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
).
- Navigate to the scenario folder you want to deploy
- Copy
terraform.tfvars.example
toterraform.tfvars
- Update
terraform.tfvars
with your desired values - Run Terraform
$ cd <scenario you want to deply> $ terraform init $ terraform plan $ terraform apply
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