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Copy file name to clipboardExpand all lines: README.md
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1. Have access to an Azure subscription and Entra ID account with Contributor permissions.
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2. Confirm the subscription you are deploying into has the [Required Roles and Scopes](docs/Required_roles_scopes_resources.md).
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3. The solution ensures secure access to the private VNET through a jump-box VM with Azure Bastion. By default, Bastion does not require an inbound NSG rule for network traffic. However, if your environment enforces specific policy rules, you can resolve access issues by entering your machine's IP address in the `allowedIpAddress` parameter when prompted during deployment. If not specified, all IP addresses are allowed to connect to Azure Bastion.
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4. If deploying from your [local environment](docs/local_environment_steps.md), install the [Azure Developer CLI (AZD)](https://learn.microsoft.com/en-us/azure/developer/azure-developer-cli/install-azd?tabs=winget-windows%2Cbrew-mac%2Cscript-linux&pivots=os-windows).
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4. If deploying from your [local environment](docs/local_environment_steps.md), install the [Azure CLI (AZ)](https://learn.microsoft.com/en-us/cli/azure/install-azure-cli?view=azure-cli-latest) and the [Azure Developer CLI (AZD)](https://learn.microsoft.com/en-us/azure/developer/azure-developer-cli/install-azd?tabs=winget-windows%2Cbrew-mac%2Cscript-linux&pivots=os-windows).
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5. If deploying via [GitHub Codespaces](docs/github_code_spaces_steps.md) - requires the user to be on a GitHub Team or Enterprise Cloud plan.
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6. If leveraging [GitHub Actions](docs/github_actions_steps.md).
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### Check Azure OpenAI Quota Availability
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To ensure sufficient quota is available in your subscription, please follow **[quota check instructions guide](./docs/quota_check.md)** before deploying the solution.
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### Services Enabled
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For additional documentation of the default enabled services of this solution accelerator, please see:
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1.[Azure Open AI Service](https://learn.microsoft.com/en-us/azure/ai-services/openai/)
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### Region Availability
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By default, this template uses AI models which may not be available in all Azure regions. Check for [up-to-date region availability](https://learn.microsoft.com/azure/ai-services/openai/concepts/models#standard-deployment-model-availability) and select a region during deployment accordingly.
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By default, this template uses AI models which may not be available in all Azure regions. Please follow [quota check instructions guide](./docs/quota_check.md) before deploying the solution. Additionally, check for [up-to-date region availability](https://learn.microsoft.com/azure/ai-services/openai/concepts/models#standard-deployment-model-availability) and select a region during deployment accordingly.
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### Costs
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This template has [Managed Identity](https://learn.microsoft.com/entra/identity/managed-identities-azure-resources/overview) built in to eliminate the need for developers to manage these credentials. Applications can use managed identities to obtain Microsoft Entra tokens without having to manage any credentials.
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## Resources
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-[Azure AI Foundry documentation](https://learn.microsoft.com/en-us/azure/ai-foundry/)
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-[Azure Well Architecture Framework documentation](https://learn.microsoft.com/en-us/azure/well-architected/)
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-[Azure OpenAI Service - Documentation, quickstarts, API reference - Azure AI services | Microsoft Learn](https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/use-your-data)
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-[Azure AI Content Understanding documentation](https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/)
Copy file name to clipboardExpand all lines: docs/github_code_spaces_steps.md
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**Prompting for MFA**
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7. Return to the codespaces window and type “az login”. The [Azure CLI](https://learn.microsoft.com/en-us/cli/azure/what-is-azure-cli?view=azure-cli-latest) is used to validate available AI model quota.
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7. Return to the codespaces window now. In the terminal window, begin by initializing the environment by typing the command “azd init”
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8. Return to the codespaces window now. In the terminal window, begin by initializing the environment by typing the command “azd init”
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8. Enter the name for your environment
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9. Enter the name for your environment
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9. Now start the deployment of the infrastructure by typing the command “azd provision”
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10. Now start the deployment of the infrastructure by typing the command “azd up”
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This step will allow you to choose from the subscriptions you have available, based on the account you logged in with in the login step. Next it will prompt you for the region to deploy the resources into as well as any additional Azure resources to be provisioned and configured.
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**Be sure to remember the vm password. This will be used in a later step. You are still required to log into Azure once you connect through the virtual machine.
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11. The automated model quota check will run, and will check if the location selected will have the necessary quota for the AI Models that are listed in the parameters file prior to deploying any resources.
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If the location selected has sufficient quota for the models you plan to deploy, the provisioning will begin without notification.
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This step will allow you to choose from the subscriptions you have available, based on the account you logged in with in the azd auth login step. Next it will prompt you for the region to deploy the resources into.
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If the location selected does not have the available quota for the models selected in your parameters, there will be a message back to the user, prior to any provisioning of resources. This will allow the developer to change the location of the provisiong and try again. Note that in our example, Italy North had capacity for gpt-4o but not for text-embedding-ada-002. This terminated the entire provisioning, because both models could not be deployed due to a quota issue.
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10. Next you will be prompted for values to enable additional features outside of the AI Foundry required features. They are false by default.
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**Be sure to remember the vm password and vm username. This will be used in a later step. Because we are using FDPO subscriptions, we do not have access to Entra to create the SSO to the jump box at this time. You are still required to log into Azure once you connect to the virtual machine.
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12. After completeing the required paramters that you were prompted for, and a successful model quota validation, the provisioning of resources will run and deploy the Network Isolated AI Foundry development portal and dependent resources in about 20 minutes.
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11. After completeing the required paramters that you were prompted for, the provisioning of resources will run and deploy the Network Isolated AI hub, project and dependent resources in about 20 minutes.
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# Post Deployment Steps:
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These steps will help to check that the isolated environment was set up correctly.
This solution uses the [Azure Developer CLI](https://learn.microsoft.com/en-us/azure/developer/azure-developer-cli/overview) to quickly provision and deploy infrastructure and applications to Azure.
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This solution uses the [Azure CLI](https://learn.microsoft.com/en-us/cli/azure/what-is-azure-cli?view=azure-cli-latest) and the [Azure Developer CLI](https://learn.microsoft.com/en-us/azure/developer/azure-developer-cli/overview) to quickly provision and deploy infrastructure and applications to Azure.
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To get started, authenticate with an Azure Subscription ([details](https://learn.microsoft.com/en-us/azure/developer/azure-developer-cli/reference#azd-auth-login)):
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```powershell
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azd auth login
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```
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Also authenticate with the Azure CLI ([details](https://learn.microsoft.com/en-us/cli/azure/authenticate-azure-cli?view=azure-cli-latest)):
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```powershell
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az login
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```
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Establish a new environment. Provide a name that represents the application domain:
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One way to check if the access is private to the hub is to launch the AI Foundry hub from the portal.
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When a user that is not connected through the virtual network via an RDP approved connection will see the following screen in their browser. This is the intended behavior!
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A more thorough check is to look for the networking settings and checking for private endpoints.
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1. Go to the Azure Portal and select your Azure AI hub that was just created.
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2. Click on Settings and then Networking.
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3. Open the Workspace managed outbound access tab.
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Here, you will find the private endpoints that are connected to the resources within the hub managed virtual network. Ensure that these private endpoints are active.
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The hub should show that Public access is ‘disabled’.
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## Connecting to the isolated network via RDP
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1. Navigate to the resource group where the isolated AI Foundry was deployed to and select the virtual machine.
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2. Be sure that the Virtual Machine is running. If not, start the VM.
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3. Select “Bastion” under the ‘Connect’ heading in the VM resource.
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4. Supply the username and the password you created as environment variables and press the connect button.
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5. Your virtual machine will launch and you will see a different screen.
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6. Launch Edge browser and navigate to your AI Foundry Hub. https://ai.azure.com Sign in using your credentials.
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7. You are challenged by MFA to connect.
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8. You will now be able to view the Foundry Hub which is contained in an isolated network.
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