AML - Idle Shutdown test

docs/en/rules/Azure.ML.ComputeIdleShutdown.md

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+---
+reviewed: 2023-10-06
+severity: Critical
+pillar: Cost Optimization
+category: Provision
+resource: ML
+online version: https://azure.github.io/PSRule.Rules.Azure/en/rules/Azure.ML.ComputeIdleShutdown/
+---
+
+# ML Compute Idle Shutdown
+
+## SYNOPSIS
+
+Use ML - Compute Instances configured for idle shutdown.
+
+## DESCRIPTION
+
+Machine Learning uses compute instances as a training or inference compute for development and testing. It's similar to a virtual machine on the cloud.
+
+To avoid getting charged for a compute instance that is switched on but not being actively used, you can configure when to automatically shut down compute instances due to inactivity.
+
+## RECOMMENDATION
+
+Consider configuring ML - Compute Instances to automatically shutdown after a period of idle use as part of a broader cost optimization strategy. 
+
+## EXAMPLES
+
+### Configure with Azure template
+
+To deploy an ML - compute instance that complies with this rule:
+
+- Provide a idle shutdown time as an ISO 8601 format string, i.e. 15mins = "PT15M"
+- Define the "idleTimeBeforeShutdown" as this value 
+
+For example:
+
+```json
+{
+  "type": "Microsoft.MachineLearningServices/workspaces/computes",
+  "apiVersion": "2023-04-01",
+  "name": "[format('{0}/{1}', 'example-ws', parameters('name'))]",
+  "location": "[parameters('location')]",
+  "properties": {
+    "managedResourceGroupId": "[subscriptionResourceId('Microsoft.Resources/resourceGroups', 'example-mg')]",
+    "computeType": "ComputeInstance",
+    "properties": {
+      "vmSize": "[parameters('vmSize')]",
+      "idleTimeBeforeShutdown": "[parameters('idleTimeBeforeShutdown')]"
+    }
+  }
+}
+```
+
+### Configure with Bicep
+
+To deploy an ML - compute instance that complies with this rule:
+
+- Provide a idle shutdown time as an ISO 8601 format string, i.e. 15mins = 'PT15M'
+- Define the "idleTimeBeforeShutdown" as this value 
+
+For example:
+
+```bicep
+resource aml_compute_instance 'Microsoft.MachineLearningServices/workspaces/computes@2023-04-01' ={
+  name: '${mlWorkspace.name}/${name}'
+  location: location
+  properties:{
+    managedResourceGroupId: managedRg.id
+    computeType: 'ComputeInstance'
+    properties: {
+      vmSize: vmSize 
+      idleTimeBeforeShutdown: idleTimeBeforeShutdown // this must be a string in ISO 8601 format
+    }
+  }
+}
+
+## LINKS
+
+- [Configure idle shutdown](https://learn.microsoft.com/azure/machine-learning/how-to-create-compute-instance?view=azureml-api-2&tabs=azure-cli#configure-idle-shutdown)
+- [ML - Compute objects](https://learn.microsoft.com/azure/templates/microsoft.machinelearningservices/workspaces/computes?pivots=deployment-language-bicep#compute-objects)
+- [ML - Workspaces](https://learn.microsoft.com/azure/templates/microsoft.machinelearningservices/2023-04-01/workspaces?pivots=deployment-language-bicep)
+- [ML Compute](https://learn.microsoft.com/azure/machine-learning/azure-machine-learning-glossary?view=azureml-api-2#compute)
+- [AI + Machine Learning cost estimates](https://learn.microsoft.com/azure/well-architected/cost/provision-ai-ml)

docs/en/rules/Azure.ML.ComputeVnet.md

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+---
+reviewed: 2023-10-10
+severity: Critical
+pillar: Security
+category: Networking
+resource: ML
+online version: https://azure.github.io/PSRule.Rules.Azure/en/rules/Azure.ML.ComputeVnet/
+---
+
+# ML Compute hosted in VNet
+
+## SYNOPSIS
+
+Azure Machine Learning Computes should be hosted in a virtual network (VNet).
+
+## DESCRIPTION
+
+Azure Virtual Networks (VNets) provide enhanced security and isolation for your Azure Machine Learning Compute Clusters and Instances, as well as subnets, access control policies, and other features to further restrict access. When a compute is configured with a virtual network, it is not publicly addressable and can only be accessed from virtual machines and applications within the virtual network.
+
+## RECOMMENDATION
+
+ML - Compute should be hosted in a virtual network (VNet) as part of a broader security strategy. 
+
+## EXAMPLES
+
+### Configure with Azure template
+
+To deploy an ML - compute that complies with this rule:
+
+- update the compute properties to reference a specific subnet.
+
+For example:
+
+```json
+
+{
+    "type": "Microsoft.MachineLearningServices/workspaces/computes",
+    "apiVersion": "2023-04-01",
+    "name": "[format('{0}/{1}', 'example-ws', parameters('name'))]",
+    "location": "[parameters('location')]",
+    "properties": {
+      "managedResourceGroupId": "[subscriptionResourceId('Microsoft.Resources/resourceGroups', 'example-rg')]",
+      "computeType": "[parameters('computeType')]",
+      "properties": {
+        "vmSize": "[parameters('vmSize')]",
+          "subnet": {
+            "id": "[parameters('subnetId')]"
+          }
+      }
+    }
+}
+
+```
+
+### Configure with Bicep
+
+To deploy an ML - compute that complies with this rule:
+
+- update the compute properties to reference a specific subnet.
+
+For example:
+
+```bicep
+
+resource aml_compute_instance 'Microsoft.MachineLearningServices/workspaces/computes@2023-04-01' ={
+  name: '${mlWorkspace.name}/${name}'
+  location: location
+
+  properties:{
+    managedResourceGroupId: managedRg.id
+    computeType: ComputeType
+    properties: {
+      vmSize: vmSize 
+      subnet:{
+        id: subnet.id
+      }
+    }
+  }
+}
+```
+
+
+## LINKS
+
+- [Managed compute in a managed virtual network](https://learn.microsoft.com/azure/machine-learning/how-to-managed-network-compute?view=azureml-api-2&tabs=azure-cli)
+- [ML - Network security and isolation](https://learn.microsoft.com/azure/machine-learning/concept-enterprise-security?view=azureml-api-2#network-security-and-isolation)
+- [ML - Compute objects](https://learn.microsoft.com/azure/templates/microsoft.machinelearningservices/workspaces/computes?pivots=deployment-language-bicep#resource-format)
+- [ML - Workspaces](https://learn.microsoft.com/azure/templates/microsoft.machinelearningservices/2023-04-01/workspaces?pivots=deployment-language-bicep)
+- [ML Compute](https://learn.microsoft.com/azure/machine-learning/azure-machine-learning-glossary?view=azureml-api-2#compute)
+- [WAF - Azure services for securing network connectivity](https://learn.microsoft.com/azure/well-architected/security/design-network-connectivity)
+

docs/en/rules/Azure.ML.DisableLocalAuth.md

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+---
+reviewed: 2023-10-10
+severity: Critical
+pillar: Security
+category: Identity and Access Management
+resource: ML
+online version: https://azure.github.io/PSRule.Rules.Azure/en/rules/Azure.ML.DisableLocalAuth/
+---
+
+# ML Compute has local authentication disabled
+
+## SYNOPSIS
+
+Azure Machine Learning compute resources should have local authentication methods disabled.
+
+## DESCRIPTION
+
+Disabling local authentication methods improves security by ensuring that Machine Learning Computes require Azure Active Directory identities exclusively for authentication. 
+
+## RECOMMENDATION
+
+ML - Compute should be configured with local authentication disabled as part of a broader security strategy. 
+
+## EXAMPLES
+
+### Configure with Azure template
+
+To deploy an ML - compute that complies with this rule:
+
+- Set the `disableLocalAuth` property value to true.
+
+For example:
+
+```json
+
+{
+    "type": "Microsoft.MachineLearningServices/workspaces/computes",
+    "apiVersion": "2023-04-01",
+    "name": "[format('{0}/{1}', 'example-ws', parameters('name'))]",
+    "location": "[parameters('location')]",
+    "properties": {
+      "managedResourceGroupId": "[subscriptionResourceId('Microsoft.Resources/resourceGroups', 'example-rg')]",
+      "computeType": "[parameters('computeType')]",
+      "disableLocalAuth": true,
+      "properties": {
+        "vmSize": "[parameters('vmSize')]",
+      }
+    }
+}
+
+```
+
+### Configure with Bicep
+
+To deploy an ML - compute that complies with this rule:
+
+- Set the `disableLocalAuth` property value to `true`.
+
+For example:
+
+```bicep
+
+resource aml_compute_instance 'Microsoft.MachineLearningServices/workspaces/computes@2023-04-01' ={
+  name: '${mlWorkspace.name}/${name}'
+  location: location
+
+  properties:{
+    managedResourceGroupId: managedRg.id
+    computeType: ComputeType
+    disableLocalAuth: true
+    properties: {
+      vmSize: vmSize 
+    }
+  }
+}
+```
+
+## LINKS
+
+- [Disable local authentication](https://learn.microsoft.com/azure/machine-learning/how-to-integrate-azure-policy?view=azureml-api-2#disable-local-authentication)
+- [ML - Compute objects](https://learn.microsoft.com/azure/templates/microsoft.machinelearningservices/workspaces/computes?pivots=deployment-language-bicep#resource-format)
+- [ML - Workspaces](https://learn.microsoft.com/azure/templates/microsoft.machinelearningservices/2023-04-01/workspaces?pivots=deployment-language-bicep)
+- [ML Compute](https://learn.microsoft.com/azure/machine-learning/azure-machine-learning-glossary?view=azureml-api-2#compute)
+- [Azure Policy Regulatory Compliance controls for Azure Machine Learning](https://learn.microsoft.com/azure/machine-learning/security-controls-policy?view=azureml-api-2)
+- [WAF - Authentication with Azure AD](https://learn.microsoft.com/azure/well-architected/security/design-identity-authentication)

docs/en/rules/Azure.ML.WrkspPublicAccess.md

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+---
+reviewed: 2023-10-12
+severity: Critical
+pillar: Security
+category: Networking
+resource: ML
+online version: https://azure.github.io/PSRule.Rules.Azure/en/rules/Azure.ML.WrkspPublicAccess/
+---
+
+# ML Workspace has public access disabled
+
+## SYNOPSIS
+
+Disable public network access from a ML - Workspace. 
+
+## DESCRIPTION
+
+Disabling public network access improves security by ensuring that the Machine Learning Workspaces aren't exposed on the public internet. You can control exposure of your workspaces by creating private endpoints instead. 
+
+## RECOMMENDATION
+
+Consider setting the 'publicNetworkAccess' parameter of the Workspace properties to "Disabled", as part of a broader security strategy. 
+
+## EXAMPLES
+
+### Configure with Azure template
+
+To deploy an ML - Workspace that complies with this rule:
+
+- update the 'publicNetworkAccess' parameter of the Workspace properties to "Disabled".
+
+For example:
+
+```json
+{
+    "type": "Microsoft.MachineLearningServices/workspaces",
+    "apiVersion": "2023-04-01",
+    "name": "[parameters('name')]",
+    "location": "[parameters('location')]",
+    "sku": {
+      "name": "basic",
+      "tier": "basic"
+    },
+    "identity": {
+      "type": "SystemAssigned"
+    },
+    "properties": {
+      "friendlyName": "[parameters('name')]",
+      "keyVault": "[resourceId('Microsoft.KeyVault/vaults', parameters('KeyVaultName'))]",
+      "storageAccount": "[resourceId('Microsoft.Storage/storageAccounts', parameters('StorageAccountName'))]",
+      "applicationInsights": "[resourceId('Microsoft.Insights/components', parameters('AppInsightsName'))]",
+      "containerRegistry": "[resourceId('Microsoft.ContainerRegistry/registries', parameters('ContainerRegistryName'))]",
+      "publicNetworkAccess": "Disabled"
+    }
+
+```
+
+### Configure with Bicep
+
+To deploy an ML - Workspace that complies with this rule:
+
+- update the 'publicNetworkAccess' parameter of the Workspace properties to 'Disabled'.
+
+For example:
+
+```bicep
+resource Ml_Workspace 'Microsoft.MachineLearningServices/workspaces@2023-04-01' = {
+  name: name
+  location: location
+  sku: {
+    name: 'basic'
+    tier: 'basic'
+  }
+  identity: {
+    type: 'SystemAssigned'
+  }
+  properties: {
+    friendlyName: friendlyName
+    keyVault: KeyVault.id
+    storageAccount: StorageAccount.id
+    applicationInsights: AppInsights.id
+    containerRegistry: ContainerRegistry.id
+    publicNetworkAccess: 'Disabled'
+  }
+}
+
+```
+
+## LINKS
+
+- [Configure a private endpoint for an Azure Machine Learning workspace](https://learn.microsoft.com/azure/machine-learning/how-to-configure-private-link?view=azureml-api-2&tabs=cli)
+- [ML - Public access to Workspaces](https://learn.microsoft.com/azure/machine-learning/how-to-secure-workspace-vnet?view=azureml-api-2&tabs=required%2Cpe%2Ccli#public-access-to-workspace)
+- [ML - Workspaces](https://learn.microsoft.com/azure/templates/microsoft.machinelearningservices/workspaces?pivots=deployment-language-bicep#workspaceproperties)
+- [Security and governance for ML](https://learn.microsoft.com/azure/machine-learning/concept-enterprise-security?view=azureml-api-2)
+- [WAF - Azure services for securing network connectivity](https://learn.microsoft.com/azure/well-architected/security/design-network-connectivity)