This repo shows several examples for rolling out complete Azure Machine Learning enterprise enviroments via Terraform.

Depending on the scneario you want to roll out, this includes the following resources:

• Azure Machine Learning Workspace (optionally with Private Link)
• Azure Storage Account (optionally with VNET binding (using Service Endpoints) and Private Link for Blob and File)
• Azure Key Vault (optionally with VNET binding (using Service Endpoints) and Private Link)
• Azure Container Registry (optionally with VNET binding and Private Link)
• Azure Application Insights
• Virtual Network (optional)
• Jumphost (Windows) with Bastion for easy access to the VNET (optional)
• Compute Cluster (in VNET)
• Compute Instance (in VNET)
• Azure Kubernetes Service (optional)

Make sure you have the Azure CLI and the Azure Machine Learning CLI extension installed (az extension add -n azure-cli-ml).

1. Navigate to the scenario folder you want to deploy
2. Copy terraform.tfvars.example to terraform.tfvars
3. Update terraform.tfvars with your desired values
4. Run Terraform

   $ cd <scenario you want to deply>
   $ terraform init
   $ terraform plan
   $ terraform apply

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