	#</create_attached_resources>
+
+	sed -i "s/<SUBSCRIPTION_ID>/$SUBSCRIPTION_ID/g;
+			s/<RESOURCE_GROUP>/$RESOURCE_GROUP/g;
+			s/<AML_USER_MANAGED_ID>/$AML_USER_MANAGED_ID/g;" $USER_IDENTITY_YML
 
-#<assign_uai_to_workspace>
-az ml workspace update --subscription $SUBSCRIPTION_ID --resource-group $RESOURCE_GROUP --name $AML_WORKSPACE_NAME --file $USER_IDENTITY_YML
-#</assign_uai_to_workspace>
+	#<assign_uai_to_workspace>
+	az ml workspace update --subscription $SUBSCRIPTION_ID --resource-group $RESOURCE_GROUP --name $AML_WORKSPACE_NAME --file $USER_IDENTITY_YML
+	#</assign_uai_to_workspace>
 
-#<attache_spark>
-sed -i "s/<SUBSCRIPTION_ID>/$SUBSCRIPTION_ID/g;
+	#<attache_spark>
+	sed -i "s/<SUBSCRIPTION_ID>/$SUBSCRIPTION_ID/g;
 		s/<RESOURCE_GROUP>/$RESOURCE_GROUP/g;
 		s/<AML_WORKSPACE_NAME>/$AML_WORKSPACE_NAME/g;
 		s/<ATTACHED_SPARK_POOL_NAME>/$ATTACHED_SPARK_POOL_NAME/g;
@@ -72,27 +170,26 @@ sed -i "s/<SUBSCRIPTION_ID>/$SUBSCRIPTION_ID/g;
 		s/<ATTACHED_SPARK_POOL_NAME_UAI>/$ATTACHED_SPARK_POOL_NAME_UAI/g;
 		s/<AML_USER_MANAGED_ID>/$AML_USER_MANAGED_ID/g;" $ATTACH_SPARK_PY
 
-python $ATTACH_SPARK_PY
-#</attache_spark>
+	python $ATTACH_SPARK_PY
+	#</attache_spark>
 
-COMPUTE_MANAGED_IDENTITY=$(az ml compute show --name $ATTACHED_SPARK_POOL_NAME --resource-group $RESOURCE_GROUP --workspace-name $AML_WORKSPACE_NAME --query identity.principal_id --out tsv)
+	COMPUTE_MANAGED_IDENTITY=$(az ml compute show --name $ATTACHED_SPARK_POOL_NAME --resource-group $RESOURCE_GROUP --workspace-name $AML_WORKSPACE_NAME --query identity.principal_id --out tsv)
 
-if [[ ! -z "$COMPUTE_MANAGED_IDENTITY" ]]
-then
-  az synapse role assignment create --workspace-name $SYNAPSE_WORKSPACE_NAME --role $SPARK_POOL_ADMIN_ROLE_ID --assignee $COMPUTE_MANAGED_IDENTITY
-fi
+	if [[ ! -z "$COMPUTE_MANAGED_IDENTITY" ]]
+	then
+	az synapse role assignment create --workspace-name $SYNAPSE_WORKSPACE_NAME --role $SPARK_POOL_ADMIN_ROLE_ID --assignee $COMPUTE_MANAGED_IDENTITY
+	fi
 
-COMPUTE_MANAGED_IDENTITY=$(az ml compute show --name $ATTACHED_SPARK_POOL_NAME_UAI --resource-group $RESOURCE_GROUP --workspace-name $AML_WORKSPACE_NAME --query identity.principal_id --out tsv)
+	COMPUTE_MANAGED_IDENTITY=$(az ml compute show --name $ATTACHED_SPARK_POOL_NAME_UAI --resource-group $RESOURCE_GROUP --workspace-name $AML_WORKSPACE_NAME --query identity.principal_id --out tsv)
 
-if [[ ! -z "$COMPUTE_MANAGED_IDENTITY" ]]
-then
-  az synapse role assignment create --workspace-name $SYNAPSE_WORKSPACE_NAME --role $SPARK_POOL_ADMIN_ROLE_ID --assignee $COMPUTE_MANAGED_IDENTITY
-fi
+	if [[ ! -z "$COMPUTE_MANAGED_IDENTITY" ]]
+	then
+	az synapse role assignment create --workspace-name $SYNAPSE_WORKSPACE_NAME --role $SPARK_POOL_ADMIN_ROLE_ID --assignee $COMPUTE_MANAGED_IDENTITY
+	fi
 
-az synapse role assignment create --workspace-name $SYNAPSE_WORKSPACE_NAME --role $SPARK_POOL_ADMIN_ROLE_ID --assignee $AML_USER_MANAGED_ID
+	az synapse role assignment create --workspace-name $SYNAPSE_WORKSPACE_NAME --role $SPARK_POOL_ADMIN_ROLE_ID --assignee $AML_USER_MANAGED_ID_OID
 
-#<replace_template_values>
-sed -i "s/<SUBSCRIPTION_ID>/$SUBSCRIPTION_ID/g;
+	sed -i "s/<SUBSCRIPTION_ID>/$SUBSCRIPTION_ID/g;
 		s/<RESOURCE_GROUP>/$RESOURCE_GROUP/g;
 		s/<AML_WORKSPACE_NAME>/$AML_WORKSPACE_NAME/g;
 		s/<SYNAPSE_WORKSPACE_NAME>/$SYNAPSE_WORKSPACE_NAME/g;
@@ -101,4 +198,4 @@ sed -i "s/<SUBSCRIPTION_ID>/$SUBSCRIPTION_ID/g;
 		s/<USER_ASSIGNED_IDENTITY_CLIENT_ID>/$AML_USER_MANAGED_ID/g;
 		s/<ATTACHED_SPARK_POOL_NAME_UAI>/$ATTACHED_SPARK_POOL_NAME_UAI/g;
 		s/<AML_USER_MANAGED_ID>/$AML_USER_MANAGED_ID/g;" $2
-#</replace_template_values>
+fi
diff --git a/sdk/python/jobs/spark/submit_spark_pipeline_jobs.ipynb b/sdk/python/jobs/spark/submit_spark_pipeline_jobs.ipynb
index 0c3594274a..8f7b672f80 100644
--- a/sdk/python/jobs/spark/submit_spark_pipeline_jobs.ipynb
+++ b/sdk/python/jobs/spark/submit_spark_pipeline_jobs.ipynb
@@ -55,6 +55,7 @@
     "subscription_id = \"<SUBSCRIPTION_ID>\"\n",
     "resource_group = \"<RESOURCE_GROUP>\"\n",
     "workspace = \"<AML_WORKSPACE_NAME>\"\n",
+    "attached_spark_pool_name = \"<ATTACHED_SPARK_POOL_NAME>\"\n",
     "ml_client = MLClient(\n",
     "    DefaultAzureCredential(), subscription_id, resource_group, workspace\n",
     ")\n",
@@ -91,7 +92,7 @@
     "    )\n",
     "    spark_step.outputs.wrangled_data.mode = InputOutputModes.DIRECT\n",
     "    spark_step.identity = ManagedIdentityConfiguration()\n",
-    "    spark_step.compute = \"<ATTACHED_SPARK_POOL_NAME>\"\n",
+    "    spark_step.compute = attached_spark_pool_name\n",
     "\n",
     "\n",
     "pipeline = spark_pipeline(\n",
@@ -132,6 +133,7 @@
     "subscription_id = \"<SUBSCRIPTION_ID>\"\n",
     "resource_group = \"<RESOURCE_GROUP>\"\n",
     "workspace = \"<AML_WORKSPACE_NAME>\"\n",
+    "attached_spark_pool_name_uai = \"<ATTACHED_SPARK_POOL_NAME_UAI>\"\n",
     "ml_client = MLClient(\n",
     "    DefaultAzureCredential(), subscription_id, resource_group, workspace\n",
     ")\n",
@@ -168,7 +170,7 @@
     "    )\n",
     "    spark_step.outputs.wrangled_data.mode = InputOutputModes.DIRECT\n",
     "    spark_step.identity = UserIdentityConfiguration()\n",
-    "    spark_step.compute = \"<ATTACHED_SPARK_POOL_NAME_UAI>\"\n",
+    "    spark_step.compute = attached_spark_pool_name_uai\n",
     "\n",
     "\n",
     "pipeline = spark_pipeline(\n",
@@ -209,6 +211,7 @@
     "subscription_id = \"<SUBSCRIPTION_ID>\"\n",
     "resource_group = \"<RESOURCE_GROUP>\"\n",
     "workspace = \"<AML_WORKSPACE_NAME>\"\n",
+    "attached_spark_pool_name = \"<ATTACHED_SPARK_POOL_NAME>\"\n",
     "ml_client = MLClient(\n",
     "    DefaultAzureCredential(), subscription_id, resource_group, workspace\n",
     ")\n",
@@ -242,7 +245,7 @@
     "        path=\"azureml://datastores/workspaceblobstore/paths/data/wrangled/\",\n",
     "    )\n",
     "    spark_step.outputs.wrangled_data.mode = InputOutputModes.DIRECT\n",
-    "    spark_step.compute = \"<ATTACHED_SPARK_POOL_NAME>\"\n",
+    "    spark_step.compute = attached_spark_pool_name\n",
     "\n",
     "\n",
     "pipeline = spark_pipeline(\n",
diff --git a/sdk/python/jobs/spark/submit_spark_standalone_jobs.ipynb b/sdk/python/jobs/spark/submit_spark_standalone_jobs.ipynb
index b202b67b7a..522a421ad7 100644
--- a/sdk/python/jobs/spark/submit_spark_standalone_jobs.ipynb
+++ b/sdk/python/jobs/spark/submit_spark_standalone_jobs.ipynb
@@ -54,6 +54,7 @@
     "subscription_id = \"<SUBSCRIPTION_ID>\"\n",
     "resource_group = \"<RESOURCE_GROUP>\"\n",
     "workspace = \"<AML_WORKSPACE_NAME>\"\n",
+    "attached_spark_pool_name = \"<ATTACHED_SPARK_POOL_NAME>\"\n",
     "ml_client = MLClient(\n",
     "    DefaultAzureCredential(), subscription_id, resource_group, workspace\n",
     ")\n",
@@ -67,7 +68,7 @@
     "    executor_cores=2,\n",
     "    executor_memory=\"2g\",\n",
     "    executor_instances=2,\n",
-    "    compute=\"<ATTACHED_SPARK_POOL_NAME>\",\n",
+    "    compute=attached_spark_pool_name,\n",
     "    inputs={\n",
     "        \"titanic_data\": Input(\n",
     "            type=\"uri_file\",\n",
@@ -113,6 +114,7 @@
     "subscription_id = \"<SUBSCRIPTION_ID>\"\n",
     "resource_group = \"<RESOURCE_GROUP>\"\n",
     "workspace = \"<AML_WORKSPACE_NAME>\"\n",
+    "attached_spark_pool_name = \"<ATTACHED_SPARK_POOL_NAME_UAI>\"\n",
     "ml_client = MLClient(\n",
     "    DefaultAzureCredential(), subscription_id, resource_group, workspace\n",
     ")\n",
@@ -126,7 +128,7 @@
     "    executor_cores=2,\n",
     "    executor_memory=\"2g\",\n",
     "    executor_instances=2,\n",
-    "    compute=\"<ATTACHED_SPARK_POOL_NAME_UAI>\",\n",
+    "    compute=attached_spark_pool_name,\n",
     "    inputs={\n",
     "        \"titanic_data\": Input(\n",
     "            type=\"uri_file\",\n",
@@ -172,6 +174,7 @@
     "subscription_id = \"<SUBSCRIPTION_ID>\"\n",
     "resource_group = \"<RESOURCE_GROUP>\"\n",
     "workspace = \"<AML_WORKSPACE_NAME>\"\n",
+    "attached_spark_pool_name = \"<ATTACHED_SPARK_POOL_NAME>\"\n",
     "ml_client = MLClient(\n",
     "    DefaultAzureCredential(), subscription_id, resource_group, workspace\n",
     ")\n",
@@ -185,7 +188,7 @@
     "    executor_cores=2,\n",
     "    executor_memory=\"2g\",\n",
     "    executor_instances=2,\n",
-    "    compute=\"<ATTACHED_SPARK_POOL_NAME>\",\n",
+    "    compute=attached_spark_pool_name,\n",
     "    inputs={\n",
     "        \"titanic_data\": Input(\n",
     "            type=\"uri_file\",\n",
diff --git a/sdk/python/jobs/spark/submit_spark_standalone_jobs_managed_vnet.ipynb b/sdk/python/jobs/spark/submit_spark_standalone_jobs_managed_vnet.ipynb
index 088a07d41c..efdd4ecea9 100644
--- a/sdk/python/jobs/spark/submit_spark_standalone_jobs_managed_vnet.ipynb
+++ b/sdk/python/jobs/spark/submit_spark_standalone_jobs_managed_vnet.ipynb
@@ -183,7 +183,7 @@
     "# Provisioning managed VNet with Spark support\n",
     "include_spark = True\n",
     "provision_network_result = ml_client.workspaces.begin_provision_network(\n",
-    "    ws_name, include_spark\n",
+    "    workspace_name=ws_name, include_spark=include_spark\n",
     ").result()"
    ]
   },
@@ -592,7 +592,7 @@
     "\n",
     "# This will add a new outbound rule to existing rules\n",
     "rule_name = \"<OUTBOUND_RULE_NAME>\"  # This name should be unique\n",
-    "adls_storage_account = \"<STORAGE_ACCOUNT_NAME>\"\n",
+    "adls_storage_account = \"<GEN2_STORAGE_ACCOUNT_NAME>\"\n",
     "service_resource_id = f\"/subscriptions/{subscription_id}/resourceGroups/{resource_group}/providers/Microsoft.Storage/storageAccounts/{adls_storage_account}\"\n",
     "subresource_target = \"dfs\"\n",
     "spark_enabled = True\n",
@@ -747,7 +747,7 @@
     "# Enter the Azure Data Lake Storage (ADLS) Gen2 account name and container name.\n",
     "# The file `titanic.csv` should be placed inside folder `data`\n",
     "# created in the Azure Data Lake Storage (ADLS) Gen2 container.\n",
-    "adls_storage_account = \"<STORAGE_ACCOUNT_NAME>\"\n",
+    "adls_storage_account = \"<GEN2_STORAGE_ACCOUNT_NAME>\"\n",
     "container_name = \"<ADLS_CONTAINER_NAME>\"\n",
     "\n",
     "spark_job = spark(\n",
@@ -862,7 +862,9 @@
    },
    "outputs": [],
    "source": [
-    "ml_client.workspaces.begin_delete(name=ws_name, delete_dependent_resources=True)"
+    "ml_client.workspaces.begin_delete(\n",
+    "    name=ws_name, permanently_delete=True, delete_dependent_resources=True\n",
+    ")"
    ]
   }
  ],
diff --git a/sdk/python/readme.py b/sdk/python/readme.py
index c4042abbbc..9dacd9cf1b 100644
--- a/sdk/python/readme.py
+++ b/sdk/python/readme.py
@@ -19,7 +19,6 @@
     "train-hyperparameter-tune-deploy-with-keras",
     "train-hyperparameter-tune-deploy-with-tensorflow",
     "interactive_data_wrangling",
-    "submit_spark_standalone_jobs_managed_vnet",
     # mlflow SDK samples notebooks
     "mlflow_sdk_online_endpoints_progresive",
     "mlflow_sdk_online_endpoints",