This deployment configuration specifies an Azure Machine Learning workspace, and its associated resources including Azure Key Vault, Azure Storage, Azure Application Insights and Azure Container Registry.

In addition to these core services, this configuration specifies any networking components that are required to set up Azure Machine Learning for private network connectivity using Azure Private Link.

This configuration describes the minimal set of resources you require to get started with Azure Machine Learning in a network-isolated set-up.

To learn more about security configurations in Azure Machine Learning, see Enterprise security and governance for Azure Machine Learning.

Resources

Terraform Resource Type	Description
`azurerm_resource_group`	The resource group all resources get deployed into
`azurerm_application_insights`	An Azure Application Insights instance associated to the Azure Machine Learning workspace
`azurerm_key_vault`	An Azure Key Vault instance associated to the Azure Machine Learning workspace
`azurerm_storage_account`	An Azure Storage instance associated to the Azure Machine Learning workspace
`azurerm_container_registry`	An Azure Container Registry instance associated to the Azure Machine Learning workspace
`azurerm_machine_learning_workspace`	An Azure Machine Learning workspace instance
`azurerm_virtual_network`	An Azure Machine Learning workspace instance
`azurerm_subnet`	An Azure Machine Learning workspace instance
`azurerm_private_dns_zone`	Private DNS Zones for FQDNs required for Azure Machine Learning and associated resources
`azurerm_private_dns_zone_virtual_network_link`	Virtual network links of the Private DNS Zones to the virtual network resource
`azurerm_private_endpoint`	Private Endpoints for the Azure Machine Learning workspace and associated resources

Variables

Name	Description
name	Name of the deployment
environment	The deployment environment name (used for pre- and postfixing resource names)
location	The Azure region used for deployments

Usage

terraform plan -var name=azureml567 -out demo.tfplan

terraform apply "demo.tfplan"