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Copy file name to clipboardExpand all lines: articles/container-apps/aspire-dashboard.md
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ms.service: azure-container-apps
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ms.custom: devx-track-azurecli, devx-track-dotnet
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ms.topic: how-to
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ms.date: 1/14/2025
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ms.date: 05/02/2025
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ms.author: cshoe
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zone_pivot_groups: azure-azd-cli-portal
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---
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# Read real time app data with Aspire Dashboard in Azure Container Apps (preview)
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# Read real time app data with Aspire Dashboard in Azure Container Apps
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The [Aspire Dashboard](/dotnet/aspire/fundamentals/dashboard/overview) displays live data about how applications and other resources are running within an environment.
# Tutorial: Enable Azure Container Apps on Azure Arc-enabled Kubernetes
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With [Azure Arc-enabled Kubernetes clusters](/azure/azure-arc/kubernetes/overview), you can create a [Container Apps enabled custom location](azure-arc-create-container-app.md) in your on-premises or cloud Kubernetes cluster to deploy your Azure Container Apps applications as you would any other region.
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> * Create a custom location.
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> * Create the Azure Container Apps connected environment.
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> [!NOTE]
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> During the preview, Azure Container Apps on Arc are not supported in production configurations. This article provides an example configuration for evaluation purposes only.
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>
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> This tutorial uses [Azure Kubernetes Service (AKS)](/azure/aks/) to provide concrete instructions for setting up an environment from scratch. However, for a production workload, you may not want to enable Azure Arc on an AKS cluster as it is already managed in Azure.
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## Prerequisites
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- An Azure account with an active subscription.
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- If you don't have one, you [can create one for free](https://azure.microsoft.com/free/).
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- Install the [Azure CLI](/cli/azure/install-azure-cli).
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- Access to a public or private container registry, such as the [Azure Container Registry](/azure/container-registry/).
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- Review the [requirements and limitations](azure-arc-overview.md) of the public preview. Of particular importance are the cluster requirements.
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author: craigshoemaker
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ms.service: azure-container-apps
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ms.topic: conceptual
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ms.date: 03/06/2025
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ms.date: 05/12/2025
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# Azure Container Apps on Azure Arc (Preview)
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# Azure Container Apps on Azure Arc
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You can run Container Apps on an Azure Arc-enabled AKS or AKS on Azure Local cluster.
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-**A Container Apps connected environment**, which enables configuration common across apps but not related to cluster operations. Conceptually, it's deployed into the custom location resource, and app developers create apps into this environment.
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## Public preview limitations
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## Limitations
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The following public preview limitations apply to Azure Container Apps on Azure Arc enabled Kubernetes.
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The following limitations apply to Azure Container Apps on Azure Arc enabled Kubernetes.
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| Limitation | Details |
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|---|---|
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| Supported Azure regions | East US, West Europe, East Asia|
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| Supported Azure regions |Central US, East Asia, East US, North Central US, Southeast Asia, Sweden Central, UK South, West Europe, West US|
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| Cluster networking requirement | Must support [LoadBalancer](https://kubernetes.io/docs/concepts/services-networking/service/#loadbalancer) service type |
| Feature: Pull images from ACR with managed identity | Not available (depends on managed identities) |
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| Logs | Log Analytics must be configured with cluster extension; not per-application |
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The following features are supported:
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- Labels
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- Metrics
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- Easy auth
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- Log stream
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- Resilience
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- Custom domains
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- Container Apps jobs
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- Revision Management
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- App container console
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> [!IMPORTANT]
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> If deploying onto **AKS on Azure Local** ensure that you have [setup HAProxy as your load balancer](/azure/aks/hybrid/configure-load-balancer) before attempting to install the extension.
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| Pod | Description | Number of Instances | CPU | Memory | Type |
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|----|----|----|----|----|----|
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|`<extensionName>-k8se-activator`| Used as part of the scaling pipeline | 2 | 100 millicpu | 500 MB | ReplicaSet |
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|`<extensionName>-k8se-billing`| Billing record generation - Azure Container Apps on Azure Arc enabled Kubernetes is Free of Charge during preview | 3 | 100 millicpu | 100 MB | ReplicaSet |
|`<extensionName>-k8se-containerapp-controller`| The core operator pod that creates resources on the cluster and maintains the state of components. | 2 | 100 millicpu | 1 GB | ReplicaSet |
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|`<extensionName>-k8se-envoy`| A front-end proxy layer for all data-plane http requests. It routes the inbound traffic to the correct apps. | 3 | 1 Core | 1,536 MB | ReplicaSet |
-[Are there any scaling limits?](#are-there-any-scaling-limits)
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-[Can the extension be installed on Windows nodes?](#can-the-extension-be-installed-on-windows-nodes)
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-[Can I deploy the Container Apps extension on an Arm64 based cluster?](#can-i-deploy-the-container-apps-extension-on-an-arm64-based-cluster)
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### How much does it cost?
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Azure Container Apps on Azure Arc-enabled Kubernetes is free during the public preview.
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### Which Container Apps features are supported?
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During the preview period, certain Azure Container App features are being validated. When they're supported, their left navigation options in the Azure portal will be activated. Features that aren't yet supported remain grayed out.
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Check the portal for the most up to date list. Features not supported are grayed out in the portal.
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-[Storage mounts](cold-start.md#manage-large-downloads): Reduce the effects of network latency by storing large files in an Azure storage account associated with your container app.
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<aname="deploy-foundry-models"></a>
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## Deploy Foundry models to serverless GPUs (preview)
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Azure Container Apps serverless GPUs now support Azure AI Foundry models in public preview. Azure AI Foundry Models have two deployment options:
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-[**Serverless APIs**](/azure/ai-foundry/how-to/deploy-models-serverless?tabs=azure-ai-studio) which provide pay-as-you-go billing for some of the most popular models.
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-[**Managed compute**](/azure/ai-foundry/how-to/create-manage-compute) that allow you to deploy the full selection of Foundry models with pay-per-GPU pricing.
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Azure Container Apps serverless GPU offers a balanced deployment option between serverless APIs and managed compute for you to deploy Foundry models. This option is on-demand with serverless scaling that scales in to zero when not in use and complies with your data residency needs. With serverless GPUs, using Foundry models give you flexibility to run any supported model with automatic scaling, pay-per-second-pricing, full data governance, out of the box enterprise networking and security support.
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Language models of the type `MLFLOW` are supported. To see a list of `MLFLOW` models, go to the list of models available in the [azureml registry](https://aka.ms/azureml-registry). To locate the models, add a filter for `MLFLOW` models using the following steps:
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1. Select **Filter**.
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1. Select **Add Filter**.
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1. For the filter rule, enter **Type = MLFLOW**.
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The following CLI command shows how to deploy a Foundry model to serverless GPUs:
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```azurecli
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az containerapp up \
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--name <CONTAINER_APP_NAME> \
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--environment <ENVIORNMENT_NAME> \
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--resource-group <RESOURCE_GROUP_NAME> \
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--model-registry <MODEL_REGISTRY_NAME> \
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--model-name <MODEL_NAME> \
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--model-version <MODEL_VERSION>
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```
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When you deploy a Foundry model to Azure Container Apps serverless GPUs as an online endpoint, a scoring script is required. The scoring script (named *score.py*) defines how you interact with the model. By default, the example CLI command provides a scoring script. However, you can also provide your own *score.py* file. The following example shows [how to use a custom score.py file](/azure/machine-learning/how-to-deploy-online-endpoints?view=azureml-api-2&tabs=cli).
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## Submit feedback
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Submit issue to the [Azure Container Apps GitHub repo](https://github.com/microsoft/azure-container-apps).
# Create a private link to an Azure Container App with Azure Front Door (preview)
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# Create a private link to an Azure Container App with Azure Front Door
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In this article, you learn how to connect directly from Azure Front Door to your Azure Container Apps using a private link instead of the public internet. In this tutorial, you create an Azure Container Apps workload profiles environment, an Azure Front Door, and connect them securely through a private link. You then verify the connectivity between your container app and the Azure Front Door.
# Use a private endpoint with an Azure Container Apps environment (preview)
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# Use a private endpoint with an Azure Container Apps environment
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In this article, you learn how to use a private endpoint to securely access your Azure Container App without exposing it to the public Internet.
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A private endpoint uses a private IP address from your virtual network (VNet). This endpoint connects you privately and securely to a service powered by [Azure Private Link](/azure/private-link/private-link-overview).
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Private endpoints on Azure Container Apps only support inbound HTTP traffic. TCP traffic isn't supported.
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