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.openpublishing.redirection.json

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},
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{
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"source_path_from_root": "/articles/aks/cluster-configuration.md",
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"redirect_url": "/azure/aks/concepts-clusters-workloads.md",
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"redirect_url": "/azure/aks/concepts-clusters-workloads",
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"redirect_document_id": false
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},
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{

articles/ai-services/openai/includes/assistants-python.md

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Install the OpenAI Python client library with:
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```console
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pip install openai
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pip install openai==v1.20.0
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```
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> [!NOTE]
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> Azure OpenAI does not yet support Assistants V2. Please use the v1.20.0 release of the OpenAI Python library until V2 support is available.
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> [!NOTE]
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> This library is maintained by OpenAI. Refer to the [release history](https://github.com/openai/openai-python/releases) to track the latest updates to the library.
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articles/ai-services/speech-service/batch-synthesis.md

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- Optionally you can set the `description`, `timeToLiveInHours`, and other properties. For more information, see [batch synthesis properties](batch-synthesis-properties.md).
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> [!NOTE]
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> The maximum JSON payload size that will be accepted is 2 megabytes. Each Speech resource can have up to 300 batch synthesis jobs that are running concurrently.
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> The maximum JSON payload size that will be accepted is 2 megabytes.
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Set the required `YourSynthesisId` in path. The `YourSynthesisId` have to be unique. It must be 3-64 long, contains only numbers, letters, hyphens, underscores and dots, starts and ends with a letter or number.
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articles/ai-services/speech-service/bring-your-own-storage-speech-resource.md

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## Create and configure BYOS-enabled Speech resource
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This section describes how to create a BYOS enabled Speech resource.
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This section describes how to create a BYOS enabled Speech resource.
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### Request access to BYOS for your Azure subscriptions
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You need to request access to BYOS functionality for each of the Azure subscriptions you plan to use. To request access, fill and submit [Cognitive Services & Applied AI Customer Managed Keys and Bring Your Own Storage access request form](https://aka.ms/cogsvc-cmk). Wait for the request to be approved.
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### (Optional) Check whether Azure subscription has access to BYOS
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You can quickly check whether your Azure subscription has access to BYOS. This check uses [preview features](/azure/azure-resource-manager/management/preview-features) functionality of Azure.
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# [Azure portal](#tab/portal)
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This functionality isn't available through Azure portal.
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> [!NOTE]
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> You may view the list of preview features for a given Azure subscription as explained in [this article](/azure/azure-resource-manager/management/preview-features), however note that not all preview features, including BYOS are visible this way.
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# [PowerShell](#tab/powershell)
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To check whether an Azure subscription has access to BYOS with PowerShell, we use [Get-AzProviderFeature](/powershell/module/az.resources/get-azproviderfeature) command.
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You can [install PowerShell locally](/powershell/azure/install-azure-powershell) or use [Azure Cloud Shell](../../cloud-shell/overview.md).
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If you use local installation of PowerShell, connect to your Azure account using `Connect-AzAccount` command before trying the following script.
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```azurepowershell
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# Target subscription parameters
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# REPLACE WITH YOUR CONFIGURATION VALUES
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$azureSubscriptionId = "XXXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXXXX"
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# Select the right subscription
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Set-AzContext -SubscriptionId $azureSubscriptionId
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# Check whether the Azure subscription has access to BYOS
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Get-AzProviderFeature -ListAvailable -ProviderNamespace "Microsoft.CognitiveServices" | where-object FeatureName -Match byox
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```
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If you get the response like this, your subscription has access to BYOS.
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```powershell
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FeatureName ProviderName RegistrationState
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----------- ------------ -----------------
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byoxPreview Microsoft.CognitiveServices Registered
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```
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If you get empty response or `RegistrationState` value is `NotRegistered` then your Azure subscription doesn't have access to BYOS and you need to [request it](#request-access-to-byos-for-your-azure-subscriptions).
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# [Azure CLI](#tab/azure-cli)
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To check whether an Azure subscription has access to BYOS with Azure CLI, we use [az feature show](/cli/azure/feature) command.
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You can [install Azure CLI locally](/cli/azure/install-azure-cli) or use [Azure Cloud Shell](../../cloud-shell/overview.md).
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> [!NOTE]
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> The following script doesn't use variables because variable usage differs, depending on the platform where Azure CLI runs. See information on Azure CLI variable usage in [this article](/cli/azure/azure-cli-variables).
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If you use local installation of Azure CLI, connect to your Azure account using `az login` command before trying the following script.
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```azurecli
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az account set --subscription "XXXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXXXX"
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az feature show --name byoxPreview --namespace Microsoft.CognitiveServices --output table
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```
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If you get the response like this, your subscription has access to BYOS.
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```dos
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Name RegistrationState
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--------------------------------------- -------------------
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Microsoft.CognitiveServices/byoxPreview Registered
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```
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If you get empty response or `RegistrationState` value is `NotRegistered` then your Azure subscription doesn't have access to BYOS and you need to [request it](#request-access-to-byos-for-your-azure-subscriptions).
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> [!Tip]
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> See additional commands related to listing Azure subscription preview features in [this article](/azure/azure-resource-manager/management/preview-features).
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# [REST](#tab/rest)
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To check through REST API whether an Azure subscription has access to BYOS use [Features - List](/rest/api/resources/features/list) request from Azure Resource Manager REST API.
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If your subscription has access to BYOS, the REST response will contain the following element:
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```json
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{
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"properties": {
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"state": "Registered"
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},
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"id": "/subscriptions/XXXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXXXX/providers/Microsoft.Features/providers/Microsoft.CognitiveServices/features/byoxPreview",
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"type": "Microsoft.Features/providers/features",
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"name": "Microsoft.CognitiveServices/byoxPreview"
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}
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```
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If the REST response doesn't contain the reference to `byoxPreview` feature or its state is `NotRegistered` then your Azure subscription doesn't have access to BYOS and you need to [request it](#request-access-to-byos-for-your-azure-subscriptions).
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***
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### Plan and prepare your Storage account
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If you use Azure portal to create a BYOS-enabled Speech resource, an associated Storage account can be created automatically. For all other provisioning methods (Azure CLI, PowerShell, REST API Request) you need to use existing Storage account.

articles/ai-services/speech-service/speech-services-quotas-and-limits.md

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| Quota | Free (F0) | Standard (S0) |
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|-----|-----|-----|
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|REST API limit | Not available for F0 | 50 requests per 5 seconds |
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| Max JSON payload size to create a synthesis job | N/A | 500 kilobytes |
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| Concurrent active synthesis jobs | N/A | 200 |
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| Max number of text inputs per synthesis job | N/A | 1000 |
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|REST API limit | Not available for F0 | 100 requests per 10 seconds |
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| Max JSON payload size to create a synthesis job | N/A | 2 megabytes |
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| Concurrent active synthesis jobs | N/A | No limit |
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| Max number of text inputs per synthesis job | N/A | 10000 |
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|Max time to live for a synthesis job since it being in the final state | N/A | Up to 31 days (specified using properties) |
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#### Custom neural voice - professional

articles/ai-studio/concepts/rbac-ai-studio.md

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## Azure AI hub resource vs Azure AI project
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In the Azure AI Studio, there are two levels of access: the Azure AI hub resource and the Azure AI project. The resource is home to the infrastructure (including virtual network setup, customer-managed keys, managed identities, and policies) as well as where you configure your Azure AI services. Azure AI hub resource access can allow you to modify the infrastructure, create new Azure AI hub resources, and create projects. Azure AI projects are a subset of the Azure AI hub resource that act as workspaces that allow you to build and deploy AI systems. Within a project you can develop flows, deploy models, and manage project assets. Project access lets you develop AI end-to-end while taking advantage of the infrastructure setup on the Azure AI hub resource.
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In the Azure AI Studio, there are two levels of access: the Azure AI hub and the Azure AI project. The AI hub is home to the infrastructure (including virtual network setup, customer-managed keys, managed identities, and policies) as well as where you configure your Azure AI services. Azure AI hub access can allow you to modify the infrastructure, create new Azure AI hub resources, and create projects. Azure AI projects are a subset of the Azure AI hub resource that act as workspaces that allow you to build and deploy AI systems. Within a project you can develop flows, deploy models, and manage project assets. Project access lets you develop AI end-to-end while taking advantage of the infrastructure setup on the Azure AI hub resource.
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:::image type="content" source="../media/concepts/azureai-hub-project-relationship.png" alt-text="Diagram of the relationship between AI Studio resources." lightbox="../media/concepts/azureai-hub-project-relationship.png":::
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| `Microsoft.Insights/Components/Write` | Write to an application insights component configuration. |
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| `Microsoft.OperationalInsights/workspaces/write` | Create a new workspace or links to an existing workspace by providing the customer ID from the existing workspace. |
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## Sample enterprise RBAC setup
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The following is an example of how to set up role-based access control for your Azure AI Studio for an enterprise.
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> [!NOTE]
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> You must be an owner of the resource at that level to create custom roles within that resource.
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## Scenario: Use a customer-managed key
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When using a customer-managed key (CMK), an Azure Key Vault is used to store the key. The user or service principal used to create the workspace must have owner or contributor access to the key vault.
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If your Azure AI hub is configured with a **user-assigned managed identity**, the identity must be granted the following roles. These roles allow the managed identity to create the Azure Storage, Azure Cosmos DB, and Azure Search resources used when using a customer-managed key:
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- `Microsoft.Storage/storageAccounts/write`
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- `Microsoft.Search/searchServices/write`
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- `Microsoft.DocumentDB/databaseAccounts/write`
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Within the key vault, the user or service principal must have create, get, delete, and purge access to the key through a key vault access policy. For more information, see [Azure Key Vault security](/azure/key-vault/general/security-features#controlling-access-to-key-vault-data).
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## Next steps
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- [How to create an Azure AI hub resource](../how-to/create-azure-ai-resource.md)

articles/aks/custom-node-configuration.md

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## Next steps
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- Learn [how to configure your AKS cluster](cluster-configuration.md).
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- Learn [how to configure your AKS cluster](./concepts-clusters-workloads.md).
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- Learn how [upgrade the node images](node-image-upgrade.md) in your cluster.
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- See [Upgrade an Azure Kubernetes Service (AKS) cluster](upgrade-cluster.md) to learn how to upgrade your cluster to the latest version of Kubernetes.
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- See the list of [Frequently asked questions about AKS](faq.md) to find answers to some common AKS questions.

articles/automation/automation-linux-hrw-install.md

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ms.date: 04/21/2024
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> [!NOTE]
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> Hybrid Worker would follow support timelines of the OS vendor.
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> Before enabling the Update Management feature, which depends on the system Hybrid Runbook Worker role, confirm the distributions it supports [here](update-management/operating-system-requirements.md).
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The minimum requirements for a Linux system and user Hybrid Runbook Worker are:

articles/automation/automation-windows-hrw-install.md

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description: This article tells how to deploy an agent-based Hybrid Runbook Worker that you can use to run runbooks on Windows-based machines in your local datacenter or cloud environment.
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ms.date: 04/21/2024
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---
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title: Azure Arc Jumpstart scenario using Edge Storage Accelerator (preview)
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description: Learn about an Azure Arc scenario that uses Edge Storage Accelerator.
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author: sethmanheim
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ms.author: sethm
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ms.topic: overview
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ms.date: 04/18/2024
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---
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# Azure Arc Jumpstart scenario using Edge Storage Accelerator
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Edge Storage Accelerator (ESA) collaborated with the [Arc Jumpstart](https://azurearcjumpstart.com/) team to implement a scenario in which a computer vision AI model detects defects in bolts by analyzing video from a supply line video feed streamed over Real-Time Streaming Protocol (RTSP). The identified defects are then stored in a container within a storage account using Edge Storage Accelerator.
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## Scenario description
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In this automated setup, ESA is deployed on an [AKS Edge Essentials](/azure/aks/hybrid/aks-edge-overview) single-node instance, running in an Azure virtual machine. An Azure Resource Manager template is provided to create the necessary Azure resources and configure the **LogonScript.ps1** custom script extension. This extension handles AKS Edge Essentials cluster creation, Azure Arc onboarding for the Azure VM and AKS Edge Essentials cluster, and Edge Storage Accelerator deployment. Once AKS Edge Essentials is deployed, ESA is installed as a Kubernetes service that exposes a CSI driven storage class for use by applications in the Edge Essentials Kubernetes cluster.
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For more information, see the following articles:
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- [Watch the ESA jumpstart scenario on YouTube](https://youtu.be/Qnh2UH1g6Q4)
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- [Visit the ESA jumpstart documentation](https://aka.ms/esajumpstart)
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## Next steps
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- [Edge Storage Accelerator overview](overview.md)
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- [AKS Edge Essentials overview](/azure/aks/hybrid/aks-edge-overview)

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