Merge pull request #296440 from craigshoemaker/aca/jason/gpu-tutorial

[Container Apps] Update: Serverless GPU tutorial (CLI)

Author: AnnaMHuff

articles/container-apps/gpu-image-generation.md

@@ -7,15 +7,16 @@ ms.service: azure-container-apps
 ms.custom:
   - ignite-2024
 ms.topic: how-to
-ms.date: 11/06/2024
+ms.date: 03/17/2025
 ms.author: cshoe
+zone_pivot_groups: container-apps-portal-or-cli
 ---
 
 # Tutorial: Generate images using serverless GPUs in Azure Container Apps
 
 In this article, you learn how to create a container app that uses [serverless GPUs](gpu-serverless-overview.md) to power an AI application.
 
-With serverless GPUs, you have direct access to GPU compute resources without having to do manual infrastructure configuration such as installing drivers. All you have to do is deploy your AI model's image. 
+With serverless GPUs, you have direct access to GPU compute resources without having to do manual infrastructure configuration such as installing drivers. All you have to do is deploy your AI model's image.
 
 In this tutorial you:
 
@@ -28,12 +29,27 @@ In this tutorial you:
 
 ## Prerequisites
 
+::: zone pivot="azure-portal"
+
 | Resource | Description |
 |---|---|
 | Azure account | You need an Azure account with an active subscription. If you don't have one, you [can create one for free](https://azure.microsoft.com/free/). |
-| Azure Container Registry instance | You need an existing Azure Container Registry instance or the permissions to create one. |
 | Access to serverless GPUs | Access to GPUs is only available after you request GPU quotas. You can submit your GPU quota request via a [customer support case](/azure/azure-portal/supportability/how-to-create-azure-support-request). |
 
+::: zone-end
+
+::: zone pivot="azure-cli"
+
+| Resource | Description |
+|---|---|
+| Azure account | You need an Azure account with an active subscription. If you don't have one, you [can create one for free](https://azure.microsoft.com/free/). |
+| Access to serverless GPUs | Access to GPUs is only available after you request GPU quotas. You can submit your GPU quota request via a [customer support case](/azure/azure-portal/supportability/how-to-create-azure-support-request). |
+| [Azure CLI](/cli/azure/install-azure-cli) | Install the [Azure CLI](/cli/azure/install-azure-cli) or upgrade to the latest version. |
+
+::: zone-end
+
+::: zone pivot="azure-portal"
+
 ## Create your container app
 
 1. Go to the Azure portal and search for and select **Container Apps**.
@@ -53,7 +69,7 @@ In this tutorial you:
 
     | Setting | Value |
     |---|---|
-    | Region | Select **West US 3**. <br><br>For more supported regions, refer to [Using serverless GPUs in Azure](gpu-serverless-overview.md#supported-regions). |
+    | Region | Select **Sweden Central**. <br><br>For more supported regions, refer to [Using serverless GPUs in Azure](gpu-serverless-overview.md#supported-regions). |
     | Container Apps environment | Select **Create new**. |
 
     In the *Create Container Apps environment* window, enter the following values:
@@ -75,9 +91,9 @@ In this tutorial you:
     | Image type | Select **public**. |
     | Registry login server | Enter **mcr.microsoft.com**. |
     | Image and tag | Enter **k8se/gpu-quickstart:latest**. |
-    | Workload profile | Select the option that begins with **Consumption - Up to 4**... |
+    | Workload profile | Select **Consumption - Up to 4 vCPUs, 8 Gib memory**. |
     | GPU | Select the checkbox. |
-    | GPU Type | Select the **T4** option and select the link to add the profile to your environment. |
+    | GPU Type | Select **Consumption-GPU-NC8as-T4 - Up to 8 vCPUs, 56 GiB memory** and select the link to add the profile to your environment. |
 
     Select **Next: Ingress >**.
 
@@ -105,9 +121,88 @@ From the *Overview* window, select the **Application Url** link to open the web
 > - To achieve the best performance of your GPU apps, follow the steps to [improve cold start for your serverless GPUs](gpu-serverless-overview.md#improve-gpu-cold-start).
 > - When there are multiple containers in your application, the first container gets access to the GPU.
 
+::: zone-end
+
+::: zone pivot="azure-cli"
+
+## Create environment variables
+
+Define the following environment variables. Before running this command, replace the `<PLACEHOLDERS>` with your values.
+
+```azurecli
+RESOURCE_GROUP="<RESOURCE_GROUP>"
+ENVIRONMENT_NAME="<ENVIRONMENT_NAME>"
+LOCATION="swedencentral"
+CONTAINER_APP_NAME="<CONTAINER_APP_NAME>"
+CONTAINER_IMAGE="mcr.microsoft.com/k8se/gpu-quickstart:latest"
+WORKLOAD_PROFILE_NAME="NC8as-T4"
+WORKLOAD_PROFILE_TYPE="Consumption-GPU-NC8as-T4"
+```
+
+## Create your container app
+
+1. Create the resource group to contain the resources you create in this tutorial. This command should output `Succeeded`.
+
+    ```azurecli
+    az group create \
+      --name $RESOURCE_GROUP \
+      --location $LOCATION \
+      --query "properties.provisioningState"
+    ```
+
+1. Create a Container Apps environment to host your container app. This command should output `Succeeded`.
+
+    ```azurecli
+    az containerapp env create \
+      --name $ENVIRONMENT_NAME \
+      --resource-group $RESOURCE_GROUP \
+      --location "$LOCATION" \
+      --query "properties.provisioningState"
+    ```
+
+1. Add a workload profile to your environment.
+
+    ```azurecli
+    az containerapp env workload-profile add \
+      --name $ENVIRONMENT_NAME \
+      --resource-group $RESOURCE_GROUP \
+      --workload-profile-name $WORKLOAD_PROFILE_NAME \
+      --workload-profile-type $WORKLOAD_PROFILE_TYPE
+    ```
+
+1. Create your container app.
+
+    ```azurecli
+    az containerapp create \
+      --name $CONTAINER_APP_NAME \
+      --resource-group $RESOURCE_GROUP \
+      --environment $ENVIRONMENT_NAME \
+      --image $CONTAINER_IMAGE \
+      --target-port 80 \
+      --ingress external \
+      --cpu 8.0 \
+      --memory 56.0Gi \
+      --workload-profile-name $WORKLOAD_PROFILE_NAME \
+      --query properties.configuration.ingress.fqdn
+    ```
+
+    This command outputs the application URL for your container app.
+
+## Use your GPU app
+
+Open the application URL for your container app in your browser. Note it can take up to five minutes for the container app to start up.
+
+The Azure Container Apps with Serverless GPUs application lets you enter a prompt to generate an image. You can also simply select `Generate Image` to use the default prompt. In the next step, you view the results of the GPU processing.
+
+> [!NOTE]
+> - To achieve the best performance of your GPU apps, follow the steps to [improve cold start for your serverless GPUs](gpu-serverless-overview.md#improve-gpu-cold-start).
+> - When there are multiple containers in your application, the first container gets access to the GPU.
+
+::: zone-end
+
 ## Monitor your GPU
 
-Once you generate an image, use the following steps to view results of the GPU processing:
+Once you generate an image, use the following steps to view the results of the GPU processing:
 
 1. Open your container app in the Azure portal.
 
@@ -117,7 +212,7 @@ Once you generate an image, use the following steps to view results of the GPU p
 
 1. Select your container.
 
-1. Select **Reconnect*.
+1. Select **Reconnect**.
 
 1. In the *Choose start up command* window, select **/bin/bash**, and select **Connect**.
 
@@ -129,6 +224,8 @@ The resources created in this tutorial have an effect on your Azure bill.
 
 If you aren't going to use these services long-term, use the steps to remove everything created in this tutorial.
 
+::: zone pivot="azure-portal"
+
 1. In the Azure portal, search for and select **Resource Groups**.
 
 1. Select **my-gpu-demo-group**.
@@ -139,6 +236,18 @@ If you aren't going to use these services long-term, use the steps to remove eve
 
 1. Select **Delete**.
 
+::: zone-end
+
+::: zone pivot="azure-cli"
+
+Run the following command.
+
+```azurecli
+az group delete --name $RESOURCE_GROUP
+```
+
+::: zone-end
+
 ## Next steps
 
 > [!div class="nextstepaction"]