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