links

Author: Larry Franks

articles/machine-learning/service/how-to-deploy-and-where.md

@@ -343,6 +343,8 @@ For more information on creating an AKS cluster outside of the Azure Machine Lea
 * [Create an AKS cluster](https://docs.microsoft.com/cli/azure/aks?toc=%2Fazure%2Faks%2FTOC.json&bc=%2Fazure%2Fbread%2Ftoc.json&view=azure-cli-latest#az-aks-create)
 * [Create an AKS cluster (portal)](https://docs.microsoft.com/azure/aks/kubernetes-walkthrough-portal?view=azure-cli-latest)
 
+For more information on the `cluster_purpose` parameter ,see the [AksCompute.ClusterPurpose](https://docs.microsoft.com/python/api/azureml-core/azureml.core.compute.aks.akscompute.clusterpurpose?view=azure-ml-py) reference.
+
 > [!IMPORTANT]
 > For [`provisioning_configuration()`](https://docs.microsoft.com/python/api/azureml-core/azureml.core.compute.akscompute?view=azure-ml-py), if you pick custom values for agent_count and vm_size, then you need to make sure agent_count multiplied by vm_size is greater than or equal to 12 virtual CPUs. For example, if you use a vm_size of "Standard_D3_v2", which has 4 virtual CPUs, then you should pick an agent_count of 3 or greater.
 
@@ -376,6 +378,10 @@ attach_config = AksCompute.attach_configuration(resource_group = resource_group,
 aks_target = ComputeTarget.attach(ws, 'mycompute', attach_config)
 ```
 
+For more information on `attack_configuration()`, see the [AksCompute.attach_configuration()](https://docs.microsoft.com/python/api/azureml-core/azureml.core.compute.akscompute?view=azure-ml-py#attach-configuration-resource-group-none--cluster-name-none--resource-id-none--cluster-purpose-none-) reference.
+
+For more information on the `cluster_purpose` parameter, see the [AksCompute.ClusterPurpose](https://docs.microsoft.com/python/api/azureml-core/azureml.core.compute.aks.akscompute.clusterpurpose?view=azure-ml-py) reference.
+
 ## Consume web services
 
 Every deployed web service provides a REST API, so you can create client applications in a variety of programming languages.