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Copy file name to clipboardExpand all lines: docs/Dev_ContainerSteps.md
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@@ -30,19 +30,35 @@ You can run this solution in VS Code Dev Containers, which will open the project
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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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3. Return to terminal and type the below commandfor initializing the environment.
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```shell
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azd init
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```
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4. Enter the environment name.
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>**Note:** Length of the environment name should be less than or equal to 12 characters.
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3. Now start the deployment of the infrastructure by typing the below command:
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5. Now start the deployment of the infrastructure by typing the below command:
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```shell
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azd up
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```
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> ⚠️ **Note:** The latest version of the Azure Developer CLI (AZD) is currently limited on prompting formissing parameters. The feature flag parametersin this solution have been temporarily defaulted to `'disabled'`until this limitation is lifted and prompting will resume.
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Log in to **Azure**for authentication. 
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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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**Important:** 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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> ⚠️ **Note:**
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> 1. For **WAF Deployment**, Select the **Network Isolation** as **'True'**.
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>
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> 2. For **Sample App Deployment**, Select the **appSampleEnabled** as **'True'**.
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>
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6. The automated model quota check will run, and will check if the location selected will have the necessary quota forthe AI Models that are listedin the parameters file prior to deploying any resources.
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These steps will help to check that the isolated environment was set up correctly.
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Follow these steps to check the creation of the required private endpoints in the environment (when set to networkIsolation = true).
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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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One way to verify whether access is private to the foundry is by launching Azure AI Foundry 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 thourough check is to look for the networking settings and checking for private end points.
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1. Go to the Azure Portal and selectyour Azure AI hub that was just created.
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2. Click on Settings and then Networking.
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2. Click on Resource Management 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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Here, you will find the private endpoints that are connected to the resources within the foundry managed virtual network. Ensure that these private endpoints are active.
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The foundry 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 selectthe virtual machine.
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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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6. Launch Edge browser and navigate to your Azure AI Foundry. 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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8. You will now be able to view the Azure AI Foundry which is contained in an isolated network.
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Copy file name to clipboardExpand all lines: docs/github_code_spaces_steps.md
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@@ -38,6 +38,7 @@ You can run this solution using GitHub Codespaces. The button will open a web-ba
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4. Enter the environment name.
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>**Note:** Length of the environment name should be less than or equal to 12 characters.
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```
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> ⚠️ **Note:** The latest version of the Azure Developer CLI (AZD) is currently limited on prompting formissing parameters. The feature flag parametersin this solution have been temporarily defaulted to `'disabled'`until this limitation is lifted and prompting will resume.
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Log in to **Azure**for authentication. 
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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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**Important:** 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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+
> ⚠️ **Note:**
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> 1. For **WAF Deployment**, Select the **Network Isolation** as **'True'**.
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>
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> 2. For **Sample App Deployment**, Select the **appSampleEnabled** as **'True'**.
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>
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6. The automated model quota check will run, and will check if the location selected will have the necessary quota forthe AI Models that are listedin the parameters file prior to deploying any resources.
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@@ -72,28 +78,25 @@ You can run this solution using GitHub Codespaces. The button will open a web-ba
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These steps will help to check that the isolated environment was set up correctly.
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Follow these steps to check the creation of the required private endpoints in the environment (when set to networkIsolation = true).
74
80
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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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+
One way to verify whether access is private to the foundry is by launching Azure AI Foundry from the portal.
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+
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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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+
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A more thourough check is to look for the networking settings and checking for private end points.
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1. Go to the Azure Portal and selectyour Azure AI hub that was just created.
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2. Click on Settings and then Networking.
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-
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-
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+
2. Click on Resource Management and then Networking.
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-
3. Open the Workspace managed outbound access tab.
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+
92
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93
-
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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.
96
-
The hub should show that Public access is ‘disabled’.
98
+
Here, you will find the private endpoints that are connected to the resources within the foundry managed virtual network. Ensure that these private endpoints are active.
99
+
The foundry should show that Public access is ‘disabled’.
97
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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 selectthe virtual machine.
@@ -110,22 +113,22 @@ A more thourough check is to look for the networking settings and checking for p
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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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6. Launch Edge browser and navigate to your Azure AI Foundry. 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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8. You will now be able to view the Azure AI Foundry which is contained in an isolated network.
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-
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