Azure AI Studio
This deployment configuration specifies an Azure AI hub, and its associated resources including Azure Key Vault, Azure Storage. You can optionally provision and attach Azure Application Insights and Azure Container Registry.
This configuration describes the minimal set of resources you require to get started with Azure AI Studio.
Resources
Terraform Resource Type | Description |
---|---|
azurerm_resource_group |
The resource group all resources get deployed into. |
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_application_insights |
An Azure Application Insights instance associated to the Azure Machine Learning workspace. |
azurerm_container_registry |
An Azure Container Registry instance associated to the Azure Machine Learning workspace. |
Variables
Name | Description | Default |
---|---|---|
names | Prefix name for dependent resources. | myfirst |
location | The Azure region used for deployments | East US |
sku | The SKU for AI Services resources | S0 |
Usage
After git cloning the repo, run the following commands after having docker running on your machine.
terraform init
az login
terraform plan -var names="tftemplate" -out demo.tfplan
terraform apply "demo.tfplan"
Common mistakes
- Make sure docker is running
- Make sure to have logged into your Azure Subscription by running
az login
. - Ensure that you have the correct RBAC permissions for in your subscription, hub, and project.