-This article uses a sample React single-page application (SPA) to illustrate how to add Azure Active Directory B2C (Azure AD B2C) authentication to your React apps.

-| protectedResources| endpoint| The URL of the web API: `http://localhost:5000/api/todolist`. |

- endpoint: "http://localhost:5000/api/todolist",

-You're now ready to test the React scoped access to the API. In this step, run both the web API and the sample React application on your local machine. Then, sign in to the React application, and select the **TodoList** button to start a request to the protected API.

-1. Complete the sign-up or sign in process. Upon successful sign in, you should see your profile.

-1. From the menu, select **Hello API**.

-1. Check out the result of the REST API call. The following screenshot shows the React sample REST API return value.

-description: In this quickstart, learn how a Windows Presentation Foundation (WPF) application can get an access token and call an API protected by the Microsoft identity platform.

-# Quickstart: Acquire a token and call Microsoft Graph API from a Windows desktop app

->

-#### Using Microsoft.Identity.Web templates

-You can create a web API from scratch by using Microsoft.Identity.Web project templates. For details see [Microsoft.Identity.Web - Web API project template](https://aka.ms/ms-id-web/webapi-project-templates).

-#### Starting from an existing ASP.NET Core 3.1 application

- services.AddMicrosoftIdentityWebApiAuthentication(Configuration, "AzureAd");

-you can also write the following (which is equivalent)

-public void ConfigureServices(IServiceCollection services)

- // Adds Microsoft Identity platform (AAD v2.0) support to protect this API

- services.AddAuthentication(AzureADDefaults.JwtBearerAuthenticationScheme)

- .AddMicrosoftIdentityWebApi(Configuration, "AzureAd");

-services.AddControllers();

-}

-> If you use Microsoft.Identity.Web and don't set the `Audience` in *appsettings.json*, the following is used:

-> - `$"{ClientId}"` if you have set the [access token accepted version](scenario-protected-web-api-app-registration.md#accepted-token-version) to `2`, or for Azure AD B2C web APIs.

-> - `$"api://{ClientId}` in all other cases (for v1.0 [access tokens](access-tokens.md)).

-> For details, see Microsoft.Identity.Web [source code](https://github.com/AzureAD/microsoft-identity-web/blob/d2ad0f5f830391a34175d48621a2c56011a45082/src/Microsoft.Identity.Web/Resource/RegisterValidAudience.cs#L70-L83).

-The preceding code snippet is extracted from the [ASP.NET Core web API incremental tutorial](https://github.com/Azure-Samples/active-directory-dotnet-native-aspnetcore-v2/blob/63087e83326e6a332d05fee6e1586b66d840b08f/1.%20Desktop%20app%20calls%20Web%20API/TodoListService/Startup.cs#L23-L28). The detail of **AddMicrosoftIdentityWebApiAuthentication** is available in [Microsoft.Identity.Web](microsoft-identity-web.md). This method calls [AddMicrosoftIdentityWebAPI](/dotnet/api/microsoft.identity.web.microsoftidentitywebapiauthenticationbuilderextensions.addmicrosoftidentitywebapi), which itself instructs the middleware on how to validate the token.

-## Startup.cs

-Your web API will need to acquire a token for the downstream API. You specify it by adding the `.EnableTokenAcquisitionToCallDownstreamApi()` line after `.AddMicrosoftIdentityWebApi(Configuration)`. This line exposes the `ITokenAcquisition` service, that you can use in your controller/pages actions. However, as you'll see in the next two bullet points, you can do even simpler. You'll also need to choose a token cache implementation, for example `.AddInMemoryTokenCaches()`, in *Startup.cs*:

-public class Startup

-{

- // ...

- public void ConfigureServices(IServiceCollection services)

- {

- // ...

- services.AddAuthentication(JwtBearerDefaults.AuthenticationScheme)

- .AddMicrosoftIdentityWebApi(Configuration, Configuration.GetSection("AzureAd"))

- .EnableTokenAcquisitionToCallDownstreamApi()

- .AddInMemoryTokenCaches();

- // ...

- }

- // ...

-}

-1. Add `.AddMicrosoftGraph()` after `.EnableTokenAcquisitionToCallDownstreamApi()` in the *Startup.cs* file. `.AddMicrosoftGraph()` has several overrides. Using the override that takes a configuration section as a parameter, the code becomes:

-public class Startup

-{

- // ...

- public void ConfigureServices(IServiceCollection services)

- {

- // ...

- services.AddAuthentication(JwtBearerDefaults.AuthenticationScheme)

- .AddMicrosoftIdentityWebApi(Configuration, Configuration.GetSection("AzureAd"))

- .EnableTokenAcquisitionToCallDownstreamApi()

- .AddMicrosoftGraph(Configuration.GetSection("GraphBeta"))

- .AddInMemoryTokenCaches();

- // ...

- }

- // ...

-}

-public class Startup

-{

- // ...

- public void ConfigureServices(IServiceCollection services)

- {

- // ...

- services.AddAuthentication(JwtBearerDefaults.AuthenticationScheme)

- .AddMicrosoftIdentityWebApi(Configuration, "AzureAd")

- .EnableTokenAcquisitionToCallDownstreamApi()

- .AddDownstreamWebApi("MyApi", Configuration.GetSection("GraphBeta"))

- .AddInMemoryTokenCaches();

- // ...

- }

- // ...

-}

-The following image shows the various possibilities of *Microsoft.Identity.Web* and their impact on the *Startup.cs* file:

- - **Azure AD Certificate-based authentication (CBA) settings**. For more information, see [What is pass-through authentication](../authentication/concept-certificate-based-authentication.md)

- For Windows 10, Windows Server 2016 and later versions, itΓÇÖs recommended to use SSO via [Primary Refresh Token (PRT)](../devices/concept-primary-refresh-token.md) with [Azure AD joined devices](../devices/concept-azure-ad-join.md), [hybrid Azure AD joined devices](../devices/concept-azure-ad-join-hybrid.md) or personal registered devices via Add Work or School Account.

-Do the following:

-1. To access the UX, sign in to the [Azure AD portal](https://aka.ms/stagedrolloutux).

-2. Select the **Enable Staged Rollout for managed user sign-in** link.

- For example, if you want to enable **Password Hash Sync** and **Seamless single sign-on**, slide both controls to **On**.

-

-

-3. Add the groups to the feature to enable *pass-through authentication* and *seamless SSO*. To avoid a UX time-out, ensure that the security groups contain no more than 200 members initially.

-Use Privileged Identity Management (PIM) in Azure Active Directory (Azure AD), part of Microsoft Entra,to allow eligible role members for privileged access groups to schedule role activation for a specified date and time. They can also select a activation duration up to the maximum duration configured by administrators.

- 

- 

- If the [role requires approval](pim-resource-roles-approval-workflow.md) to activate, a notification will appear in the upper right corner of your browser informing you the request is pending approval.

- 

-* Embark supports **SP** initiated SSO.

-1. On the **Basic SAML Configuration** section, enter the values for the following fields:

- In the **Sign on URL** text box, type a URL using the following pattern:

- `https://<ENVIRONMENT>.ehr.com/microsoftbenefits`

- > The Sign on URL value is not real. Update the value with the actual Sign on URL. Contact [Embark support team](mailto:wtw.software.support.notification@willistowerswatson.com) to get the value. You can also refer to the patterns shown in the **Basic SAML Configuration** section in the Azure portal.

-1. Your Embark application expects the SAML assertions in a specific format, which requires you to add custom attribute mappings to your SAML token attributes configuration. The following screenshot shows an example for this. The default value of **Unique User Identifier** is **user.userprincipalname** but Embark expects this to be mapped with the user's employee id. For that you can use **user.employeeid** attribute from the list or use the appropriate attribute value based on your organization configuration..

-* Click on **Test this application** in Azure portal. This will redirect to Embark Sign-on URL where you can initiate the login flow.

-* Go to Embark Sign-on URL directly and initiate the login flow from there.

-* You can use Microsoft My Apps. When you click the Embark tile in the My Apps, this will redirect to Embark Sign-on URL. For more information about the My Apps, see [Introduction to the My Apps](../user-help/my-apps-portal-end-user-access.md).

- mountOptions:

- - nconnect=8 # only supported on linux kernel version >= 5.3

-[enable-blob-csi-driver]: azure-blob-csi.md#before-you-begin

- mountOptions:

- - nconnect=8 # only supported on linux kernel version >= 5.3

-[enable-blob-csi-driver]: azure-blob-csi.md#before-you-begin

-|kind | Managed or unmanaged (blob based) disk | `managed` (`dedicated` and `shared` are deprecated) | No | `managed`|

-az k8s-configuration flux create -g flux-demo-rg -c flux-demo-arc -n cluster-config --namespace cluster-config -t connectedClusters --scope cluster -u https://github.com/Azure/gitops-flux2-kustomize-helm-mt --branch main --kustomization name=infra path=./infrastructure prune=true --kustomization name=apps path=./apps/staging prune=true dependsOn=["infra"]

-1. Set the parameter values to be used while creating the `fluxConfigurations` resource.

-## Azure Arc-enabled VMWare VCenter issues

-When deploying the resource bridge on VMWare Vcenter, you may get an error saying that you have insufficient permission. To resolve this issue, make sure that your user account has all of the following privileges in VMware vCenter and then try again.

-* [Open an Azure support request](../../azure-portal/supportability/how-to-create-azure-support-request.md).

-> To upgrade the arc resource bridge VM to the latest version, you will need to perform the onboarding again with the **same resource IDs**. This will cause some downtime as operations performed through Arc during this time might fail.

-There are two different sets of credentials stored on the Arc resource bridge. But you can use the same account credentials for both.

-If you're running this command from a different workstation, you must make sure the following files are copied to the new workstation in the same location.

-[Troubleshoot common issues related to resource bridge](../resource-bridge/troubleshoot-resource-bridge.md)

-description: This quickstart shows how to connect to Azure Government and create a web app in Azure Government using portal

-cloud: gov

-#Customer intent: As a developer working for a federal government agency "x", I want to connect to Azure Government using portal so I can start creating apps and developing against Azure Government's secure isolated datacenters.

-Microsoft Azure Government delivers a dedicated cloud with world-class security and compliance, enabling US government agencies and their partners to transform their workloads to the cloud. To manage your Azure Government cloud workloads and applications you can connect to Azure Government using different tools, as described in the following video.

-This quickstart shows how to use the Azure Government portal to access and start managing resources in Azure Government. The Azure Government portal is the primary way most people will connect to their Azure Government environment. If you don't have an Azure Government subscription, create a [free account](https://azure.microsoft.com/global-infrastructure/government/request/) before you begin.

-Sign in using your Azure Government credentials. Once you sign it, you should see "Microsoft Azure Government" in the upper left of the main navigation bar.

-

-

-This quickstart showed you how to use the Azure Government portal to connect to Azure Government. Once you are connected to Azure Government, you may want to explore Azure services. Make sure you check out the variations, described in [Compare Azure Government and global Azure](./compare-azure-government-global-azure.md). To learn more about Azure services, continue to the Azure documentation.

-## Networking

-The Azure Monitor Agent supports Azure service tags. Both *AzureMonitor* and *AzureResourceManager* tags are required. It supports connecting via *direct proxies, Log Analytics gateway, and private links* as described in the following sections.

-### Firewall requirements

-| Cloud |Endpoint |Purpose |Port |Direction |Bypass HTTPS inspection|

-|||||--|--|

-| Azure Commercial |global.handler.control.monitor.azure.com |Access control service|Port 443 |Outbound|Yes |

-| Azure Commercial |`<virtual-machine-region-name>`.handler.control.monitor.azure.com |Fetch data collection rules for specific machine |Port 443 |Outbound|Yes |

-| Azure Commercial |`<log-analytics-workspace-id>`.ods.opinsights.azure.com |Ingest logs data |Port 443 |Outbound|Yes |

-| Azure Commercial | management.azure.com | Only needed if sending time series data (metrics) to Azure Monitor [Custom metrics](../essentials/metrics-custom-overview.md) database | Port 443 | Outbound | Yes |

-| Azure Government | Replace '.com' above with '.us' | Same as above | Same as above | Same as above| Same as above |

-| Azure China | Replace '.com' above with '.cn' | Same as above | Same as above | Same as above| Same as above |

-If you use private links on the agent, you must also add the [DCE endpoints](../essentials/data-collection-endpoint-overview.md#components-of-a-data-collection-endpoint).

-### Proxy configuration

-If the machine connects through a proxy server to communicate over the internet, review the following requirements to understand the network configuration required.

-The Azure Monitor Agent extensions for Windows and Linux can communicate either through a proxy server or a [Log Analytics gateway](./gateway.md) to Azure Monitor by using the HTTPS protocol. Use it for Azure virtual machines, Azure virtual machine scale sets, and Azure Arc for servers. Use the extensions settings for configuration as described in the following steps. Both anonymous and basic authentication by using a username and password are supported.

-> [!IMPORTANT]

-> Proxy configuration is not supported for [Azure Monitor Metrics (Public preview)](../essentials/metrics-custom-overview.md) as a destination. If you're sending metrics to this destination, it will use the public internet without any proxy.

-1. Use this flowchart to determine the values of the *`Settings` and `ProtectedSettings` parameters first.

- 

-1. After determining the `Settings` and `ProtectedSettings` parameter values, *provide these other parameters* when you deploy Azure Monitor Agent, using PowerShell commands, as shown in the following examples:

-# [Windows VM](#tab/PowerShellWindows)

-```powershell

-$settingsString = @{"proxy" = @{mode = "application"; address = "http://[address]:[port]"; auth = true}}

-$protectedSettingsString = @{"proxy" = @{username = "[username]"; password = "[password]"}}

-Set-AzVMExtension -ExtensionName AzureMonitorWindowsAgent -ExtensionType AzureMonitorWindowsAgent -Publisher Microsoft.Azure.Monitor -ResourceGroupName <resource-group-name> -VMName <virtual-machine-name> -Location <location> -TypeHandlerVersion 1.0 -SettingString $settingsString -ProtectedSettingString $protectedSettingsString

-```

-# [Linux VM](#tab/PowerShellLinux)

-```powershell

-$settingsString = @{"proxy" = @{mode = "application"; address = "http://[address]:[port]"; auth = true}}

-$protectedSettingsString = @{"proxy" = @{username = "[username]"; password = "[password]"}}

-Set-AzVMExtension -ExtensionName AzureMonitorLinuxAgent -ExtensionType AzureMonitorLinuxAgent -Publisher Microsoft.Azure.Monitor -ResourceGroupName <resource-group-name> -VMName <virtual-machine-name> -Location <location> -TypeHandlerVersion 1.5 -SettingString $settingsString -ProtectedSettingString $protectedSettingsString

-```

-# [Windows Arc-enabled server](#tab/PowerShellWindowsArc)

-```powershell

-$settingsString = @{"proxy" = @{mode = "application"; address = "http://[address]:[port]"; auth = true}}

-$protectedSettingsString = @{"proxy" = @{username = "[username]"; password = "[password]"}}

-New-AzConnectedMachineExtension -Name AzureMonitorWindowsAgent -ExtensionType AzureMonitorWindowsAgent -Publisher Microsoft.Azure.Monitor -ResourceGroupName <resource-group-name> -MachineName <arc-server-name> -Location <arc-server-location> -Setting $settingsString -ProtectedSetting $protectedSettingsString

-```

-# [Linux Arc-enabled server](#tab/PowerShellLinuxArc)

-```powershell

-$settingsString = @{"proxy" = @{mode = "application"; address = "http://[address]:[port]"; auth = true}}

-$protectedSettingsString = @{"proxy" = @{username = "[username]"; password = "[password]"}}

-New-AzConnectedMachineExtension -Name AzureMonitorLinuxAgent -ExtensionType AzureMonitorLinuxAgent -Publisher Microsoft.Azure.Monitor -ResourceGroupName <resource-group-name> -MachineName <arc-server-name> -Location <arc-server-location> -Setting $settingsString -ProtectedSetting $protectedSettingsString

-```

-### Log Analytics gateway configuration

-1. Follow the preceding instructions to configure proxy settings on the agent and provide the IP address and port number that corresponds to the gateway server. If you've deployed multiple gateway servers behind a load balancer, the agent proxy configuration is the virtual IP address of the load balancer instead.

-1. Add the **configuration endpoint URL** to fetch data collection rules to the allowlist for the gateway

- `Add-OMSGatewayAllowedHost -Host global.handler.control.monitor.azure.com`

- `Add-OMSGatewayAllowedHost -Host <gateway-server-region-name>.handler.control.monitor.azure.com`.

- (If you're using private links on the agent, you must also add the [data collection endpoints](../essentials/data-collection-endpoint-overview.md#components-of-a-data-collection-endpoint).)

-1. Add the **data ingestion endpoint URL** to the allowlist for the gateway

- `Add-OMSGatewayAllowedHost -Host <log-analytics-workspace-id>.ods.opinsights.azure.com`.

-1. Restart the **OMS Gateway** service to apply the changes

- `Stop-Service -Name <gateway-name>`

- `Start-Service -Name <gateway-name>`.

-### Private link configuration

-To configure the agent to use private links for network communications with Azure Monitor, follow instructions to [enable network isolation](./azure-monitor-agent-data-collection-endpoint.md#enable-network-isolation-for-the-azure-monitor-agent) by using [data collection endpoints](azure-monitor-agent-data-collection-endpoint.md).

-description: Use data collection endpoints to uniquely configure ingestion settings for your machines.

-# Enable network isolation for the Azure Monitor agent

-## Create data collection endpoint

-## Create private link

-## Add DCE to AMPLS

-[Azure Monitor Agent (AMA)](./agents-overview.md) collects monitoring data from the guest operating system of Azure and hybrid virtual machines. The agent delivers the data to Azure Monitor for use by features, insights, and other services, such as [Microsoft Sentinel](../../sentintel/../sentinel/overview.md) and [Microsoft Defender for Cloud](../../defender-for-cloud/defender-for-cloud-introduction.md). Azure Monitor Agent replaces the Log Analytics agent (also known as MMA and OMS) for both Windows and Linux machines Azure Monitor and introduces a simplified, flexible method of configuring collection configuration called [Data Collection Rules (DCRs)](../essentials/data-collection-rule-overview.md). This article provides high-level guidance on when and how to migrate to the new Azure Monitor Agent (AMA) based on the agent's benefits and limitations.

-## Benefits

- - AMA uses Managed Identity or Azure Active Directory (Azure AD) tokens (for clients), which are much more secure than the legacy authentication methods.

- - AMA provides a higher events per second (EPS) upload rate compared to legacy agents.

- - DCRs lets you configure data collection for specific machines connected to a workspace as compared to the ΓÇ£all or nothingΓÇ¥ mode that legacy agents have.

- - Centralized, ΓÇÿin the cloudΓÇÖ agent configuration makes every action, across the data collection lifecycle, simpler and more easily scalable, from onboarding to deployment to updates and changes over time.

-## When should I migrate to the Azure Monitor Agent?

-Your migration plan to the Azure Monitor Agent should include the following considerations:

- Most new capabilities in Azure Monitor will be made available only with Azure Monitor Agent. Review whether Azure Monitor Agent has the features you require and if there are some features that you can temporarily do without to get other important features in the new agent.

- If Azure Monitor Agent has all the core capabilities you need, start transitioning to it. If there are critical features that you require, continue with the current agent until Azure Monitor Agent reaches parity.

-> [!IMPORTANT]

-> The Log Analytics agent will be [retired on **31 August, 2024**](https://azure.microsoft.com/updates/were-retiring-the-log-analytics-agent-in-azure-monitor-on-31-august-2024/). If you are currently using the Log Analytics agent with Azure Monitor or other supported features and services, you should start planning your migration to Azure Monitor Agent using the information in this article.

-## Should I install Azure Monitor Agent together with a legacy agent?

-Azure Monitor Agent can run alongside the legacy Log Analytics agents on the same machine so that you can continue to use their existing functionality during evaluation or migration. While this allows you to begin the transition given the limitations, keep in mind the considerations below:

-> [!NOTE]

-> When you use both agents during evaluation or migration, you can use the **Category** column of the [Heartbeat](/azure/azure-monitor/reference/tables/Heartbeat) table in your Log Analytics workspace, and filter for **Azure Monitor Agent**.

-## Current capabilities

-For full details about the capabilities of Azure Monitor Agent and a comparison with legacy agent capabilities, see [Azure Monitor Agent overview](../agents/agents-overview.md).

-If you use Microsoft Sentinel, see [Gap analysis for Microsoft Sentinel](../../sentinel/ama-migrate.md#gap-analysis-between-agents) for a comparison of the extra data collected by Microsoft Sentinel.

-## Test migration

-To ensure safe deployment during migration, begin testing with few resources running the existing Log Analytics agent in your nonproduction environment. After you validate the data collected on these test resources, roll out to production by following the same steps.

-[Azure Policy](../../governance/policy/overview.md) and [Resource Manager templates](../resource-manager-samples.md) provide scalability to migrate a large number of agents.

-Start by analyzing your current monitoring setup with the Log Analytics agent using the following criteria:

- - Sources, such as virtual machines, virtual machine scale sets, and on-premises servers

- - Data sources, such as performance counters, Windows event logs, and Syslog

- - Destinations, such as Log Analytics workspaces

-> Before you deploy to a large number of agents, you should consider [configuring the workspace](agent-data-sources.md) to disable data collection for the Log Analytics agent. If you leave it enabled, you may collect duplicate data resulting in increased cost until you remove the Log Analytics agents from your virtual machines. Alternatively, you may choose to have duplicate collection during the migration period until you can confirm that the AMA has been deployed and configured correctly.

-See [Using Azure Policy](azure-monitor-agent-manage.md#using-azure-policy) for details on deploying Azure Monitor Agent across a set of virtual machines. Associate the agents to the data collection rules developed during your [testing](#test-migration).

-Validate that data is flowing as expected with the Azure Monitor Agent and that all downstream dependencies like dashboards, alerts, and runbook workers. Workbooks should all continue to function using data from the new agent.

-When you confirm that data is being collected properly, [uninstall the Log Analytics agent](./agent-manage.md#uninstall-agent) from the resources. Don't uninstall it if you need to use it for System Center Operations Manager scenarios or others solutions not yet available on Azure Monitor Agent. Clean up any configuration files, workspace keys, or certificates that were used previously by the Log Analytics agent.

-Statseat supports EU Data Boundary for Application Insights resources in the following regions:

-N/A

-N/A

-Track the Disk I/O failure when using disk persistence for retriable telemetry

-Not supported yet.

->[!NOTE]

->For Azure Red Hat OpenShift V3, a template ConfigMap file is created in the *openshift-azure-logging* namespace.

->

- > [!NOTE]

- > This step is not required when working with Azure Red Hat OpenShift V3 because the ConfigMap template already exists on the cluster.

-2. Edit the ConfigMap yaml file with your customizations to collect stdout, stderr, and/or environmental variables. If you are editing the ConfigMap yaml file for Azure Red Hat OpenShift V3, first run the command `oc edit configmaps container-azm-ms-agentconfig -n openshift-azure-logging` to open the file in a text editor.

-3. For clusters other than Azure Red Hat OpenShift V3, create ConfigMap by running the following kubectl command: `kubectl apply -f <configmap_yaml_file.yaml>`.

-To verify the configuration was successfully applied to a cluster other than Azure Red Hat OpenShift V3, use the following command to review the logs from an agent pod: `kubectl logs omsagent-fdf58 -n kube-system`. If there are configuration errors from the omsagent pods, the output will show errors similar to the following:

- >[!NOTE]

- >This command is not applicable to Azure Red Hat OpenShift V3 cluster.

- >

-After you correct the error(s) in ConfigMap on clusters other than Azure Red Hat OpenShift V3, save the yaml file and apply the updated ConfigMaps by running the command: `kubectl apply -f <configmap_yaml_file.yaml`. For Azure Red Hat OpenShift V3, edit and save the updated ConfigMaps by running the command:

-``` bash

-oc edit configmaps container-azm-ms-agentconfig -n openshift-azure-logging

-```

-If you have already deployed a ConfigMap on clusters other than Azure Red Hat OpenShift V3 and you want to update it with a newer configuration, you can edit the ConfigMap file you've previously used and then apply using the same command as before, `kubectl apply -f <configmap_yaml_file.yaml`. For Azure Red Hat OpenShift V3, edit and save the updated ConfigMaps by running the command:

-``` bash

-oc edit configmaps container-azm-ms-agentconfig -n openshift-azure-logging

-```

-On May 31, 2022 Container Insights support for Azure Red Hat OpenShift v4.x will be retired. If you use the script-based model of Container Insights for Azure Red Hat OpenShift v4.x, make sure to transition to Container Insights on [Azure Arc enabled Kubernetes](./container-insights-enable-arc-enabled-clusters.md) prior to that date.

- 1. One or more subscriptions from the **Subscriptions** dropdown.

- 1. Resources and resource groups from the **CurrentResource** dropdown.

- 1. A time range for which to view data from the **TimeRange** dropdown.

- | West US 2 | | | | |

-description: A description of Azure Percept for DeepStream developer tools that provide a custom developer experience.

-# Azure Percept for DeepStream overview

-Azure Percept for DeepStream includes developer tools that provide a custom developer experience. It enables you to create NVIDIA DeepStream containers using Microsoft-based images and guidance, supported models from NVIDIA out of the box, and/or bring your own models.

-DeepStream is NVIDIAΓÇÖs toolkit to develop and deploy Vision AI applications and services. It provides multi-platform, scalable, Transport Layer Security (TLS)-encrypted security that can be deployed on-premises, on the edge, and in the cloud.

-## Azure Percept for DeepStream offers:

- Auto selection of AI model execution and inference provider: One of several execution providers, such as ORT, CUDA, and TENSORT, are automatically selected to simplify your development process.

- Region of Interest (ROI) configuration widget: Percept Player, a web app widget, is included for customizing ROIs to enable event detection for your business scenario.

- You can add a Python-based model and parser using a configuration file, instead of hardcoding it into the pipeline.

- This solution supports many of the most common CV models in use today, for example NVIDIA TAO, ONNX, CAFFE, UFF (TensorFlow), and Triton.

- Support for model and container customization, USB or RTSP camera and pre-recorded video streams, event-based video snippet storage in Azure Storage and Alerts, and AI model deployment via Azure IoT Module Twin update.

-## Azure Percept for DeepStream key components

-The following table provides a list of Azure Percept for DeepStreamΓÇÖs key components and a description of each one.

-| Components | Details |

-|-||

-| **Edge devices** | Azure Percept for DeepStream is available on the following devices:<br> - [Azure Stack HCI](/azure-stack/hci/overview): Requires a NVIDIA GPU (T4 or A2)<br> - [NVIDIA Jetson Orin](https://www.nvidia.com/autonomous-machines/embedded-systems/jetson-orin/)<br> - [NVIDIA Jetson Xavier](https://www.nvidia.com/autonomous-machines/embedded-systems/jetson-agx-xavier/)<br><br>**Note**<br>You can use any of the listed devices with any of the development paths. Some implementation steps may differ depending on the architecture of your device. Azure Stack HCI uses AMD64. Jetson devices use ARM64.<br><br> |

-| **Computer vision models** | Azure Percept for DeepStream can work with many different computer vision (CV) models as outlined:<br><br> - **NVIDIA Models** <br>For example: Body Pose Estimation and License Plate Recognition. License Plate Recognition includes three models: traffic cam net, license plate detection, and license plate reading and other Nivida Models.<br><br> - **ONNX Models** <br>For example: SSD-MobileNetV1, YOLOv4, Tiny YOLOv3, EfficentNet-Lite.<br><br> |

-| **Development Paths** | Azure Percept for DeepStream offers three development paths:<br><br> - **Getting started path** <br>This path uses pre-trained models and pre-recorded videos of simulated manufacturing environment to demonstrate the steps required to create an Edge AI solution using Azure Percept for DeepStream.<br>If you're just getting started on your computer vision (CV) app journey or simply want to learn more about Azure Percept for DeepStream, we recommend this path.<br><br> - **Pre-built model path** <br>This path provides pre-built parsers in Python for the CV models outlined earlier. You can easily deploy one of these models and integrate your own video stream.<br>If you're familiar with Azure IoT Edge solutions and want to leverage one of the supported models with an existing video stream, we recommend this path. <br><br> - **Bring your own model (BYOM) path**<br>This path provides you with steps of how to integrate your own custom model and parser into your Azure Percept for DeepStream Edge AI solution.<br>If you're an experienced developer who is familiar with cloud-based CV solutions and want a simplified deployment experience Azure Percept for DeepStream, we recommend this path.<br><br> |

-## Next steps

-Text to come.

-<!-- You're now ready to start using Azure Percept for DeepStream to create, manage, and deploy custom Edge AI solutions. We recommend the following resources to get started:

-description: A description of Azure Percept on Azure Stack HCI.

-# Azure Percept on Azure Stack HCI overview

-Azure Percept on Azure Stack HCI is a virtualized workload that enables you to extend the capabilities of your existing [Azure Stack HCI](https://azure.microsoft.com/products/azure-stack/hci/) deployments quickly and easily by adding sophisticated AI solutions at the Edge. It is available as a preconfigured virtual hard disk (VHDX) that functions as an Azure IoT Edge device with AI capabilities.

-## Azure Percept on Azure Stack HCI enables you:

-### Maximize your investments easily

-Maximize your existing investments in the Azure Stack HCI computer infrastructure when you run Azure Percept on Azure Stack HCI. You can leverage [Windows Admin Center (WAC)](https://www.microsoft.com/windows-server/windows-admin-center) management expertise with Azure Percept for Azure Stack HCI extension to ingest and analyze data streams from your existing IP camera infrastructure. Using WAC also enables you to easily deploy, manage, scale, and secure your Azure Percept virtual machine (VM).

-### Bring data to storage and compute

-Use Azure Stack HCIΓÇÖs robust storage and compute options to pre-process raw data at the Edge before sending it to Azure for further processing and training. Since artificial intelligence/machine learning (AI/ML) solutions at the edge generate and process a significant amount of data, using Azure Stack HCI reduces the amount of data transfer or bandwidth consumed into Azure.

-### Maintain device security

-Azure Percept on Azure Stack HCI provides multiple layers of security. Leverage security mechanisms and processes built into the solution, including virtual trusted platform module (TPM), secure boot, secure provisioning, trusted software, secure update, and [Microsoft Defender for IoT](https://www.microsoft.com/security/blog/2021/11/02/how-microsoft-defender-for-iot-can-secure-your-iot-devices/#:~:text=Microsoft%20Defender%20for%20IoT%20is%20an%20open%20platform,to%20enrich%20the%20information%20coming%20from%20multiple%20sources).

-## Key components of Azure Percept on Azure Stack HCI

-Azure Percept on Azure Stack HCI integrates with Azure Percept Studio, Azure IoT Edge, IoT Hub, and Spatial Analysis from Azure Cognitive Services to create an end-to-end intelligent solution that leverages your existing IP camera devices.

-The following diagram provides a high-level view of the Azure Percept on Azure Stack HCI architecture.

-

-**Azure Percept on Azure Stack HCI includes the following key components:**

-### Azure Stack HCI

-[Azure Stack HCI](https://azure.microsoft.com/products/azure-stack/hci/) is a hyperconverged infrastructure (HCI) cluster solution that hosts virtualized Windows and Linux workloads and their storage in a hybrid environment that combines on-premises infrastructure with Azure cloud services. It requires a minimum of two clustered compute nodes, scales to as many as 16 clustered nodes, and enables data pre-processing at the edge by providing robust storage and compute options. Azure Percept on Azure Stack HCI runs as a pre-configured VM on Azure Stack HCI and has failover capability to ensure continuous operation. For information about customizable solutions that you can configure to meet your needs, see [certified Azure Stack HCI systems](https://azurestackhcisolutions.azure.microsoft.com/#/catalog).

-### Azure Percept virtual machine (VM)

-The Azure Percept VM leverages a virtual hard disk (VHDX) that runs on the Azure Stack HCI device. It enables you to host your own AI models, communicate with the cloud via IoT Hub, and update the Azure Percept virtual machine (VM) so you can update containers, download models, and manage devices remotely.

-The Percept VM leverages Azure IoT Edge to communicate with [Azure IoT Hub](https://www.bing.com/aclk?ld=e8d3D-tqxgHU7f2fug-xNf9TVUCUyRhu5fu58-tWHmwhmAtKIzkXCQETOv1QnKdXCr1kFm6NQ4SA4K5mukLPrpKC5z7nTlhrXnaiTqPPGu2a47SnDq-aKylUzhYQLxKs1yyOtnDuD1DDg4q04CZdFUFwPani9jnp6DLiQPMoYBkhhEJ3FV6SFro1VVB67p_n_4De1B7A&u=aHR0cHMlM2ElMmYlMmZhenVyZS5taWNyb3NvZnQuY29tJTJmZW4tdXMlMmZmcmVlJTJmaW90JTJmJTNmT0NJRCUzZEFJRDIyMDAyNzdfU0VNX2VhM2NkYWExN2Y5MzFkNDE2NTkwYjgyMjdlMjk0ZjdmJTNhRyUzYXMlMjZlZl9pZCUzZGVhM2NkYWExN2Y5MzFkNDE2NTkwYjgyMjdlMjk0ZjdmJTNhRyUzYXMlMjZtc2Nsa2lkJTNkZWEzY2RhYTE3ZjkzMWQ0MTY1OTBiODIyN2UyOTRmN2Y&rlid=ea3cdaa17f931d416590b8227e294f7f&ntb=1). It runs locally and securely, performs AI inferencing at the Edge, and communicates with Azure services for security and updates. It includes [Defender for IoT](https://www.bing.com/ck/a?!&&p=4b4f5983a77f5d870170a12cd507a8d967bd32e10eab125544ac7aad1691be23JmltdHM9MTY1Mjc1MzE3OCZpZ3VpZD1mZmQyZGJiNi1iOWFlLTRiYjgtOTQ1MC1iM2FlNmQ1ZTBlNmUmaW5zaWQ9NTQ1Mg&ptn=3&fclid=f087fcb3-d585-11ec-b34a-9f80cb12a098&u=a1aHR0cHM6Ly9henVyZS5taWNyb3NvZnQuY29tL2VuLXVzL3NlcnZpY2VzL2lvdC1kZWZlbmRlci8&ntb=1) to provide a lightweight security agent that proactively monitors for security threats like botnets, brute force attempts, crypto miners, malware, and chatbots, that you can also integrate into your Azure Monitor infrastructure.

-### Azure Percept Windows Admin Center Extension (WAC)

-[Windows Admin Center (WAC)](https://www.microsoft.com/windows-server/windows-admin-center) is a locally deployed application accessed via your browser for managing Azure Stack HCI clusters, Windows Server, and more. Azure Percept on Azure Stack HCI is installed through a WAC extension that guides the user through configuring and deploying the Percept VM and related services. It creates a secure and performant AI video inferencing solution usable from the edge to the cloud.

-### Azure Percept Solution Development Paths

-Whether you're a beginner, an expert, or anywhere in between, from zero to low code, to creating or bringing your own models, Azure Percept has a solution development path for you to build your Edge artificial intelligence (AI) solution. Azure Percept has three solution development paths that you can use to build Edge AI solutions: Azure Percept Studio, Azure Percept for DeepStream, and Azure Percept Open-Source Project. You aren't limited to one path; you can choose any or all of them depending on your business needs. For more information about the solution development paths, visit [Azure Percept solution development paths overview](https://microsoft.sharepoint-df.com/:w:/t/AzurePerceptHCIDocumentation/EU92ZnNynDBGuVn3P5Xr5gcBFKS5HQguZm7O5sEENPUvPA?e=33T6Vi).

-#### *Azure Percept Studio*

-[Azure Percept Studio](/azure/azure-percept/studio/azure-percept-studio-overview) is a user-friendly portal for creating, deploying, and operating Edge artificial intelligence (AI) solutions. Using a low-code to no-code approach, you can discover and complete guided workflows and create an end-to-end Edge AI solution. This solution integrates Azure IoT and Azure AI cloud services like Azure IoT Hub, IoT Edge, Azure Storage, Log Analytics, and Spatial Analysis from Azure Cognitive Services.

-#### *Azure Percept for DeepStream*

-[Azure Percept for DeepStream](/azure/azure-percept/deepstream/azure-percept-for-deepstream-overview) includes developer tools that provide a custom developer experience. It enables you to create NVIDIA DeepStream containers using Microsoft-based images and guidance, supported models from NVIDIA out of the box, and/or bring your own models (BYOM). DeepStream is NVIDIAΓÇÖs toolkit to develop and deploy Vision AI applications and services. It provides multi-platform, scalable, Transport Layer Security (TLS)-encrypted security that can be deployed on-premises, on the edge, and in the cloud.

-#### *Azure Percept Open-Source Project*

-[Azure Percept Open-Source Project](/azure/azure-percept/open-source/azure-percept-open-source-project-overview) is a framework for creating, deploying, and operating Edge artificial intelligence (AI) solutions at scale with the control and flexibility of open-source natively on your environment. Azure Percept Open-Source Project is fully open-sourced and leverages the open-source software (OSS) community to deliver enhanced experiences. It's a self-managed solution where you host the environment in your own cluster.

-## Next steps

-Text to come.

-<!-- Before you start setting up your Azure Percept virtual machine (VM), we recommend the following articles:

-If youΓÇÖre ready to start setting up your Azure Percept virtual machine (VM), we recommend the following tutorial:

-description: An overview of the Azure Percept Open-Source project

-# Azure Percept Open-Source Project overview

-Azure Percept Open-Source Project is a framework for creating, deploying, and operating Edge artificial intelligence (AI) solutions at scale with the control and flexibility of open-source natively on your environment. It's fully open-sourced and leverages the open-source software (OSS) community to deliver enhanced experiences. And, as a self-managed solution, you can host the experience on your own Kubernetes clusters.

-Azure Percept Open-Source Project has a no- to low-code portal experience as well as APIs that can be used to build custom Edge AI applications. It supports running Edge AI apps by utilizing cameras and Edge devices with different Edge runtimes and accelerators across multiple locations at scale. Since it's designed with machine learning operations (MLOps) in mind, it provides support for active learning, continuous training, and data gathering using your machine learning (ML) models running at the edge.

-## Azure Percept Open-Source Project offers

- You can easily build camera-based Edge AI apps using first- and third-party ML models. In one seamless flow, you can leverage pre-built models from our partnerΓÇÖs Model Zoo and create your own ML models with Azure Custom Vision.

- Azure Percept Open-Source Project is Kubernetes native, so you can run the experience wherever Kubernetes runs; on-premises, hybrid, cloud, or multicloud environments. You can manage your experience using Kubernetes native tools such as Kubectl, our unique command line interface (CLI), and/or our no- to low-code native web portal. Edge AI apps and assets you create are projected and managed as Kubernetes objects, which allows you to rely on the Kubernetes control plane to manage the state of your Edge AI assets across many environments at scale.

- Azure Percept Open-Source Project is built on and supports popular industrial standards, protocols, and frameworks like Open Platform Communications Unified Architecture (OPC-UA), Open Network Video Interface Forum (ONVIF), OpenTelemetry, CloudEvents, Distributed Application Runtime (Dapr), Message Queuing Telemetry Transport (MQTT), Open Neural Network Exchange (ONNX), Akri, Kubectl, Helm, and many others.

- Even without any Edge hardware, you can get started with a few commands, then seamlessly transit from prototype/pilot to production at scale. Azure Percept Open-Source Project has an easy-to-use no- to low-code portal experience that allows developers to create and manage Edge AI solutions in minutes instead of days or months.

- Azure Percept Open-Source Project natively uses and supports Azure Edge and AI Services like Azure IoT Hub, Azure IoT Edge, Azure Cognitive Services, Azure Storage Server, Azure ML, and so on. At the same time, it also allows you to modify the experience for use cases that require the use of other services (Azure or non-Azure) or other Open-Source Software (OSS) tools.

-## Next steps

-Text to come.

-<!-- You're now ready to start using Azure Percept Open-Source Project. We recommend the following resources to get started.

-description: Description of Azure Percept Studio.

-# Azure Percept Studio overview

-Azure Percept Studio is a user-friendly portal for creating, deploying, and operating Edge artificial intelligence (AI) solutions. Using a low-code to no-code approach, you can discover and complete guided workflows and create an end-to-end Edge AI solution. This solution integrates Azure IoT and Azure AI cloud services like Azure IoT Hub, IoT Edge, Azure Storage, Log Analytics, and Spatial Analysis from Azure Cognitive Services.

-With Azure Percept Studio, you can connect your Edge AI compute devices and cameras and then configure and apply the pre-built AI skills included with Azure Precept Studio to automate and transform your operations at the edge. For example, you can use your cameras to count people in an area, detect when people cross a line, or when people enter/exit a restricted or secured area. You can then use AI skills to help you analyze this data in real-time so you can manage queues, space utilization, and occupancy, like a store entrance or exit, a curbside pickup area, or intruders on secure premises.

-## Azure Percept Studio offers:

- Whether you're a beginner or an advanced developer working on a pilot solution, Azure Percept Studio offers access to well-integrated workflows that you can use to reduce friction around building Edge AI solutions. You can create a pilot Edge AI solution in 10 minutes.

- Azure Spatial Analysis is fully integrated in Azure Percept. Spatial Analysis detects the presence and movements of people in real time video feed from IP cameras. There are three skills available around people understanding: people counting in an area, detecting when people cross a line, and detecting when people enter/ exit and area.

- Once your solution is created, you can operate your devices and solutions remotely, monitor multiple video streams, and create live inference telemetry. To optimize your operations at the Edge, you can then aggregate inference data over time and derive insights and trends that you can use in real time to create alerts that help you be proactive instead of reactive.

-## Next steps

-Text to come.

-<!-- If you havenΓÇÖt set up your Azure Percept on Azure Stack HCI, we recommend the following tutorial to start setting up your VM using Azure Percept Windows Admin Center Extension (WAC):

-If you have already set up your Azure Percept on Azure Stack HCI and are ready to start building your edge AI solution, we recommend the following tutorial:

-View definition is an optional artifact in Azure Managed Applications. It allows to customize overview page and add more views such as Metrics and Custom resources.

-The view definition artifact must be named **viewDefinition.json** and placed at the same level as **createUiDefinition.json** and **mainTemplate.json** in the .zip package that creates a managed application definition. To learn how to create the .zip package and publish a managed application definition, see [Publish an Azure Managed Application definition](publish-service-catalog-app.md)

-The **viewDefinition.json** file has only one top level `views` property, which is an array of views. Each view is shown in the managed application user interface as a separate menu item in the table of contents. Each view has a `kind` property that sets the type of the view. It must be set to one of the following values: [Overview](#overview), [Metrics](#metrics), [CustomResources](#custom-resources), [Associations](#associations). For more information, see current [JSON schema for viewDefinition.json](https://schema.management.azure.com/schemas/viewdefinition/0.0.1-preview/ViewDefinition.json#).

- "$schema": "https://schema.management.azure.com/schemas/viewdefinition/0.0.1-preview/ViewDefinition.json#",

- "contentVersion": "0.0.0.1",

- "views": [

- {

- "kind": "Overview",

- "properties": {

- "header": "Welcome to your Azure Managed Application",

- "description": "This managed application is for demo purposes only.",

- "commands": [

- {

- "displayName": "Test Action",

- "path": "testAction"

- }

- ]

- }

- },

- {

- "kind": "Metrics",

- "properties": {

- "displayName": "This is my metrics view",

- "version": "1.0.0",

- "charts": [

- {

- "displayName": "Sample chart",

- "chartType": "Bar",

- "metrics": [

- {

- "name": "Availability",

- "aggregationType": "avg",

- "resourceTagFilter": [ "tag1" ],

- "resourceType": "Microsoft.Storage/storageAccounts",

- "namespace": "Microsoft.Storage/storageAccounts"

- }

- ]

- }

- ]

- }

- },

- {

- "kind": "CustomResources",

- "properties": {

- "displayName": "Test custom resource type",

- "version": "1.0.0",

- "resourceType": "testCustomResource",

- "createUIDefinition": { },

- "commands": [

- {

- "displayName": "Custom Context Action",

- "path": "testCustomResource/testContextAction",

- "icon": "Stop",

- "createUIDefinition": { }

- }

- "columns": [

- {"key": "name", "displayName": "Name"},

- {"key": "properties.myProperty1", "displayName": "Property 1"},

- {"key": "properties.myProperty2", "displayName": "Property 2", "optional": true}

- ]

- }

- },

- {

- "kind": "Associations",

- "properties": {

- "displayName": "Test association resource type",

- "version": "1.0.0",

- "targetResourceType": "Microsoft.Compute/virtualMachines",

- "createUIDefinition": { }

- }

- }

- ]

-When you provide this view in **viewDefinition.json**, it overrides the default Overview page in your managed application.

- "kind": "Overview",

- "properties": {

- "header": "Welcome to your Azure Managed Application",

- "description": "This managed application is for demo purposes only.",

- "commands": [

- {

- "displayName": "Test Action",

- "path": "testAction"

- }

- ]

- }

-|commands|No|The array of additional toolbar buttons of the overview page, see [commands](#commands).|

-

- "kind": "Metrics",

- "properties": {

- "displayName": "This is my metrics view",

- "version": "1.0.0",

- "charts": [

- {

- "displayName": "Sample chart",

- "chartType": "Bar",

- "metrics": [

- {

- "name": "Availability",

- "aggregationType": "avg",

- "resourceTagFilter": [ "tag1" ],

- "resourceType": "Microsoft.Storage/storageAccounts",

- "namespace": "Microsoft.Storage/storageAccounts"

- }

- ]

- }

- }

-|namespace|No|Additional information to use when determining the correct metrics provider.|

-

-You can define multiple views of this type. Each view represents a **unique** custom resource type from the custom provider you defined in **mainTemplate.json**. For an introduction to custom providers, see [Azure Custom Providers Preview overview](../custom-providers/overview.md).

- "kind": "CustomResources",

- "properties": {

- "displayName": "Test custom resource type",

- "version": "1.0.0",

- "resourceType": "testCustomResource",

- "icon": "Polychromatic.ResourceList",

- "createUIDefinition": { },

- "commands": [

- {

- "displayName": "Custom Context Action",

- "path": "testCustomResource/testContextAction",

- "icon": "Stop",

- "createUIDefinition": { },

- }

- ],

- "columns": [

- {"key": "name", "displayName": "Name"},

- {"key": "properties.myProperty1", "displayName": "Property 1"},

- {"key": "properties.myProperty2", "displayName": "Property 2", "optional": true}

- ]

- }

-|displayName|Yes|The displayed title of the view. The title should be **unique** for each CustomResources view in your **viewDefinition.json**.|

-|commands|No|The array of additional toolbar buttons of the CustomResources view, see [commands](#commands).|

-

-Commands is an array of additional toolbar buttons that are displayed on page. Each command represents a POST action from your Azure Custom Provider defined in **mainTemplate.json**. For an introduction to custom providers, see [Azure Custom Providers overview](../custom-providers/overview.md).

- "commands": [

- {

- "displayName": "Start Test Action",

- "path": "testAction",

- "icon": "Start",

- "createUIDefinition": { }

- },

- ]

-|path|Yes|The custom provider action name. The action must be defined in **mainTemplate.json**.|

-You can define multiple views of this type. This view allows you to link existing resources to the managed application through the custom provider you defined in **mainTemplate.json**. For an introduction to custom providers, see [Azure Custom Providers Preview overview](../custom-providers/overview.md).

-In this view you can extend existing Azure resources based on the `targetResourceType`. When a resource is selected, it will create an onboarding request to the **public** custom provider, which can apply a side effect to the resource.

- "kind": "Associations",

- "properties": {

- "displayName": "Test association resource type",

- "version": "1.0.0",

- "targetResourceType": "Microsoft.Compute/virtualMachines",

- "createUIDefinition": { }

- }

-|displayName|Yes|The displayed title of the view. The title should be **unique** for each Associations view in your **viewDefinition.json**.|

-|targetResourceType|Yes|The target resource type. This is the resource type that will be displayed for resource onboarding.|

-> [!NOTE]

-> The trial account is not available on the Azure Government cloud.

-This article compares the capabilities of **Azure Video Indexer APIs** and **Media Services v3 APIs**.

-|Billing|[Media Services pricing](https://azure.microsoft.com/pricing/details/media-services/#analytics) |[Media Services pricing](https://azure.microsoft.com/pricing/details/media-services/#analytics) |

-|Free Trial|East US|Not available|

- Make sure the Media Services account was created with the classic APIs.

- :::image type="content" alt-text="Screenshot that shows how to use the classic API." source="./media/create-account/enable-classic-api.png":::

-* If you connect automatically, Azure Video Indexer sets the media **Reserved Units** to 10 S3 units:

- 

-* No manual content moderation available in Government cloud.

-* Bing description - in Gov cloud we won't present a description of celebrities and named entities identified. This is a UI capability only.

-This tutorial walks you through the steps of creating an Azure Video Indexer account and its accompanying resources by using the Azure portal. The created account is an Azure Resource Manager (ARM) based account (currently in preview). For information about different Azure Video Indexer account types, see the [Overview of account types](accounts-overview.md) topic.

-This getting started quickstart shows how to sign in to the Azure Video Indexer website and how to upload your first video.

-When creating an Azure Video Indexer account, you can choose a free trial account (where you get a certain number of free indexing minutes) or a paid option (where you aren't limited by the quota). With free trial, Azure Video Indexer provides up to 600 minutes of free indexing to website users and up to 2400 minutes of free indexing to API users. With paid option, you create an Azure Video Indexer account that is [connected to your Azure subscription and an Azure Media Services account](connect-to-azure.md). You pay for minutes indexed, for more information, see [Media Services pricing](https://azure.microsoft.com/pricing/details/media-services/).

-| **Vault credentials aren't valid** <br/> <br/> Vault credential files might be corrupt, might have expired, or they might have a different file extension than *.vaultCredentials*. (For example, they might have been downloaded more than 10 days before the time of registration.)| [Download new credentials](backup-azure-file-folder-backup-faq.yml#where-can-i-download-the-vault-credentials-file-) from the Recovery Services vault on the Azure portal. Then take these steps, as appropriate: <br><br>- If you've already installed and registered MARS, open the Microsoft Azure Backup Agent MMC console. Then select **Register Server** in the **Actions** pane to complete the registration with the new credentials. <br> - If the new installation fails, try reinstalling with the new credentials. <br><br> **Note**: If multiple vault credential files have been downloaded, only the latest file is valid for the next 10 days. We recommend that you download a new vault credential file. |

-For scenarios that require real-time transcription, we recommend using the [Speech SDK](speech-sdk.md). Currently, speech-to-text is available in [more than 20 languages](language-support.md), and the SDK is available in C++, C#, Java, Python, JavaScript, Objective-C, and Go. Samples are available in each language on [GitHub](https://github.com/Azure-Samples/cognitive-services-speech-sdk). For the latest news and updates, see [Release notes](releasenotes.md).

-If the language in the audio could change, use continuous [language identification](language-identification.md). Language identification is used to identify languages spoken in audio when compared against a list of [supported languages](language-support.md#language-identification). You provide up to 10 candidate languages, at least one of which is expected be in the audio. The Speech service returns the most likely language in the audio.

-Currently, conversation transcription supports [all speech-to-text languages](language-support.md#speech-to-text) in the following regions:ΓÇ»`centralus`, `eastasia`, `eastus`, `westeurope`.

-Based on the neural text-to-speech technology and the multilingual, multi-speaker, universal model, Custom Neural Voice lets you create synthetic voices that are rich in speaking styles, or adaptable cross languages. The realistic and natural sounding voice of Custom Neural Voice can represent brands, personify machines, and allow users to interact with applications conversationally. See the [supported languages](language-support.md#custom-neural-voice) for Custom Neural Voice.

-Out of the box, speech to text utilizes a Universal Language Model as a base model that is trained with Microsoft-owned data and reflects commonly used spoken language. The base model is pre-trained with dialects and phonetics representing a variety of common domains. When you make a speech recognition request, the most recent base model for each [supported language](language-support.md) is used by default. The base model works very well in most speech recognition scenarios.

-> Customization options vary by language/locale (see [Supported languages](./language-support.md)).

-You have easy access to a broad portfolio of [languages and voices](language-support.md#text-to-speech). These voices include state-of-the-art prebuilt neural voices and your custom neural voice, if you've built one.

-1. Choose the voice and the language for your script content. Audio Content Creation includes all of the [Microsoft text-to-speech voices](language-support.md#text-to-speech). You can use prebuilt neural voices or a custom neural voice.

-Custom Speech projects contain models, training and testing datasets, and deployment endpoints. Each project is specific to a [locale](language-support.md). For example, you might create a project for English in the United States.

-|Custom endpoint|Speech recognition requests will fall back to the most recent base model for the same [locale](language-support.md). You will get results, but recognition might not accurately transcribe your domain data. |Update the endpoint's model as described in the [Deploy a Custom Speech model](how-to-custom-speech-deploy-model.md) guide. |

-For a list of base models that support training with audio data, see [Language support](language-support.md#speech-to-text). Even if a base model does support training with audio data, the service might use only part of the audio. And it will still use all the transcripts.

-For a list of supported base models and locales for training with structured text, see [Language support](language-support.md#speech-to-text). You must use the latest base model for these locales. For locales that don't support training with structured text, the service will take any training sentences that don't reference any classes as part of training with plain-text data.

-|`@list`|A list of items that can be referenced in an example sentence.|Maximum of 10 lists. Maximum of 4,000 items per list.|

-|`#ExampleSentences`|A pound symbol (`#`) delimits a section of example sentences. The section heading can only contain letters, digits, and underscores. Example sentences should reflect the range of speech that your model should expect. A training sentence can refer to items under a `@list` by using surrounding left and right curly braces (`{@list name}`). You can refer to multiple lists in the same training sentence, or none at all.|Maximum of 50,000 example sentences|

-You can provide a custom pronunciation file to improve recognition. Don't use custom pronunciation files to alter the pronunciation of common words. For a list of languages that support custom pronunciation, see [language support](language-support.md#speech-to-text).

-Not all base models support [training with audio data](language-support.md#speech-to-text). For a list of base models that support training with audio data, see [Language support](language-support.md#speech-to-text).

- You can also select **Neural - cross lingual** and **Target language** to create a secondary language for your voice model. Only one target language can be selected for a voice model. You don't need to prepare additional data in the target language for training, but your test script needs to be in the target language. For the languages supported by cross lingual feature, see [supported languages](language-support.md#custom-neural-voice).

-[Custom Neural Voice](https://aka.ms/customvoice) is a set of online tools that you use to create a recognizable, one-of-a-kind voice for your brand. All it takes to get started are a handful of audio files and the associated transcriptions. See if Custom Neural Voice supports your [language](language-support.md#custom-neural-voice) and [region](regions.md#speech-service).

-With cross lingual feature (public preview), you can create a different language for your voice model. If the language of your training data is supported by cross lingual feature, you can create a voice that speaks a different language from your training data. For example, with the `zh-CN` training data, you can create a voice that speaks `en-US` or any of the languages supported by cross lingual feature. For details, see [supported languages](language-support.md#custom-neural-voice). You don't need to prepare additional data in the target language for training, but your test script needs to be in the target language.

-> We are retiring the standard voices from September 1, 2021 through August 31, 2024. If you used a standard voice with your Speech resource prior to September 1, 2021 then you can continue to do so until August 31, 2024. All other Speech resources can only use prebuilt neural voices. You can choose from the supported [neural voice names](language-support.md#prebuilt-neural-voices). After August 31, the standard voices won't be supported with any Speech resource.

-> For information about availability of pronunciation assessment, see [supported languages](language-support.md#pronunciation-assessment) and [available regions](regions.md#speech-service).

-The phoneme name is provided together with the score, to help identity which phonemes were pronounced accurately or inaccurately. For the [supported languages](language-support.md#pronunciation-assessment), you can get the phoneme name in [SAPI](/previous-versions/windows/desktop/ee431828(v=vs.85)#american-english-phoneme-table) format, and for the `en-US` locale, you can also get the phoneme name in [IPA](https://en.wikipedia.org/wiki/IPA) format.

-By default, LUIS recognizes intents in US English (`en-us`). By assigning a locale code to the `SpeechRecognitionLanguage` property of the speech configuration, you can recognize intents in other languages. For example, add `config.SpeechRecognitionLanguage = "de-de";` in our application before creating the recognizer to recognize intents in German. For more information, see [LUIS language support](../LUIS/luis-language-support.md#languages-supported).

-> Viseme ID supports neural voices in [all viseme-supported locales](language-support.md#viseme). Scalable Vector Graphics (SVG) only supports neural voices in `en-US` locale, and blend shapes supports neural voices in `en-US` and `zh-CN` locales.

-> The examples below are in English but the guidelines apply to all languages supported by Custom Keyword. For a list of all supported languages, see [Language support](language-support.md#custom-keyword-and-keyword-verification).

-Language identification is used to identify languages spoken in audio when compared against a list of [supported languages](language-support.md#language-identification).

-For more information, see [supported languages](language-support.md#language-identification).

-Language support varies by Speech service functionality. The following tables summarize language support for [speech-to-text](#speech-to-text), [text-to-speech](#text-to-speech), [speech translation](#speech-translation), and [speaker recognition](#speaker-recognition) service offerings.

-## Speech-to-text

-The Speech service supports the languages (locales) in the following tables.

-To improve accuracy, customization is available for some languages and base model versions by uploading audio + human-labeled transcripts, plain text, structured text, and pronunciation. By default, plain text customization is supported for all available base models. To learn more about customization, see [Custom Speech](./custom-speech-overview.md).

-### [Speech-to-text](#tab/speechtotext)

-| Language | Locale (BCP-47) |

-|--|--|

-| Afrikaans (South Africa) | `af-ZA` |

-| Albanian (Albania) | `sq-AL` |

-| Amharic (Ethiopia) | `am-ET` |

-| Arabic (Algeria) | `ar-DZ` |

-| Arabic (Bahrain), modern standard | `ar-BH` |

-| Arabic (Egypt) | `ar-EG` |

-| Arabic (Iraq) | `ar-IQ` |

-| Arabic (Israel) | `ar-IL` |

-| Arabic (Jordan) | `ar-JO` |

-| Arabic (Kuwait) | `ar-KW` |

-| Arabic (Lebanon) | `ar-LB` |

-| Arabic (Libya) | `ar-LY` |

-| Arabic (Morocco) | `ar-MA` |

-| Arabic (Oman) | `ar-OM` |

-| Arabic (Palestinian Authority) | `ar-PS` |

-| Arabic (Qatar) | `ar-QA` |

-| Arabic (Saudi Arabia) | `ar-SA` |

-| Arabic (Syria) | `ar-SY` |

-| Arabic (Tunisia) | `ar-TN` |

-| Arabic (United Arab Emirates) | `ar-AE` |

-| Arabic (Yemen) | `ar-YE` |

-| Armenian (Armenia) | `hy-AM` |

-| Azerbaijani (Azerbaijan) | `az-AZ` |

-| Basque (Spain) | `eu-ES` |

-| Bengali (India) | `bn-IN` |

-| Bosnian (Bosnia and Herzegovina) | `bs-BA` |

-| Bulgarian (Bulgaria) | `bg-BG` |

-| Burmese (Myanmar) | `my-MM` |

-| Catalan (Spain) | `ca-ES` |

-| Chinese (Cantonese, Simplified) | `yue-CN` |

-| Chinese (Cantonese, Traditional) | `zh-HK` |

-| Chinese (Mandarin, Simplified) | `zh-CN` |

-| Chinese (Southwestern Mandarin, Simplified) | `zh-CN-sichuan` |

-| Chinese (Taiwanese Mandarin, Traditional) | `zh-TW` |

-| Chinese (Wu, Simplified) | `wuu-CN` |

-| Croatian (Croatia) | `hr-HR` |

-| Czech (Czech) | `cs-CZ` |

-| Danish (Denmark) | `da-DK` |

-| Dutch (Belgium) | `nl-BE` |

-| Dutch (Netherlands) | `nl-NL` |

-| English (Australia) | `en-AU` |

-| English (Canada) | `en-CA` |

-| English (Ghana) | `en-GH` |

-| English (Hong Kong) | `en-HK` |

-| English (India) | `en-IN` |

-| English (Ireland) | `en-IE` |

-| English (Kenya) | `en-KE` |

-| English (New Zealand) | `en-NZ` |

-| English (Nigeria) | `en-NG` |

-| English (Philippines) | `en-PH` |

-| English (Singapore) | `en-SG` |

-| English (South Africa) | `en-ZA` |

-| English (Tanzania) | `en-TZ` |

-| English (United Kingdom) | `en-GB` |

-| English (United States) | `en-US` |

-| Estonian (Estonia) | `et-EE` |

-| Filipino (Philippines) | `fil-PH` |

-| Finnish (Finland) | `fi-FI` |

-| French (Belgium) | `fr-BE` |

-| French (Canada) | `fr-CA` |

-| French (France) | `fr-FR` |

-| French (Switzerland) | `fr-CH` |

-| Galician (Spain) | `gl-ES` |

-| Georgian (Georgia) | `ka-GE` |

-| German (Austria) | `de-AT` |

-| German (Germany) | `de-DE` |

-| German (Switzerland) | `de-CH` |

-| Greek (Greece) | `el-GR` |

-| Gujarati (Indian) | `gu-IN` |

-| Hebrew (Israel) | `he-IL` |

-| Hindi (India) | `hi-IN` |

-| Hungarian (Hungary) | `hu-HU` |

-| Icelandic (Iceland) | `is-IS` |

-| Indonesian (Indonesia) | `id-ID` |

-| Irish (Ireland) | `ga-IE` |

-| Italian (Italy) | `it-IT` |

-| Italian (Switzerland) | `it-CH` |

-| Japanese (Japan) | `ja-JP` |

-| Javanese (Indonesia) | `jv-ID` |

-| Kannada (India) | `kn-IN` |

-| Kazakh (Kazakhstan) | `kk-KZ` |

-| Khmer (Cambodia) | `km-KH` |

-| Korean (Korea) | `ko-KR` |

-| Lao (Laos) | `lo-LA` |

-| Latvian (Latvia) | `lv-LV` |

-| Lithuanian (Lithuania) | `lt-LT` |

-| Macedonian (North Macedonia) | `mk-MK` |

-| Malay (Malaysia) | `ms-MY` |

-| Maltese (Malta) | `mt-MT` |

-| Marathi (India) | `mr-IN` |

-| Mongolian (Mongolia) | `mn-MN` |

-| Nepali (Nepal) | `ne-NP` |

-| Norwegian (Bokmål, Norway) | `nb-NO` |

-| Pashto (Afghanistan) | `ps-AF` |

-| Persian (Iran) | `fa-IR` |

-| Polish (Poland) | `pl-PL` |

-| Portuguese (Brazil) | `pt-BR` |

-| Portuguese (Portugal) | `pt-PT` |

-| Romanian (Romania) | `ro-RO` |

-| Russian (Russia) | `ru-RU` |

-| Serbian (Serbia) | `sr-RS` |

-| Sinhala (Sri Lanka) | `si-LK` |

-| Slovak (Slovakia) | `sk-SK` |

-| Slovenian (Slovenia) | `sl-SI` |

-| Somali (Somalia) | `so-SO` |

-| Spanish (Argentina) | `es-AR` |

-| Spanish (Bolivia) | `es-BO` |

-| Spanish (Chile) | `es-CL` |

-| Spanish (Colombia) | `es-CO` |

-| Spanish (Costa Rica) | `es-CR` |

-| Spanish (Cuba) | `es-CU` |

-| Spanish (Dominican Republic) | `es-DO` |

-| Spanish (Ecuador) | `es-EC` |

-| Spanish (El Salvador) | `es-SV` |

-| Spanish (Equatorial Guinea) | `es-GQ` |

-| Spanish (Guatemala) | `es-GT` |

-| Spanish (Honduras) | `es-HN` |

-| Spanish (Mexico) | `es-MX` |

-| Spanish (Nicaragua) | `es-NI` |

-| Spanish (Panama) | `es-PA` |

-| Spanish (Paraguay) | `es-PY` |

-| Spanish (Peru) | `es-PE` |

-| Spanish (Puerto Rico) | `es-PR` |

-| Spanish (Spain) | `es-ES` |

-| Spanish (Uruguay) | `es-UY` |

-| Spanish (USA) | `es-US` |

-| Spanish (Venezuela) | `es-VE` |

-| Swahili (Kenya) | `sw-KE` |

-| Swahili (Tanzania) | `sw-TZ` |

-| Swedish (Sweden) | `sv-SE` |

-| Tamil (India) | `ta-IN` |

-| Telugu (India) | `te-IN` |

-| Thai (Thailand) | `th-TH` |

-| Turkish (Turkey) | `tr-TR` |

-| Ukrainian (Ukraine) | `uk-UA` |

-| Uzbek (Uzbekistan) | `uz-UZ` |

-| Vietnamese (Vietnam) | `vi-VN` |

-| Welsh (United Kingdom) | `cy-GB` |

-| Zulu (South Africa) | `zu-ZA` |

-### [Plain text](#tab/plaintext)

-| Language | Locale (BCP-47) |

-|--|--|

-| Afrikaans (South Africa) | `af-ZA` |

-| Amharic (Ethiopia) | `am-ET` |

-| Arabic (Algeria) | `ar-DZ` |

-| Arabic (Bahrain), modern standard | `ar-BH` |

-| Arabic (Egypt) | `ar-EG` |

-| Arabic (Iraq) | `ar-IQ` |

-| Arabic (Israel) | `ar-IL` |

-| Arabic (Jordan) | `ar-JO` |

-| Arabic (Kuwait) | `ar-KW` |

-| Arabic (Lebanon) | `ar-LB` |

-| Arabic (Libya) | `ar-LY` |

-| Arabic (Morocco) | `ar-MA` |

-| Arabic (Oman) | `ar-OM` |

-| Arabic (Palestinian Authority) | `ar-PS` |

-| Arabic (Qatar) | `ar-QA` |

-| Arabic (Saudi Arabia) | `ar-SA` |

-| Arabic (Syria) | `ar-SY` |

-| Arabic (Tunisia) | `ar-TN` |

-| Arabic (United Arab Emirates) | `ar-AE` |

-| Arabic (Yemen) | `ar-YE` |

-| Bulgarian (Bulgaria) | `bg-BG` |

-| Burmese (Myanmar) | `my-MM` |

-| Catalan (Spain) | `ca-ES` |

-| Chinese (Cantonese, Traditional) | `zh-HK` |

-| Chinese (Mandarin, Simplified) | `zh-CN` |

-| Chinese (Taiwanese Mandarin) | `zh-TW` |

-| Croatian (Croatia) | `hr-HR` |

-| Czech (Czech) | `cs-CZ` |

-| Danish (Denmark) | `da-DK` |

-| Dutch (Belgium) | `nl-BE` |

-| Dutch (Netherlands) | `nl-NL` |

-| English (Australia) | `en-AU` |

-| English (Canada) | `en-CA` |

-| English (Ghana) | `en-GH` |

-| English (Hong Kong) | `en-HK` |

-| English (India) | `en-IN` |

-| English (Ireland) | `en-IE` |

-| English (Kenya) | `en-KE` |

-| English (New Zealand) | `en-NZ` |

-| English (Nigeria) | `en-NG` |

-| English (Philippines) | `en-PH` |

-| English (Singapore) | `en-SG` |

-| English (South Africa) | `en-ZA` |

-| English (Tanzania) | `en-TZ` |

-| English (United Kingdom) | `en-GB` |

-| English (United States) | `en-US` |

-| Estonian (Estonia) | `et-EE` |

-| Filipino (Philippines) | `fil-PH` |

-| Finnish (Finland) | `fi-FI` |

-| French (Belgium) | `fr-BE` |

-| French (Canada) | `fr-CA` |

-| French (France) | `fr-FR` |

-| French (Switzerland) | `fr-CH` |

-| German (Austria) | `de-AT` |

-| German (Germany) | `de-DE` |

-| German (Switzerland) | `de-CH` |

-| Greek (Greece) | `el-GR` |

-| Gujarati (Indian) | `gu-IN` |

-| Hebrew (Israel) | `he-IL` |

-| Hindi (India) | `hi-IN` |

-| Hungarian (Hungary) | `hu-HU` |

-| Icelandic (Iceland) | `is-IS` |

-| Indonesian (Indonesia) | `id-ID` |

-| Irish (Ireland) | `ga-IE` |

-| Italian (Italy) | `it-IT` |

-| Japanese (Japan) | `ja-JP` |

-| Javanese (Indonesia) | `jv-ID` |

-| Kannada (India) | `kn-IN` |

-| Khmer (Cambodia) | `km-KH` |

-| Korean (Korea) | `ko-KR` |

-| Lao (Laos) | `lo-LA` |

-| Latvian (Latvia) | `lv-LV` |

-| Lithuanian (Lithuania) | `lt-LT` |

-| Macedonian (North Macedonia) | `mk-MK` |

-| Malay (Malaysia) | `ms-MY` |

-| Maltese (Malta) | `mt-MT` |

-| Marathi (India) | `mr-IN` |

-| Norwegian (Bokmål, Norway) | `nb-NO` |

-| Persian (Iran) | `fa-IR` |

-| Polish (Poland) | `pl-PL` |

-| Portuguese (Brazil) | `pt-BR` |

-| Portuguese (Portugal) | `pt-PT` |

-| Romanian (Romania) | `ro-RO` |

-| Russian (Russia) | `ru-RU` |

-| Serbian (Serbia) | `sr-RS` |

-| Sinhala (Sri Lanka) | `si-LK` |

-| Slovak (Slovakia) | `sk-SK` |

-| Slovenian (Slovenia) | `sl-SI` |

-| Spanish (Argentina) | `es-AR` |

-| Spanish (Bolivia) | `es-BO` |

-| Spanish (Chile) | `es-CL` |

-| Spanish (Colombia) | `es-CO` |

-| Spanish (Costa Rica) | `es-CR` |

-| Spanish (Cuba) | `es-CU` |

-| Spanish (Dominican Republic) | `es-DO` |

-| Spanish (Ecuador) | `es-EC` |

-| Spanish (El Salvador) | `es-SV` |

-| Spanish (Equatorial Guinea) | `es-GQ` |

-| Spanish (Guatemala) | `es-GT` |

-| Spanish (Honduras) | `es-HN` |

-| Spanish (Mexico) | `es-MX` |

-| Spanish (Nicaragua) | `es-NI` |

-| Spanish (Panama) | `es-PA` |

-| Spanish (Paraguay) | `es-PY` |

-| Spanish (Peru) | `es-PE` |

-| Spanish (Puerto Rico) | `es-PR` |

-| Spanish (Spain) | `es-ES` |

-| Spanish (Uruguay) | `es-UY` |

-| Spanish (USA) | `es-US` |

-| Spanish (Venezuela) | `es-VE` |

-| Swahili (Kenya) | `sw-KE` |

-| Swahili (Tanzania) | `sw-TZ` |

-| Swedish (Sweden) | `sv-SE` |

-| Tamil (India) | `ta-IN` |

-| Telugu (India) | `te-IN` |

-| Thai (Thailand) | `th-TH` |

-| Turkish (Turkey) | `tr-TR` |

-| Ukrainian (Ukraine) | `uk-UA` |

-| Uzbek (Uzbekistan) | `uz-UZ` |

-| Vietnamese (Vietnam) | `vi-VN` |

-| Zulu (South Africa) | `zu-ZA` |

-### [Structured text](#tab/structuredtext)

-| Language | Locale (BCP-47) |

-|--|--|

-| English (India) | `en-IN` |

-| English (United Kingdom) | `en-GB` |

-| English (United States) | `en-US` |

-| French (Canada) | `fr-CA` |

-| French (France) | `fr-FR` |

-| German (Switzerland) | `de-CH` |

-| Spanish (Mexico) | `es-MX` |

-| Spanish (Spain) | `es-ES` |

-### [Pronunciation data](#tab/pronunciation)

-| Language | Locale (BCP-47) |

-|--|--|

-| Catalan (Spain) | `ca-ES` |

-| Croatian (Croatia) | `hr-HR` |

-| Czech (Czech) | `cs-CZ` |

-| Danish (Denmark) | `da-DK` |

-| Dutch (Netherlands) | `nl-NL` |

-| English (Australia) | `en-AU` |

-| English (Canada) | `en-CA` |

-| English (Ghana) | `en-GH` |

-| English (Hong Kong) | `en-HK` |

-| English (India) | `en-IN` |

-| English (Ireland) | `en-IE` |

-| English (Kenya) | `en-KE` |

-| English (New Zealand) | `en-NZ` |

-| English (Nigeria) | `en-NG` |

-| English (Philippines) | `en-PH` |

-| English (Singapore) | `en-SG` |

-| English (South Africa) | `en-ZA` |

-| English (Tanzania) | `en-TZ` |

-| English (United Kingdom) | `en-GB` |

-| English (United States) | `en-US` |

-| Estonian (Estonia) | `et-EE` |

-| Filipino (Philippines) | `fil-PH` |

-| Finnish (Finland) | `fi-FI` |

-| French (Canada) | `fr-CA` |

-| French (France) | `fr-FR` |

-| French (Switzerland) | `fr-CH` |

-| German (Austria) | `de-AT` |

-| German (Germany) | `de-DE` |

-| German (Switzerland) | `de-CH` |

-| Hungarian (Hungary) | `hu-HU` |

-| Indonesian (Indonesia) | `id-ID` |

-| Irish (Ireland) | `ga-IE` |

-| Italian (Italy) | `it-IT` |

-| Latvian (Latvia) | `lv-LV` |

-| Lithuanian (Lithuania) | `lt-LT` |

-| Polish (Poland) | `pl-PL` |

-| Portuguese (Brazil) | `pt-BR` |

-| Portuguese (Portugal) | `pt-PT` |

-| Romanian (Romania) | `ro-RO` |

-| Slovak (Slovakia) | `sk-SK` |

-| Slovenian (Slovenia) | `sl-SI` |

-| Spanish (Argentina) | `es-AR` |

-| Spanish (Bolivia) | `es-BO` |

-| Spanish (Chile) | `es-CL` |

-| Spanish (Colombia) | `es-CO` |

-| Spanish (Costa Rica) | `es-CR` |

-| Spanish (Cuba) | `es-CU` |

-| Spanish (Dominican Republic) | `es-DO` |

-| Spanish (Ecuador) | `es-EC` |

-| Spanish (El Salvador) | `es-SV` |

-| Spanish (Guatemala) | `es-GT` |

-| Spanish (Honduras) | `es-HN` |

-| Spanish (Mexico) | `es-MX` |

-| Spanish (Nicaragua) | `es-NI` |

-| Spanish (Panama) | `es-PA` |

-| Spanish (Paraguay) | `es-PY` |

-| Spanish (Peru) | `es-PE` |

-| Spanish (Puerto Rico) | `es-PR` |

-| Spanish (Spain) | `es-ES` |

-| Spanish (Uruguay) | `es-UY` |

-| Spanish (USA) | `es-US` |

-| Spanish (Venezuela) | `es-VE` |

-| Swedish (Sweden) | `sv-SE` |

-### [Audio data](#tab/audiodata)

-| Language | Locale (BCP-47) |

-|--|--|

-| English (United Kingdom) | `en-GB` |

-| English (United States) | `en-US` |

-| French (Canada) | `fr-CA` |

-| French (France) | `fr-FR` |

-| German (Switzerland) | `de-CH` |

-| Italian (Italy) | `it-IT` |

-| Korean (Korea) | `ko-KR` |

-| Portuguese (Brazil) | `pt-BR` |

-| Spanish (Spain) | `es-ES` |

-### [Phrase list](#tab/phraselist)

-You can use the locales in this table with [phrase list](improve-accuracy-phrase-list.md).

-| Language | Locale |

-|||

-| Chinese (Mandarin, Simplified) | `zh-CN` |

-| English (Australia) | `en-AU` |

-| English (Canada) | `en-CA` |

-| English (India) | `en-IN` |

-| English (United Kingdom)) | `en-GB` |

-| English (United States) | `en-US` |

-| French (Canada) | `fr-CA` |

-| French (France) | `fr-FR` |

-| German (Germany) | `de-DE` |

-| Italian (Italy) | `it-IT` |

-| Japanese (Japan) | `ja-JP` |

-| Korean (Korea) | `ko-KR` |

-| Portuguese (Brazil) | `pt-BR` |

-| Spanish (Mexico) | `es-MX` |

-| Spanish (Spain) | `es-ES` |

-## Text-to-speech

-Both the Microsoft Speech SDK and REST APIs support these neural voices, each of which supports a specific language and dialect, identified by locale. You can try the demo and hear the voices on [this website](https://azure.microsoft.com/services/cognitive-services/text-to-speech/#features).

-You can also get a full list of languages and voices supported for each specific region or endpoint through the [voices list API](rest-text-to-speech.md#get-a-list-of-voices). To learn how you can configure and adjust neural voices, such as Speaking Styles, see [Speech Synthesis Markup Language](speech-synthesis-markup.md#adjust-speaking-styles).

-> [!IMPORTANT]

-> Pricing varies for Prebuilt Neural Voice (referred to as *Neural* on the pricing page) and Custom Neural Voice (referred to as *Custom Neural* on the pricing page). For more information, see the [Pricing](https://azure.microsoft.com/pricing/details/cognitive-services/speech-services/) page.

-Prebuilt neural voices are created from samples that use a 24-khz sample rate. All voices can upsample or downsample to other sample rates when synthesizing.

-> The English (United Kingdom) voice `en-GB-MiaNeural` retired on October 30, 2021. All service requests to `en-GB-MiaNeural` will be redirected to `en-GB-SoniaNeural` automatically as of October 30, 2021.

->

-> If you're using container Neural TTS, [download](speech-container-howto.md#get-the-container-image-with-docker-pull) and deploy the latest version. Starting from October 30, 2021, all requests with previous versions will not succeed.

->

-> The `en-US-JessaNeural` voice has changed to `en-US-AriaNeural`. If you were using "Jessa" before, convert to "Aria." You can continue to use the full service name mapping like "Microsoft Server Speech Text to Speech Voice (en-US, AriaNeural)" in your speech synthesis requests.

-The following table lists the prebuilt neural voices supported in each language.

-| Language | Locale | Gender | Voice name | Style support |

-||||||

-| Afrikaans (South Africa) | `af-ZA` | Female | `af-ZA-AdriNeural` | General |

-| Afrikaans (South Africa) | `af-ZA` | Male | `af-ZA-WillemNeural` | General |

-| Albanian (Albania) | `sq-AL` | Female | `sq-AL-AnilaNeural` ^New | General |

-| Albanian (Albania) | `sq-AL` | Male | `sq-AL-IlirNeural` ^New | General |

-| Amharic (Ethiopia) | `am-ET` | Female | `am-ET-MekdesNeural` | General |

-| Amharic (Ethiopia) | `am-ET` | Male | `am-ET-AmehaNeural` | General |

-| Arabic (Algeria) | `ar-DZ` | Female | `ar-DZ-AminaNeural` | General |

-| Arabic (Algeria) | `ar-DZ` | Male | `ar-DZ-IsmaelNeural` | General |

-| Arabic (Bahrain) | `ar-BH` | Female | `ar-BH-LailaNeural` | General |

-| Arabic (Bahrain) | `ar-BH` | Male | `ar-BH-AliNeural` | General |

-| Arabic (Egypt) | `ar-EG` | Female | `ar-EG-SalmaNeural` | General |

-| Arabic (Egypt) | `ar-EG` | Male | `ar-EG-ShakirNeural` | General |

-| Arabic (Iraq) | `ar-IQ` | Female | `ar-IQ-RanaNeural` | General |

-| Arabic (Iraq) | `ar-IQ` | Male | `ar-IQ-BasselNeural` | General |

-| Arabic (Jordan) | `ar-JO` | Female | `ar-JO-SanaNeural` | General |

-| Arabic (Jordan) | `ar-JO` | Male | `ar-JO-TaimNeural` | General |

-| Arabic (Kuwait) | `ar-KW` | Female | `ar-KW-NouraNeural` | General |

-| Arabic (Kuwait) | `ar-KW` | Male | `ar-KW-FahedNeural` | General |

-| Arabic (Lebanon) | `ar-LB` | Female | `ar-LB-LaylaNeural` ^New | General |

-| Arabic (Lebanon) | `ar-LB` | Male | `ar-LB-RamiNeural` ^New | General |

-| Arabic (Libya) | `ar-LY` | Female | `ar-LY-ImanNeural` | General |

-| Arabic (Libya) | `ar-LY` | Male | `ar-LY-OmarNeural` | General |

-| Arabic (Morocco) | `ar-MA` | Female | `ar-MA-MounaNeural` | General |

-| Arabic (Morocco) | `ar-MA` | Male | `ar-MA-JamalNeural` | General |

-| Arabic (Oman) | `ar-OM` | Female | `ar-OM-AyshaNeural` ^New | General |

-| Arabic (Oman) | `ar-OM` | Male | `ar-OM-AbdullahNeural` ^New | General |

-| Arabic (Qatar) | `ar-QA` | Female | `ar-QA-AmalNeural` | General |

-| Arabic (Qatar) | `ar-QA` | Male | `ar-QA-MoazNeural` | General |

-| Arabic (Saudi Arabia) | `ar-SA` | Female | `ar-SA-ZariyahNeural` | General |

-| Arabic (Saudi Arabia) | `ar-SA` | Male | `ar-SA-HamedNeural` | General |

-| Arabic (Syria) | `ar-SY` | Female | `ar-SY-AmanyNeural` | General |

-| Arabic (Syria) | `ar-SY` | Male | `ar-SY-LaithNeural` | General |

-| Arabic (Tunisia) | `ar-TN` | Female | `ar-TN-ReemNeural` | General |

-| Arabic (Tunisia) | `ar-TN` | Male | `ar-TN-HediNeural` | General |

-| Arabic (United Arab Emirates) | `ar-AE` | Female | `ar-AE-FatimaNeural` | General |

-| Arabic (United Arab Emirates) | `ar-AE` | Male | `ar-AE-HamdanNeural` | General |

-| Arabic (Yemen) | `ar-YE` | Female | `ar-YE-MaryamNeural` | General |

-| Arabic (Yemen) | `ar-YE` | Male | `ar-YE-SalehNeural` | General |

-| Azerbaijani (Azerbaijan) | `az-AZ` | Male | `az-AZ-BabekNeural` ^New | General |

-| Azerbaijani (Azerbaijan) | `az-AZ` | Female | `az-AZ-BanuNeural` ^New | General |

-| Bangla (Bangladesh) | `bn-BD` | Female | `bn-BD-NabanitaNeural` | General |

-| Bangla (Bangladesh) | `bn-BD` | Male | `bn-BD-PradeepNeural` | General |

-| Bengali (India) | `bn-IN` | Female | `bn-IN-TanishaaNeural` | General |

-| Bengali (India) | `bn-IN` | Male | `bn-IN-BashkarNeural` | General |

-| Bosnian (Bosnia and Herzegovina) | `bs-BA` | Female | `bs-BA-VesnaNeural` ^New | General |

-| Bosnian (Bosnia and Herzegovina) | `bs-BA` | Male | `bs-BA-GoranNeural` ^New | General |

-| Bulgarian (Bulgaria) | `bg-BG` | Female | `bg-BG-KalinaNeural` | General |

-| Bulgarian (Bulgaria) | `bg-BG` | Male | `bg-BG-BorislavNeural` | General |

-| Burmese (Myanmar) | `my-MM` | Female | `my-MM-NilarNeural` | General |

-| Burmese (Myanmar) | `my-MM` | Male | `my-MM-ThihaNeural` | General |

-| Catalan (Spain) | `ca-ES` | Female | `ca-ES-AlbaNeural` | General |

-| Catalan (Spain) | `ca-ES` | Female | `ca-ES-JoanaNeural` | General |

-| Catalan (Spain) | `ca-ES` | Male | `ca-ES-EnricNeural` | General |

-| Chinese (Cantonese, Traditional) | `zh-HK` | Female | `zh-HK-HiuGaaiNeural` | General |

-| Chinese (Cantonese, Traditional) | `zh-HK` | Female | `zh-HK-HiuMaanNeural` | General |

-| Chinese (Cantonese, Traditional) | `zh-HK` | Male | `zh-HK-WanLungNeural` | General |

-| Chinese (Mandarin, Simplified) | `zh-CN` | Female | `zh-CN-XiaochenNeural` | Optimized for spontaneous conversation |

-| Chinese (Mandarin, Simplified) | `zh-CN` | Female | `zh-CN-XiaohanNeural` | General, multiple styles available [using SSML](speech-synthesis-markup.md#adjust-speaking-styles) |

-| Chinese (Mandarin, Simplified) | `zh-CN` | Female | `zh-CN-XiaomoNeural` | General, multiple role-play and styles available [using SSML](speech-synthesis-markup.md#adjust-speaking-styles) |

-| Chinese (Mandarin, Simplified) | `zh-CN` | Female | `zh-CN-XiaoqiuNeural` | Optimized for narrating |

-| Chinese (Mandarin, Simplified) | `zh-CN` | Female | `zh-CN-XiaoruiNeural` | Senior voice, multiple styles available [using SSML](speech-synthesis-markup.md#adjust-speaking-styles) |

-| Chinese (Mandarin, Simplified) | `zh-CN` | Female | `zh-CN-XiaoshuangNeural` | Child voice, optimized for child story and chat; multiple voice styles available [using SSML](speech-synthesis-markup.md#adjust-speaking-styles)|

-| Chinese (Mandarin, Simplified) | `zh-CN` | Female | `zh-CN-XiaoxiaoNeural` | General, multiple voice styles available [using SSML](speech-synthesis-markup.md#adjust-speaking-styles) |

-| Chinese (Mandarin, Simplified) | `zh-CN` | Female | `zh-CN-XiaoxuanNeural` | General, multiple role-play and styles available [using SSML](speech-synthesis-markup.md#adjust-speaking-styles) |

-| Chinese (Mandarin, Simplified) | `zh-CN` | Female | `zh-CN-XiaoyanNeural` | Optimized for customer service |

-| Chinese (Mandarin, Simplified) | `zh-CN` | Female | `zh-CN-XiaoyouNeural` | Child voice, optimized for story narrating |

-| Chinese (Mandarin, Simplified) | `zh-CN` | Male | `zh-CN-YunxiNeural` | General, multiple styles available [using SSML](speech-synthesis-markup.md#adjust-speaking-styles) |

-| Chinese (Mandarin, Simplified) | `zh-CN` | Male | `zh-CN-YunyangNeural` | Optimized for news reading,<br /> multiple voice styles available [using SSML](speech-synthesis-markup.md#adjust-speaking-styles) |

-| Chinese (Mandarin, Simplified) | `zh-CN` | Male | `zh-CN-YunyeNeural` | Optimized for story narrating, multiple role-play and styles available [using SSML](speech-synthesis-markup.md#adjust-speaking-styles) |

-| Chinese (Taiwanese Mandarin) | `zh-TW` | Female | `zh-TW-HsiaoChenNeural` | General |

-| Chinese (Taiwanese Mandarin) | `zh-TW` | Female | `zh-TW-HsiaoYuNeural` | General |

-| Chinese (Taiwanese Mandarin) | `zh-TW` | Male | `zh-TW-YunJheNeural` | General |

-| Croatian (Croatia) | `hr-HR` | Female | `hr-HR-GabrijelaNeural` | General |

-| Croatian (Croatia) | `hr-HR` | Male | `hr-HR-SreckoNeural` | General |

-| Czech (Czech) | `cs-CZ` | Female | `cs-CZ-VlastaNeural` | General |

-| Czech (Czech) | `cs-CZ` | Male | `cs-CZ-AntoninNeural` | General |

-| Danish (Denmark) | `da-DK` | Female | `da-DK-ChristelNeural` | General |

-| Danish (Denmark) | `da-DK` | Male | `da-DK-JeppeNeural` | General |

-| Dutch (Belgium) | `nl-BE` | Female | `nl-BE-DenaNeural` | General |

-| Dutch (Belgium) | `nl-BE` | Male | `nl-BE-ArnaudNeural` | General |

-| Dutch (Netherlands) | `nl-NL` | Female | `nl-NL-ColetteNeural` | General |

-| Dutch (Netherlands) | `nl-NL` | Female | `nl-NL-FennaNeural` | General |

-| Dutch (Netherlands) | `nl-NL` | Male | `nl-NL-MaartenNeural` | General |

-| English (Australia) | `en-AU` | Female | `en-AU-NatashaNeural` | General |

-| English (Australia) | `en-AU` | Male | `en-AU-WilliamNeural` | General |

-| English (Canada) | `en-CA` | Female | `en-CA-ClaraNeural` | General |

-| English (Canada) | `en-CA` | Male | `en-CA-LiamNeural` | General |

-| English (Hongkong) | `en-HK` | Female | `en-HK-YanNeural` | General |

-| English (Hongkong) | `en-HK` | Male | `en-HK-SamNeural` | General |

-| English (India) | `en-IN` | Female | `en-IN-NeerjaNeural` | General |

-| English (India) | `en-IN` | Male | `en-IN-PrabhatNeural` | General |

-| English (Ireland) | `en-IE` | Female | `en-IE-EmilyNeural` | General |

-| English (Ireland) | `en-IE` | Male | `en-IE-ConnorNeural` | General |

-| English (Kenya) | `en-KE` | Female | `en-KE-AsiliaNeural` | General |

-| English (Kenya) | `en-KE` | Male | `en-KE-ChilembaNeural` | General |

-| English (New Zealand) | `en-NZ` | Female | `en-NZ-MollyNeural` | General |

-| English (New Zealand) | `en-NZ` | Male | `en-NZ-MitchellNeural` | General |

-| English (Nigeria) | `en-NG` | Female | `en-NG-EzinneNeural` | General |

-| English (Nigeria) | `en-NG` | Male | `en-NG-AbeoNeural` | General |

-| English (Philippines) | `en-PH` | Female | `en-PH-RosaNeural` | General |

-| English (Philippines) | `en-PH` | Male | `en-PH-JamesNeural` | General |

-| English (Singapore) | `en-SG` | Female | `en-SG-LunaNeural` | General |

-| English (Singapore) | `en-SG` | Male | `en-SG-WayneNeural` | General |

-| English (South Africa) | `en-ZA` | Female | `en-ZA-LeahNeural` | General |

-| English (South Africa) | `en-ZA` | Male | `en-ZA-LukeNeural` | General |

-| English (Tanzania) | `en-TZ` | Female | `en-TZ-ImaniNeural` | General |

-| English (Tanzania) | `en-TZ` | Male | `en-TZ-ElimuNeural` | General |

-| English (United Kingdom) | `en-GB` | Female | `en-GB-AbbiNeural` | General |

-| English (United Kingdom) | `en-GB` | Female | `en-GB-BellaNeural` | General |

-| English (United Kingdom) | `en-GB` | Female | `en-GB-HollieNeural` | General |

-| English (United Kingdom) | `en-GB` | Female | `en-GB-LibbyNeural` | General |

-| English (United Kingdom) | `en-GB` | Female | `en-GB-MaisieNeural` | General, child voice |

-| English (United Kingdom) | `en-GB` | Female | `en-GB-MiaNeural` ^{Retired on 30 October 2021, see below} | General |

-| English (United Kingdom) | `en-GB` | Female | `en-GB-OliviaNeural` | General |

-| English (United Kingdom) | `en-GB` | Female | `en-GB-SoniaNeural` | General |

-| English (United Kingdom) | `en-GB` | Male | `en-GB-AlfieNeural` | General |

-| English (United Kingdom) | `en-GB` | Male | `en-GB-ElliotNeural` | General |

-| English (United Kingdom) | `en-GB` | Male | `en-GB-EthanNeural` | General |

-| English (United Kingdom) | `en-GB` | Male | `en-GB-NoahNeural` | General |

-| English (United Kingdom) | `en-GB` | Male | `en-GB-OliverNeural` | General |

-| English (United Kingdom) | `en-GB` | Male | `en-GB-RyanNeural` | General |

-| English (United Kingdom) | `en-GB` | Male | `en-GB-ThomasNeural` | General |

-| English (United States) | `en-US` | Female | `en-US-AmberNeural` | General |

-| English (United States) | `en-US` | Female | `en-US-AriaNeural` | General, multiple voice styles available [using SSML](speech-synthesis-markup.md#adjust-speaking-styles) |

-| English (United States) | `en-US` | Female | `en-US-AshleyNeural` | General |

-| English (United States) | `en-US` | Female | `en-US-CoraNeural` | General |

-| English (United States) | `en-US` | Female | `en-US-ElizabethNeural` | General |

-| English (United States) | `en-US` | Female | `en-US-JennyNeural` | General, multiple voice styles available [using SSML](speech-synthesis-markup.md#adjust-speaking-styles) |

-| English (United States) | `en-US` as the primary default. Additional locales are supported [using SSML](speech-synthesis-markup.md#adjust-speaking-languages) | Female | `en-US-JennyMultilingualNeural` | General |

-| English (United States) | `en-US` | Female | `en-US-MichelleNeural`| General |

-| English (United States) | `en-US` | Female | `en-US-MonicaNeural` | General |

-| English (United States) | `en-US` | Female | `en-US-SaraNeural` | General, multiple voice styles available [using SSML](speech-synthesis-markup.md#adjust-speaking-styles) |

-| English (United States) | `en-US` | Kid | `en-US-AnaNeural`| General |

-| English (United States) | `en-US` | Male | `en-US-BrandonNeural` | General |

-| English (United States) | `en-US` | Male | `en-US-ChristopherNeural` | General |

-| English (United States) | `en-US` | Male | `en-US-EricNeural` | General |

-| English (United States) | `en-US` | Male | `en-US-GuyNeural` | General, multiple voice styles available [using SSML](speech-synthesis-markup.md#adjust-speaking-styles) |

-| English (United States) | `en-US` | Male | `en-US-JacobNeural` | General |

-| Estonian (Estonia) | `et-EE` | Female | `et-EE-AnuNeural` | General |

-| Estonian (Estonia) | `et-EE` | Male | `et-EE-KertNeural` | General |

-| Filipino (Philippines) | `fil-PH` | Female | `fil-PH-BlessicaNeural` | General |

-| Filipino (Philippines) | `fil-PH` | Male | `fil-PH-AngeloNeural` | General |

-| Finnish (Finland) | `fi-FI` | Female | `fi-FI-NooraNeural` | General |

-| Finnish (Finland) | `fi-FI` | Female | `fi-FI-SelmaNeural` | General |

-| Finnish (Finland) | `fi-FI` | Male | `fi-FI-HarriNeural` | General |

-| French (Belgium) | `fr-BE` | Female | `fr-BE-CharlineNeural` | General |

-| French (Belgium) | `fr-BE` | Male | `fr-BE-GerardNeural` | General |

-| French (Canada) | `fr-CA` | Female | `fr-CA-SylvieNeural` | General |

-| French (Canada) | `fr-CA` | Male | `fr-CA-AntoineNeural` | General |

-| French (Canada) | `fr-CA` | Male | `fr-CA-JeanNeural` | General |

-| French (France) | `fr-FR` | Female | `fr-FR-BrigitteNeural` | General |

-| French (France) | `fr-FR` | Female | `fr-FR-CelesteNeural` | General |

-| French (France) | `fr-FR` | Female | `fr-FR-CoralieNeural` | General |

-| French (France) | `fr-FR` | Female | `fr-FR-DeniseNeural` | General, multiple voice styles available [using SSML](speech-synthesis-markup.md#adjust-speaking-styles) ^{Public preview} |

-| French (France) | `fr-FR` | Female | `fr-FR-EloiseNeural` | General, child voice |

-| French (France) | `fr-FR` | Female | `fr-FR-JacquelineNeural` | General |

-| French (France) | `fr-FR` | Female | `fr-FR-JosephineNeural` | General |

-| French (France) | `fr-FR` | Female | `fr-FR-YvetteNeural` | General |

-| French (France) | `fr-FR` | Male | `fr-FR-AlainNeural` | General |

-| French (France) | `fr-FR` | Male | `fr-FR-ClaudeNeural` | General |

-| French (France) | `fr-FR` | Male | `fr-FR-HenriNeural` | General |

-| French (France) | `fr-FR` | Male | `fr-FR-JeromeNeural` | General |

-| French (France) | `fr-FR` | Male | `fr-FR-MauriceNeural` | General |

-| French (France) | `fr-FR` | Male | `fr-FR-YvesNeural` | General |

-| French (Switzerland) | `fr-CH` | Female | `fr-CH-ArianeNeural` | General |

-| French (Switzerland) | `fr-CH` | Male | `fr-CH-FabriceNeural` | General |

-| Galician (Spain) | `gl-ES` | Female | `gl-ES-SabelaNeural` | General |

-| Galician (Spain) | `gl-ES` | Male | `gl-ES-RoiNeural` | General |

-| Georgian (Georgia) | `ka-GE` | Female | `ka-GE-EkaNeural` ^New | General |

-| Georgian (Georgia) | `ka-GE` | Male | `ka-GE-GiorgiNeural` ^New | General |

-| German (Austria) | `de-AT` | Female | `de-AT-IngridNeural` | General |

-| German (Austria) | `de-AT` | Male | `de-AT-JonasNeural` | General |

-| German (Germany) | `de-DE` | Female | `de-DE-AmalaNeural` | General |

-| German (Germany) | `de-DE` | Female | `de-DE-ElkeNeural` | General |

-| German (Germany) | `de-DE` | Female | `de-DE-GiselaNeural` | General, child voice |

-| German (Germany) | `de-DE` | Female | `de-DE-KatjaNeural` | General |

-| German (Germany) | `de-DE` | Female | `de-DE-KlarissaNeural` | General |

-| German (Germany) | `de-DE` | Female | `de-DE-LouisaNeural` | General |

-| German (Germany) | `de-DE` | Female | `de-DE-MajaNeural` | General |

-| German (Germany) | `de-DE` | Female | `de-DE-TanjaNeural` | General |

-| German (Germany) | `de-DE` | Male | `de-DE-BerndNeural` | General |

-| German (Germany) | `de-DE` | Male | `de-DE-ChristophNeural` | General |

-| German (Germany) | `de-DE` | Male | `de-DE-ConradNeural` | General |

-| German (Germany) | `de-DE` | Male | `de-DE-KasperNeural` | General |

-| German (Germany) | `de-DE` | Male | `de-DE-KillianNeural` | General |

-| German (Germany) | `de-DE` | Male | `de-DE-KlausNeural` | General |

-| German (Germany) | `de-DE` | Male | `de-DE-RalfNeural` | General |

-| German (Switzerland) | `de-CH` | Female | `de-CH-LeniNeural` | General |

-| German (Switzerland) | `de-CH` | Male | `de-CH-JanNeural` | General |

-| Greek (Greece) | `el-GR` | Female | `el-GR-AthinaNeural` | General |

-| Greek (Greece) | `el-GR` | Male | `el-GR-NestorasNeural` | General |

-| Gujarati (India) | `gu-IN` | Female | `gu-IN-DhwaniNeural` | General |

-| Gujarati (India) | `gu-IN` | Male | `gu-IN-NiranjanNeural` | General |

-| Hebrew (Israel) | `he-IL` | Female | `he-IL-HilaNeural` | General |

-| Hebrew (Israel) | `he-IL` | Male | `he-IL-AvriNeural` | General |

-| Hindi (India) | `hi-IN` | Female | `hi-IN-SwaraNeural` | General |

-| Hindi (India) | `hi-IN` | Male | `hi-IN-MadhurNeural` | General |

-| Hungarian (Hungary) | `hu-HU` | Female | `hu-HU-NoemiNeural` | General |

-| Hungarian (Hungary) | `hu-HU` | Male | `hu-HU-TamasNeural` | General |

-| Icelandic (Iceland) | `is-IS` | Female | `is-IS-GudrunNeural` | General |

-| Icelandic (Iceland) | `is-IS` | Male | `is-IS-GunnarNeural` | General |

-| Indonesian (Indonesia) | `id-ID` | Female | `id-ID-GadisNeural` | General |

-| Indonesian (Indonesia) | `id-ID` | Male | `id-ID-ArdiNeural` | General |

-| Irish (Ireland) | `ga-IE` | Female | `ga-IE-OrlaNeural` | General |

-| Irish (Ireland) | `ga-IE` | Male | `ga-IE-ColmNeural` | General |

-| Italian (Italy) | `it-IT` | Female | `it-IT-ElsaNeural` | General |

-| Italian (Italy) | `it-IT` | Female | `it-IT-IsabellaNeural` | General |

-| Italian (Italy) | `it-IT` | Male | `it-IT-DiegoNeural` | General |

-| Japanese (Japan) | `ja-JP` | Female | `ja-JP-NanamiNeural` | General |

-| Japanese (Japan) | `ja-JP` | Male | `ja-JP-KeitaNeural` | General |

-| Javanese (Indonesia) | `jv-ID` | Female | `jv-ID-SitiNeural` | General |

-| Javanese (Indonesia) | `jv-ID` | Male | `jv-ID-DimasNeural` | General |

-| Kannada (India) | `kn-IN` | Female | `kn-IN-SapnaNeural` | General |

-| Kannada (India) | `kn-IN` | Male | `kn-IN-GaganNeural` | General |

-| Kazakh (Kazakhstan) | `kk-KZ` | Female | `kk-KZ-AigulNeural` | General |

-| Kazakh (Kazakhstan) | `kk-KZ` | Male | `kk-KZ-DauletNeural` | General |

-| Khmer (Cambodia) | `km-KH` | Female | `km-KH-SreymomNeural` | General |

-| Khmer (Cambodia) | `km-KH` | Male | `km-KH-PisethNeural` | General |

-| Korean (Korea) | `ko-KR` | Female | `ko-KR-SunHiNeural` | General |

-| Korean (Korea) | `ko-KR` | Male | `ko-KR-InJoonNeural` | General |

-| Lao (Laos) | `lo-LA` | Female | `lo-LA-KeomanyNeural` | General |

-| Lao (Laos) | `lo-LA` | Male | `lo-LA-ChanthavongNeural` | General |

-| Latvian (Latvia) | `lv-LV` | Female | `lv-LV-EveritaNeural` | General |

-| Latvian (Latvia) | `lv-LV` | Male | `lv-LV-NilsNeural` | General |

-| Lithuanian (Lithuania) | `lt-LT` | Female | `lt-LT-OnaNeural` | General |

-| Lithuanian (Lithuania) | `lt-LT` | Male | `lt-LT-LeonasNeural` | General |

-| Macedonian (Republic of North Macedonia) | `mk-MK` | Female | `mk-MK-MarijaNeural` | General |

-| Macedonian (Republic of North Macedonia) | `mk-MK` | Male | `mk-MK-AleksandarNeural` | General |

-| Malay (Malaysia) | `ms-MY` | Female | `ms-MY-YasminNeural` | General |

-| Malay (Malaysia) | `ms-MY` | Male | `ms-MY-OsmanNeural` | General |

-| Malayalam (India) | `ml-IN` | Female | `ml-IN-SobhanaNeural` | General |

-| Malayalam (India) | `ml-IN` | Male | `ml-IN-MidhunNeural` | General |

-| Maltese (Malta) | `mt-MT` | Female | `mt-MT-GraceNeural` | General |

-| Maltese (Malta) | `mt-MT` | Male | `mt-MT-JosephNeural` | General |

-| Marathi (India) | `mr-IN` | Female | `mr-IN-AarohiNeural` | General |

-| Marathi (India) | `mr-IN` | Male | `mr-IN-ManoharNeural` | General |

-| Mongolian (Mongolia) | `mn-MN` | Female | `mn-MN-YesuiNeural` ^New | General |

-| Mongolian (Mongolia) | `mn-MN` | Male | `mn-MN-BataaNeural` ^New | General |

-| Nepali (Nepal) | `ne-NP` | Female | `ne-NP-HemkalaNeural` ^New | General |

-| Nepali (Nepal) | `ne-NP` | Male | `ne-NP-SagarNeural` ^New | General |

-| Norwegian (Bokmål, Norway) | `nb-NO` | Female | `nb-NO-IselinNeural` | General |

-| Norwegian (Bokmål, Norway) | `nb-NO` | Female | `nb-NO-PernilleNeural` | General |

-| Norwegian (Bokmål, Norway) | `nb-NO` | Male | `nb-NO-FinnNeural` | General |

-| Pashto (Afghanistan) | `ps-AF` | Female | `ps-AF-LatifaNeural` | General |

-| Pashto (Afghanistan) | `ps-AF` | Male | `ps-AF-GulNawazNeural` | General |

-| Persian (Iran) | `fa-IR` | Female | `fa-IR-DilaraNeural` | General |

-| Persian (Iran) | `fa-IR` | Male | `fa-IR-FaridNeural` | General |

-| Polish (Poland) | `pl-PL` | Female | `pl-PL-AgnieszkaNeural` | General |

-| Polish (Poland) | `pl-PL` | Female | `pl-PL-ZofiaNeural` | General |

-| Polish (Poland) | `pl-PL` | Male | `pl-PL-MarekNeural` | General |

-| Portuguese (Brazil) | `pt-BR` | Female | `pt-BR-FranciscaNeural` | General, multiple voice styles available [using SSML](speech-synthesis-markup.md#adjust-speaking-styles) |

-| Portuguese (Brazil) | `pt-BR` | Male | `pt-BR-AntonioNeural` | General |

-| Portuguese (Portugal) | `pt-PT` | Female | `pt-PT-FernandaNeural` | General |

-| Portuguese (Portugal) | `pt-PT` | Female | `pt-PT-RaquelNeural` | General |

-| Portuguese (Portugal) | `pt-PT` | Male | `pt-PT-DuarteNeural` | General |

-| Romanian (Romania) | `ro-RO` | Female | `ro-RO-AlinaNeural` | General |

-| Romanian (Romania) | `ro-RO` | Male | `ro-RO-EmilNeural` | General |

-| Russian (Russia) | `ru-RU` | Female | `ru-RU-DariyaNeural` | General |

-| Russian (Russia) | `ru-RU` | Female | `ru-RU-SvetlanaNeural` | General |

-| Russian (Russia) | `ru-RU` | Male | `ru-RU-DmitryNeural` | General |

-| Serbian (Serbia, Cyrillic) | `sr-RS` | Female | `sr-RS-SophieNeural` | General |

-| Serbian (Serbia, Cyrillic) | `sr-RS` | Male | `sr-RS-NicholasNeural` | General |

-| Sinhala (Sri Lanka) | `si-LK` | Female | `si-LK-ThiliniNeural` | General |

-| Sinhala (Sri Lanka) | `si-LK` | Male | `si-LK-SameeraNeural` | General |

-| Slovak (Slovakia) | `sk-SK` | Female | `sk-SK-ViktoriaNeural` | General |

-| Slovak (Slovakia) | `sk-SK` | Male | `sk-SK-LukasNeural` | General |

-| Slovenian (Slovenia) | `sl-SI` | Female | `sl-SI-PetraNeural` | General |

-| Slovenian (Slovenia) | `sl-SI` | Male | `sl-SI-RokNeural` | General |

-| Somali (Somalia) | `so-SO` | Female | `so-SO-UbaxNeural` | General |

-| Somali (Somalia) | `so-SO`| Male | `so-SO-MuuseNeural` | General |

-| Spanish (Argentina) | `es-AR` | Female | `es-AR-ElenaNeural` | General |

-| Spanish (Argentina) | `es-AR` | Male | `es-AR-TomasNeural` | General |

-| Spanish (Bolivia) | `es-BO` | Female | `es-BO-SofiaNeural` | General |

-| Spanish (Bolivia) | `es-BO` | Male | `es-BO-MarceloNeural` | General |

-| Spanish (Chile) | `es-CL` | Female | `es-CL-CatalinaNeural` | General |

-| Spanish (Chile) | `es-CL` | Male | `es-CL-LorenzoNeural` | General |

-| Spanish (Colombia) | `es-CO` | Female | `es-CO-SalomeNeural` | General |

-| Spanish (Colombia) | `es-CO` | Male | `es-CO-GonzaloNeural` | General |

-| Spanish (Costa Rica) | `es-CR` | Female | `es-CR-MariaNeural` | General |

-| Spanish (Costa Rica) | `es-CR` | Male | `es-CR-JuanNeural` | General |

-| Spanish (Cuba) | `es-CU` | Female | `es-CU-BelkysNeural` | General |

-| Spanish (Cuba) | `es-CU` | Male | `es-CU-ManuelNeural` | General |

-| Spanish (Dominican Republic) | `es-DO` | Female | `es-DO-RamonaNeural` | General |

-| Spanish (Dominican Republic) | `es-DO` | Male | `es-DO-EmilioNeural` | General |

-| Spanish (Ecuador) | `es-EC` | Female | `es-EC-AndreaNeural` | General |

-| Spanish (Ecuador) | `es-EC` | Male | `es-EC-LuisNeural` | General |

-| Spanish (El Salvador) | `es-SV` | Female | `es-SV-LorenaNeural` | General |

-| Spanish (El Salvador) | `es-SV` | Male | `es-SV-RodrigoNeural` | General |

-| Spanish (Equatorial Guinea) | `es-GQ` | Female | `es-GQ-TeresaNeural` | General |

-| Spanish (Equatorial Guinea) | `es-GQ` | Male | `es-GQ-JavierNeural` | General |

-| Spanish (Guatemala) | `es-GT` | Female | `es-GT-MartaNeural` | General |

-| Spanish (Guatemala) | `es-GT` | Male | `es-GT-AndresNeural` | General |

-| Spanish (Honduras) | `es-HN` | Female | `es-HN-KarlaNeural` | General |

-| Spanish (Honduras) | `es-HN` | Male | `es-HN-CarlosNeural` | General |

-| Spanish (Mexico) | `es-MX` | Female | `es-MX-DaliaNeural` | General |

-| Spanish (Mexico) | `es-MX` | Male | `es-MX-JorgeNeural` | General |

-| Spanish (Nicaragua) | `es-NI` | Female | `es-NI-YolandaNeural` | General |

-| Spanish (Nicaragua) | `es-NI` | Male | `es-NI-FedericoNeural` | General |

-| Spanish (Panama) | `es-PA` | Female | `es-PA-MargaritaNeural` | General |

-| Spanish (Panama) | `es-PA` | Male | `es-PA-RobertoNeural` | General |

-| Spanish (Paraguay) | `es-PY` | Female | `es-PY-TaniaNeural` | General |

-| Spanish (Paraguay) | `es-PY` | Male | `es-PY-MarioNeural` | General |

-| Spanish (Peru) | `es-PE` | Female | `es-PE-CamilaNeural` | General |

-| Spanish (Peru) | `es-PE` | Male | `es-PE-AlexNeural` | General |

-| Spanish (Puerto Rico) | `es-PR` | Female | `es-PR-KarinaNeural` | General |

-| Spanish (Puerto Rico) | `es-PR` | Male | `es-PR-VictorNeural` | General |

-| Spanish (Spain) | `es-ES` | Female | `es-ES-ElviraNeural` | General |

-| Spanish (Spain) | `es-ES` | Male | `es-ES-AlvaroNeural` | General |

-| Spanish (Uruguay) | `es-UY` | Female | `es-UY-ValentinaNeural` | General |

-| Spanish (Uruguay) | `es-UY` | Male | `es-UY-MateoNeural` | General |

-| Spanish (US) | `es-US` | Female | `es-US-PalomaNeural` | General |

-| Spanish (US) | `es-US` | Male | `es-US-AlonsoNeural` | General |

-| Spanish (Venezuela) | `es-VE` | Female | `es-VE-PaolaNeural` | General |

-| Spanish (Venezuela) | `es-VE` | Male | `es-VE-SebastianNeural` | General |

-| Sundanese (Indonesia) | `su-ID` | Female | `su-ID-TutiNeural` | General |

-| Sundanese (Indonesia) | `su-ID` | Male | `su-ID-JajangNeural` | General |

-| Swahili (Kenya) | `sw-KE` | Female | `sw-KE-ZuriNeural` | General |

-| Swahili (Kenya) | `sw-KE` | Male | `sw-KE-RafikiNeural` | General |

-| Swahili (Tanzania) | `sw-TZ` | Female | `sw-TZ-RehemaNeural` | General |

-| Swahili (Tanzania) | `sw-TZ` | Male | `sw-TZ-DaudiNeural` | General |

-| Swedish (Sweden) | `sv-SE` | Female | `sv-SE-HilleviNeural` | General |

-| Swedish (Sweden) | `sv-SE` | Female | `sv-SE-SofieNeural` | General |

-| Swedish (Sweden) | `sv-SE` | Male | `sv-SE-MattiasNeural` | General |

-| Tamil (India) | `ta-IN` | Female | `ta-IN-PallaviNeural` | General |

-| Tamil (India) | `ta-IN` | Male | `ta-IN-ValluvarNeural` | General |

-| Tamil (Malaysia) | `ta-MY` | Female | `ta-MY-KaniNeural` ^New | General |

-| Tamil (Malaysia) | `ta-MY` | Male | `ta-MY-SuryaNeural` ^New | General |

-| Tamil (Singapore) | `ta-SG` | Female | `ta-SG-VenbaNeural` | General |

-| Tamil (Singapore) | `ta-SG` | Male | `ta-SG-AnbuNeural` | General |

-| Tamil (Sri Lanka) | `ta-LK` | Female | `ta-LK-SaranyaNeural` | General |

-| Tamil (Sri Lanka) | `ta-LK` | Male | `ta-LK-KumarNeural` | General |

-| Telugu (India) | `te-IN` | Female | `te-IN-ShrutiNeural` | General |

-| Telugu (India) | `te-IN` | Male | `te-IN-MohanNeural` | General |

-| Thai (Thailand) | `th-TH` | Female | `th-TH-AcharaNeural` | General |

-| Thai (Thailand) | `th-TH` | Female | `th-TH-PremwadeeNeural` | General |

-| Thai (Thailand) | `th-TH` | Male | `th-TH-NiwatNeural` | General |

-| Turkish (Turkey) | `tr-TR` | Female | `tr-TR-EmelNeural` | General |

-| Turkish (Turkey) | `tr-TR` | Male | `tr-TR-AhmetNeural` | General |

-| Ukrainian (Ukraine) | `uk-UA` | Female | `uk-UA-PolinaNeural` | General |

-| Ukrainian (Ukraine) | `uk-UA` | Male | `uk-UA-OstapNeural` | General |

-| Urdu (India) | `ur-IN` | Female | `ur-IN-GulNeural` | General |

-| Urdu (India) | `ur-IN` | Male | `ur-IN-SalmanNeural` | General |

-| Urdu (Pakistan) | `ur-PK` | Female | `ur-PK-UzmaNeural` | General |

-| Urdu (Pakistan) | `ur-PK` | Male | `ur-PK-AsadNeural` | General |

-| Uzbek (Uzbekistan) | `uz-UZ` | Female | `uz-UZ-MadinaNeural` | General |

-| Uzbek (Uzbekistan) | `uz-UZ` | Male | `uz-UZ-SardorNeural` | General |

-| Vietnamese (Vietnam) | `vi-VN` | Female | `vi-VN-HoaiMyNeural` | General |

-| Vietnamese (Vietnam) | `vi-VN` | Male | `vi-VN-NamMinhNeural` | General |

-| Welsh (United Kingdom) | `cy-GB` | Female | `cy-GB-NiaNeural` | General |

-| Welsh (United Kingdom) | `cy-GB` | Male | `cy-GB-AledNeural` | General |

-| Zulu (South Africa) | `zu-ZA` | Female | `zu-ZA-ThandoNeural` | General |

-| Zulu (South Africa) | `zu-ZA` | Male | `zu-ZA-ThembaNeural` | General |

-### Prebuilt neural voices in preview

-The following neural voices are in public preview.

-> [!NOTE]

-> Voices and styles in public preview are only available in three service [regions](regions.md): East US, West Europe, and Southeast Asia.

-| Language | Locale | Gender | Voice name | Style support |

-|-||--|-||

-| Chinese (Mandarin, Simplified) | `zh-CN` | Female | `zh-CN-XiaomengNeural` ^New | General, multiple styles available [using SSML](speech-synthesis-markup.md#adjust-speaking-styles) |

-| Chinese (Mandarin, Simplified) | `zh-CN` | Female | `zh-CN-XiaoyiNeural` ^New | General, multiple styles available [using SSML](speech-synthesis-markup.md#adjust-speaking-styles) |

-| Chinese (Mandarin, Simplified) | `zh-CN` | Female | `zh-CN-XiaozhenNeural` ^New | General, multiple styles available [using SSML](speech-synthesis-markup.md#adjust-speaking-styles) |

-| Chinese (Mandarin, Simplified) | `zh-CN` | Male | `zh-CN-YunfengNeural` ^New | General, multiple styles available [using SSML](speech-synthesis-markup.md#adjust-speaking-styles) |

-| Chinese (Mandarin, Simplified) | `zh-CN` | Male | `zh-CN-YunhaoNeural` ^New | Optimized for promoting a product or service, multiple styles available [using SSML](speech-synthesis-markup.md#adjust-speaking-styles) |

-| Chinese (Mandarin, Simplified) | `zh-CN` | Male | `zh-CN-YunjianNeural` ^New | Optimized for broadcasting sports event, multiple styles available [using SSML](speech-synthesis-markup.md#adjust-speaking-styles) |

-| Chinese (Mandarin, Simplified) | `zh-CN` | Male | `zh-CN-YunxiaNeural` ^New | General, multiple styles available [using SSML](speech-synthesis-markup.md#adjust-speaking-styles) |

-| Chinese (Mandarin, Simplified) | `zh-CN` | Male | `zh-CN-YunzeNeural` ^New | General, multiple styles available [using SSML](speech-synthesis-markup.md#adjust-speaking-styles) |

-| Chinese (Mandarin, Simplified) | `zh-CN-liaoning` | Female | `zh-CN-liaoning-XiaobeiNeural` ^New | General, Liaoning accent |

-| Chinese (Mandarin, Simplified) | `zh-CN-sichuan` | Male | `zh-CN-sichuan-YunxiSichuanNeural` ^New | General, Sichuan accent |

-| English (United States) | `en-US` | Female | `en-US-JaneNeural` ^New | General, multiple voice styles available [using SSML](speech-synthesis-markup.md#adjust-speaking-styles) |

-| English (United States) | `en-US` | Female | `en-US-NancyNeural` ^New | General, multiple voice styles available [using SSML](speech-synthesis-markup.md#adjust-speaking-styles) |

-| English (United States) | `en-US` | Male | `en-US-AIGenerate1Neural` ^New | General|

-| English (United States) | `en-US` | Male | `en-US-DavisNeural` ^New | General, multiple voice styles available [using SSML](speech-synthesis-markup.md#adjust-speaking-styles) |

-| English (United States) | `en-US` | Male | `en-US-JasonNeural` ^New | General, multiple voice styles available [using SSML](speech-synthesis-markup.md#adjust-speaking-styles) |

-| English (United States) | `en-US` | Male | `en-US-RogerNeural` ^New | General|

-| English (United States) | `en-US` | Male | `en-US-TonyNeural` ^New | General, multiple voice styles available [using SSML](speech-synthesis-markup.md#adjust-speaking-styles) |

-| Italian (Italy) | `it-IT` | Female | `it-IT-FabiolaNeural` ^New | General |

-| Italian (Italy) | `it-IT` | Female | `it-IT-FiammaNeural` ^New | General |

-| Italian (Italy) | `it-IT` | Female | `it-IT-ImeldaNeural` ^New | General |

-| Italian (Italy) | `it-IT` | Female | `it-IT-IrmaNeural` ^New | General |

-| Italian (Italy) | `it-IT` | Female | `it-IT-PalmiraNeural` ^New | General |

-| Italian (Italy) | `it-IT` | Female | `it-IT-PierinaNeural` ^New | General |

-| Italian (Italy) | `it-IT` | Male | `it-IT-BenignoNeural` ^New | General |

-| Italian (Italy) | `it-IT` | Male | `it-IT-CalimeroNeural` ^New | General |

-| Italian (Italy) | `it-IT` | Male | `it-IT-CataldoNeural` ^New | General |

-| Italian (Italy) | `it-IT` | Male | `it-IT-GianniNeural` ^New | General |

-| Italian (Italy) | `it-IT` | Male | `it-IT-LisandroNeural` ^New | General |

-| Italian (Italy) | `it-IT` | Male | `it-IT-RinaldoNeural` ^New | General |

-| Portuguese (Brazil) | `pt-BR` | Female | `pt-BR-BrendaNeural` ^New | General |

-| Portuguese (Brazil) | `pt-BR` | Female | `pt-BR-ElzaNeural` ^New | General |

-| Portuguese (Brazil) | `pt-BR` | Female | `pt-BR-GiovannaNeural` ^New | General |

-| Portuguese (Brazil) | `pt-BR` | Female | `pt-BR-LeilaNeural` ^New | General |

-| Portuguese (Brazil) | `pt-BR` | Female | `pt-BR-LeticiaNeural` ^New | General |

-| Portuguese (Brazil) | `pt-BR` | Female | `pt-BR-ManuelaNeural` ^New | General |

-| Portuguese (Brazil) | `pt-BR` | Female | `pt-BR-YaraNeural` ^New | General |

-| Portuguese (Brazil) | `pt-BR` | Male | `pt-BR-DonatoNeural` ^New | General |

-| Portuguese (Brazil) | `pt-BR` | Male | `pt-BR-FabioNeural` ^New | General |

-| Portuguese (Brazil) | `pt-BR` | Male | `pt-BR-HumbertoNeural` ^New | General |

-| Portuguese (Brazil) | `pt-BR` | Male | `pt-BR-JulioNeural` ^New | General |

-| Portuguese (Brazil) | `pt-BR` | Male | `pt-BR-NicolauNeural` ^New | General |

-| Portuguese (Brazil) | `pt-BR` | Male | `pt-BR-ValerioNeural` ^New | General |

-| Spanish (Mexico) | `es-MX` | Female | `es-MX-BeatrizNeural` ^New | General |

-| Spanish (Mexico) | `es-MX` | Female | `es-MX-CandelaNeural` ^New | General |

-| Spanish (Mexico) | `es-MX` | Female | `es-MX-CarlotaNeural` ^New | General |

-| Spanish (Mexico) | `es-MX` | Female | `es-MX-LarissaNeural` ^New | General |

-| Spanish (Mexico) | `es-MX` | Female | `es-MX-MarinaNeural` ^New | General |

-| Spanish (Mexico) | `es-MX` | Female | `es-MX-NuriaNeural` ^New | General |

-| Spanish (Mexico) | `es-MX` | Female | `es-MX-RenataNeural` ^New | General |

-| Spanish (Mexico) | `es-MX` | Male | `es-MX-CecilioNeural` ^New | General |

-| Spanish (Mexico) | `es-MX` | Male | `es-MX-GerardoNeural` ^New | General |

-| Spanish (Mexico) | `es-MX` | Male | `es-MX-LibertoNeural` ^New | General |

-| Spanish (Mexico) | `es-MX` | Male | `es-MX-LucianoNeural` ^New | General |

-| Spanish (Mexico) | `es-MX` | Male | `es-MX-PelayoNeural` ^New | General |

-| Spanish (Mexico) | `es-MX` | Male | `es-MX-YagoNeural` ^New | General |

-> [!NOTE]

-> The angry, cheerful, excited, friendly, hopeful, sad, shouting, terrified, unfriendly, and whispering styles for DavisNeural, JaneNeural, JasonNeural, NancyNeural and TonyNeural are only available in three service regions: East US, West Europe, and Southeast Asia.

-|Voice|Styles|Style degree|Roles|

-|--|--|--|--|

-|en-US-AriaNeural|`angry`, `chat`, `cheerful`, `customerservice`, `empathetic`, `excited`, `friendly`, `hopeful`, `narration-professional`, `newscast-casual`, `newscast-formal`, `sad`, `shouting`, `terrified`, `unfriendly`, `whispering`|||

-|en-US-DavisNeural ^{Public preview}|`angry`, `chat`, `cheerful`, `excited`, `friendly`, `hopeful`, `sad`, `shouting`, `terrified`, `unfriendly`, `whispering`|||

-|en-US-GuyNeural|`angry`, `cheerful`, `excited`, `friendly`, `hopeful`, `newscast`, `sad`, `shouting`, `terrified`, `unfriendly`, `whispering`|||

-|en-US-JaneNeural ^{Public preview}|`angry`, `cheerful`, `excited`, `friendly`, `hopeful`, `sad`, `shouting`, `terrified`, `unfriendly`, `whispering`|||

-|en-US-JasonNeural ^{Public preview}|`angry`, `cheerful`, `excited`, `friendly`, `hopeful`, `sad`, `shouting`, `terrified`, `unfriendly`, `whispering`|||

-|en-US-JennyNeural|`angry`, `assistant`, `chat`, `cheerful`,`customerservice`, `excited`, `friendly`, `hopeful`, `newscast`, `sad`, `shouting`, `terrified`, `unfriendly`, `whispering`|||

-|en-US-NancyNeural ^{Public preview}|`angry`, `cheerful`, `excited`, `friendly`, `hopeful`, `sad`, `shouting`, `terrified`, `unfriendly`, `whispering`|||

-|en-US-SaraNeural|`angry`, `cheerful`, `excited`, `friendly`, `hopeful`, `sad`, `shouting`, `terrified`, `unfriendly`, `whispering`|||

-|en-US-TonyNeural ^{Public preview}|`angry`, `cheerful`, `excited`, `friendly`, `hopeful`, `sad`, `shouting`, `terrified`, `unfriendly`, `whispering`|||

-|fr-FR-DeniseNeural |`cheerful`, `sad`|||

-|ja-JP-NanamiNeural|`chat`, `cheerful`, `customerservice`|||

-|pt-BR-FranciscaNeural|`calm`|||

-|zh-CN-XiaohanNeural|`affectionate`, `angry`, `calm`, `cheerful`, `disgruntled`, `embarrassed`, `fearful`, `gentle`, `sad`, `serious`|Supported||

-|zh-CN-XiaomengNeural ^{Public preview}|`chat`|Supported||

-|zh-CN-XiaomoNeural|`affectionate`, `angry`, `calm`, `cheerful`, `depressed`, `disgruntled`, `embarrassed`, `envious`, `fearful`, `gentle`, `sad`, `serious`|Supported|Supported|

-|zh-CN-XiaoruiNeural|`angry`, `calm`, `fearful`, `sad`|Supported||

-|zh-CN-XiaoshuangNeural|`chat`|Supported||

-|zh-CN-XiaoxiaoNeural|`affectionate`, `angry`, `assistant`, `calm`, `chat`, `cheerful`, `customerservice`, `disgruntled`, `fearful`, `gentle`, `lyrical`, `newscast`, `poetry-reading`, `sad`, `serious`|Supported||

-|zh-CN-XiaoxuanNeural|`angry`, `calm`, `cheerful`, `depressed`, `disgruntled`, `fearful`, `gentle`, `serious`|Supported|Supported|

-|zh-CN-XiaoyiNeural ^{Public preview}|`affectionate`, `angry`, `cheerful`, `disgruntled`, `embarrassed`, `fearful`, `gentle`, `sad`, `serious`|Supported||

-|zh-CN-XiaozhenNeural ^{Public preview}|`angry`, `cheerful`, `disgruntled`, `fearful`, `sad`, `serious`|Supported||

-|zh-CN-YunfengNeural ^{Public preview}|`calm`, `angry`, ` disgruntled`, `cheerful`, `fearful`, `sad`, `serious`, `depressed`|Supported||

-|zh-CN-YunhaoNeural ^{Public preview}|`general`, `advertisement-upbeat` ^{Public preview}|Supported||

-|zh-CN-YunjianNeural ^{Public preview}|`narration-relaxed`, `sports-commentary` ^{Public preview}, `sports-commentary-excited` ^{Public preview}|Supported||

-|zh-CN-YunxiNeural|`angry`, `assistant`, `cheerful`, `depressed`, `disgruntled`, `embarrassed`, `fearful`, `narration-relaxed`, `sad`, `serious`|Supported|Supported|

-|zh-CN-YunxiaNeural ^{Public preview}|`angry`, `calm`, `cheerful`, `fearful`, `sad`|Supported||

-|zh-CN-YunyangNeural|`customerservice`, `narration-professional`, `newscast-casual`|Supported||

-|zh-CN-YunyeNeural|`angry`, `calm`, `cheerful`, `disgruntled`, `embarrassed`, `fearful`, `sad`, `serious`|Supported|Supported|

-|zh-CN-YunzeNeural ^{Public preview}|`angry`, `calm`, `cheerful`, `depressed`, `disgruntled`, `documentary-narration`, `fearful`, `sad`, `serious`|Supported|Supported|

-Custom Neural Voice lets you create synthetic voices that are rich in speaking styles. You can create a unique brand voice in multiple languages and styles by using a small set of recording data.

-With the cross-lingual feature (preview), you can transfer your custom neural voice model to speak a second language. For example, with the `zh-CN` data, you can create a voice that speaks `en-AU` or any of the languages marked with "Yes" in the Cross-lingual column in the following table.

-There are two Custom Neural Voice (CNV) project types: CNV Pro and CNV Lite (preview). In the following table, all the languages are supported by CNV Pro, and the languages marked with "Yes" in the Custom Neural Voice Lite column are supported by CNV Lite.

-| Language | Locale | Cross-lingual (preview) |Custom Neural Voice Lite (preview)|

-|--|--|--|--|

-| Arabic (Egypt) | `ar-EG` | No |No|

-| Arabic (Saudi Arabia) | `ar-SA` | No |No|

-| Bulgarian (Bulgaria) | `bg-BG` | No |No|

-| Catalan (Spain) | `ca-ES` | No |No|

-| Chinese (Cantonese, Traditional) | `zh-HK` | No |No|

-| Chinese (Mandarin, Simplified) | `zh-CN` | Yes |Yes|

-| Chinese (Mandarin, Simplified), English bilingual | `zh-CN` bilingual | Yes |No|

-| Chinese (Taiwanese Mandarin) | `zh-TW` | No |No|

-| Croatian (Croatia) | `hr-HR` | No |No|

-| Czech (Czech) | `cs-CZ` | No |No|

-| Danish (Denmark) | `da-DK` | No |No|

-| Dutch (Netherlands) | `nl-NL` | No |No|

-| English (Australia) | `en-AU` | Yes |Yes|

-| English (Canada) | `en-CA` | No |Yes|

-| English (India) | `en-IN` | No |No|

-| English (Ireland) | `en-IE` | No |No|

-| English (United Kingdom) | `en-GB` | Yes |Yes|

-| English (United States) | `en-US` | Yes |Yes|

-| Finnish (Finland) | `fi-FI` | No |No|

-| French (Canada) | `fr-CA` | Yes |No|

-| French (France) | `fr-FR` | Yes |Yes|

-| French (Switzerland) | `fr-CH` | No |No|

-| German (Austria) | `de-AT` | No |No|

-| German (Germany) | `de-DE` | Yes |Yes|

-| German (Switzerland) | `de-CH` | No |No|

-| Greek (Greece) | `el-GR` | No |No|

-| Hebrew (Israel) | `he-IL` | No |No|

-| Hindi (India) | `hi-IN` | No |No|

-| Hungarian (Hungary) | `hu-HU` | No |No|

-| Indonesian (Indonesia) | `id-ID` | No |No|

-| Italian (Italy) | `it-IT` | Yes |Yes|

-| Japanese (Japan) | `ja-JP` | Yes |Yes|

-| Korean (Korea) | `ko-KR` | Yes |Yes|

-| Malay (Malaysia) | `ms-MY` | No |No|

-| Norwegian (Bokmål, Norway) | `nb-NO` | No |No|

-| Polish (Poland) | `pl-PL` | No |No|

-| Portuguese (Brazil) | `pt-BR` | Yes |Yes|

-| Portuguese (Portugal) | `pt-PT` | No |No|

-| Romanian (Romania) | `ro-RO` | No |No|

-| Russian (Russia) | `ru-RU` | Yes |No|

-| Slovak (Slovakia) | `sk-SK` | No |No|

-| Slovenian (Slovenia) | `sl-SI` | No |No|

-| Spanish (Mexico) | `es-MX` | Yes |Yes|

-| Spanish (Spain) | `es-ES` | Yes |No|

-| Swedish (Sweden) | `sv-SE` | No |No|

-| Tamil (India) | `ta-IN` | No |No |

-| Telugu (India) | `te-IN` | No |No |

-| Thai (Thailand) | `th-TH` | No |No |

-| Turkish (Turkey) | `tr-TR` | No |No|

-| Vietnamese (Vietnam) | `vi-VN` | No |No|

-### Viseme

-A _viseme_ is the visual description of a phoneme in spoken language. It defines the position of the face and mouth while a person is speaking. Each viseme depicts the key facial poses for a specific set of phonemes. Speech audio output can be accompanied by a viseme ID, Scalable Vector Graphics (SVG), or blend shapes. For more information, see [Get facial position with viseme](how-to-speech-synthesis-viseme.md).

-> [!NOTE]

-> Viseme ID supports [neural voices](#text-to-speech) in the locales listed below. SVG only supports neural voices in the `en-US` locale, and blend shapes supports neural voices in the `en-US` and `zh-CN` locales.

-The following table lists the languages supported by viseme ID.

-| Language | Locale |

-|||

-| Arabic (Algeria) | `ar-DZ` |

-| Arabic (Bahrain) | `ar-BH` |

-| Arabic (Egypt) | `ar-EG` |

-| Arabic (Iraq) | `ar-IQ` |

-| Arabic (Jordan) | `ar-JO` |

-| Arabic (Kuwait) | `ar-KW` |

-| Arabic (Lebanon) | `ar-LB` |

-| Arabic (Libya) | `ar-LY` |

-| Arabic (Morocco) | `ar-MA` |

-| Arabic (Oman) | `ar-OM` |

-| Arabic (Qatar) | `ar-QA` |

-| Arabic (Saudi Arabia) | `ar-SA` |

-| Arabic (Syria) | `ar-SY` |

-| Arabic (Tunisia) | `ar-TN` |

-| Arabic (United Arab Emirates) | `ar-AE` |

-| Arabic (Yemen) | `ar-YE` |

-| Bulgarian (Bulgaria) | `bg-BG` |

-| Catalan (Spain) | `ca-ES` |

-| Chinese (Cantonese, Traditional) | `zh-HK` |

-| Chinese (Mandarin, Simplified) | `zh-CN` |

-| Chinese (Taiwanese Mandarin) | `zh-TW` |

-| Croatian (Croatia) | `hr-HR` |

-| Czech (Czech) | `cs-CZ` |

-| Danish (Denmark) | `da-DK` |

-| Dutch (Belgium) | `nl-BE` |

-| Dutch (Netherlands) | `nl-NL` |

-| English (Australia) | `en-AU` |

-| English (Canada) | `en-CA` |

-| English (Hongkong) | `en-HK` |

-| English (India) | `en-IN` |

-| English (Ireland) | `en-IE` |

-| English (Kenya) | `en-KE` |

-| English (New Zealand) | `en-NZ` |

-| English (Nigeria) | `en-NG` |

-| English (Philippines) | `en-PH` |

-| English (Singapore) | `en-SG` |

-| English (South Africa) | `en-ZA` |

-| English (Tanzania) | `en-TZ` |

-| English (United Kingdom) | `en-GB` |

-| English (United States) | `en-US` |

-| Finnish (Finland) | `fi-FI` |

-| French (Belgium) | `fr-BE` |

-| French (Canada) | `fr-CA` |

-| French (France) | `fr-FR` |

-| French (Switzerland) | `fr-CH` |

-| German (Austria) | `de-AT` |

-| German (Germany) | `de-DE` |

-| German (Switzerland) | `de-CH` |

-| Greek (Greece) | `el-GR` |

-| Gujarati (India) | `gu-IN` |

-| Hebrew (Israel) | `he-IL` |

-| Hindi (India) | `hi-IN` |

-| Hungarian (Hungary) | `hu-HU` |

-| Indonesian (Indonesia) | `id-ID` |

-| Italian (Italy) | `it-IT` |

-| Japanese (Japan) | `ja-JP` |

-| Korean (Korea) | `ko-KR` |

-| Malay (Malaysia) | `ms-MY` |

-| Marathi (India) | `mr-IN` |

-| Norwegian (Bokmål, Norway) | `nb-NO` |

-| Polish (Poland) | `pl-PL` |

-| Portuguese (Brazil) | `pt-BR` |

-| Portuguese (Portugal) | `pt-PT` |

-| Romanian (Romania) | `ro-RO` |

-| Russian (Russia) | `ru-RU` |

-| Slovak (Slovakia) | `sk-SK` |

-| Slovenian (Slovenia) | `sl-SI` |

-| Spanish (Argentina) | `es-AR` |

-| Spanish (Bolivia) | `es-BO` |

-| Spanish (Chile) | `es-CL` |

-| Spanish (Colombia) | `es-CO` |

-| Spanish (Costa Rica) | `es-CR` |

-| Spanish (Cuba) | `es-CU` |

-| Spanish (Dominican Republic) | `es-DO` |

-| Spanish (Ecuador) | `es-EC` |

-| Spanish (El Salvador) | `es-SV` |

-| Spanish (Equatorial Guinea) | `es-GQ` |

-| Spanish (Guatemala) | `es-GT` |

-| Spanish (Honduras) | `es-HN` |

-| Spanish (Mexico) | `es-MX` |

-| Spanish (Nicaragua) | `es-NI` |

-| Spanish (Panama) | `es-PA` |

-| Spanish (Paraguay) | `es-PY` |

-| Spanish (Peru) | `es-PE` |

-| Spanish (Puerto Rico) | `es-PR` |

-| Spanish (Spain) | `es-ES` |

-| Spanish (Uruguay) | `es-UY` |

-| Spanish (US) | `es-US` |

-| Spanish (Venezuela) | `es-VE` |

-| Swahili (Tanzania) | `sw-TZ` |

-| Swedish (Sweden) | `sv-SE` |

-| Tamil (India) | `ta-IN` |

-| Tamil (Malaysia) | `ta-MY` |

-| Tamil (Singapore) | `ta-SG` |

-| Tamil (Sri Lanka) | `ta-LK` |

-| Telugu (India) | `te-IN` |

-| Thai (Thailand) | `th-TH` |

-| Turkish (Turkey) | `tr-TR` |

-| Ukrainian (Ukraine) | `uk-UA` |

-| Urdu (India) | `ur-IN` |

-| Urdu (Pakistan) | `ur-PK` |

-| Vietnamese (Vietnam) | `vi-VN` |

-## Language identification

-With language identification, you set and get one of the supported locales in the following table. We only compare at the language level, such as English and German. If you include multiple locales of the same language, for example, `en-IN` and `en-US`, we'll only compare English (`en`) with the other candidate languages.

-|Language|Locale (BCP-47)|

-|--|--|

-Arabic|`ar-DZ`<br/>`ar-BH`<br/>`ar-EG`<br/>`ar-IQ`<br/>`ar-OM`<br/>`ar-SY`|

-|Bulgarian|`bg-BG`|

-|Catalan|`ca-ES`|

-|Chinese, Mandarin|`zh-CN`<br/>`zh-TW`|

-|Chinese, Traditional|`zh-HK`|

-|Croatian|`hr-HR`|

-|Czech|`cs-CZ`|

-|Danish|`da-DK`|

-|Dutch|`nl-NL`|

-|English|`en-AU`<br/>`en-CA`<br/>`en-GH`<br/>`en-HK`<br/>`en-IN`<br/>`en-IE`<br/>`en-KE`<br/>`en-NZ`<br/>`en-NG`<br/>`en-PH`<br/>`en-SG`<br/>`en-ZA`<br/>`en-TZ`<br/>`en-GB`<br/>`en-US`|

-|Estonian|`et-EE`|

-|Finnish|`fi-FI`|

-|French|`fr-CA`<br/>`fr-FR`|

-|German|`de-DE`|

-|Greek|`el-GR`|

-|Gujarati|`gu-IN`|

-|Hindi|`hi-IN`|

-|Hungarian|`hu-HU`|

-|Indonesian|`id-ID`|

-|Irish|`ga-IE`|

-|Italian|`it-IT`|

-|Japanese|`ja-JP`|

-|Korean|`ko-KR`|

-|Latvian|`lv-LV`|

-|Lithuanian|`lt-LT`|

-|Maltese|`mt-MT`|

-|Marathi|`mr-IN`|

-|Norwegian|`nb-NO`|

-|Polish|`pl-PL`|

-|Portuguese|`pt-BR`<br/>`pt-PT`|

-|Romanian|`ro-RO`|

-|Russian|`ru-RU`|

-|Slovak|`sk-SK`|

-|Slovenian|`sl-SI`|

-|Spanish|`es-AR`<br/>`es-BO`<br/>`es-CL`<br/>`es-CO`<br/>`es-CR`<br/>`es-CU`<br/>`es-DO`<br/>`es-EC`<br/>`es-SV`<br/>`es-GQ`<br/>`es-GT`<br/>`es-HN`<br/>`es-MX`<br/>`es-NI`<br/>`es-PA`<br/>`es-PY`<br/>`es-PE`<br/>`es-PR`<br/>`es-ES`<br/>`es-UY`<br/>`es-US`<br/>`es-VE`|

-|Swedish|`sv-SE`|

-|Tamil|`ta-IN`|

-|Telugu|`te-IN`|

-|Thai|`th-TH`|

-|Turkish|`tr-TR`|

-|Ukrainian|`uk-UA`|

-## Pronunciation assessment

-The following table lists the released languages and public preview languages.

-| Language | Locale |

-|--|--|

-|Chinese (Mandarin, Simplified)|`zh-CN`^{Public preview} |

-|English (Australia)|`en-AU`^{Public preview} |

-|English (United Kingdom)|`en-GB`^{Public preview} |

-|English (United States)|`en-US`^{General available}|

-|French (France)|`fr-FR`^{Public preview} |

-|German (Germany)|`de-DE`^{Public preview} |

-|Spanish (Spain)|`es-ES`^{Public preview} |

-> [!NOTE]

-> For pronunciation assessment, `en-US` and `en-GB` are available inΓÇ»[all regions](regions.md#speech-service), `zh-CN` is available in East Asia and Southeast Asia regions, `de-DE`, `es-ES`, and `fr-FR` are available in West Europe region, and `en-AU` is available in Australia East region.

-## Speech translation

-Speech Translation supports different languages for speech-to-speech and speech-to-text translation. The available target languages depend on whether the translation target is speech or text.

-To set the input speech recognition language, specify the full locale with a dash (`-`) separator. See the [speech-to-text language table](#speech-to-text) above. The default language is `en-US` if you don't specify a language.

-To set the translation target language, with few exceptions you only specify the language code that precedes the locale dash (`-`) separator. For example, use `es` for Spanish (Spain) instead of `es-ES`. See the speech translation target language table below. The default language is `en` if you don't specify a language.

-### Text languages

-| Text language | Language code |

-|:|:-:|

-| Afrikaans | `af` |

-| Albanian | `sq` |

-| Amharic | `am` |

-| Arabic | `ar` |

-| Armenian | `hy` |

-| Assamese | `as` |

-| Azerbaijani | `az` |

-| Bangla | `bn` |

-| Bosnian (Latin) | `bs` |

-| Bulgarian | `bg` |

-| Cantonese (Traditional) | `yue` |

-| Catalan | `ca` |

-| Chinese (Literary) | `lzh` |

-| Chinese Simplified | `zh-Hans` |

-| Chinese Traditional | `zh-Hant` |

-| Croatian | `hr` |

-| Czech | `cs` |

-| Danish | `da` |

-| Dari | `prs` |

-| Dutch | `nl` |

-| English | `en` |

-| Estonian | `et` |

-| Fijian | `fj` |

-| Filipino | `fil` |

-| Finnish | `fi` |

-| French | `fr` |

-| French (Canada) | `fr-ca` |

-| German | `de` |

-| Greek | `el` |

-| Gujarati | `gu` |

-| Haitian Creole | `ht` |

-| Hebrew | `he` |

-| Hindi | `hi` |

-| Hmong Daw | `mww` |

-| Hungarian | `hu` |

-| Icelandic | `is` |

-| Indonesian | `id` |

-| Inuktitut | `iu` |

-| Irish | `ga` |

-| Italian | `it` |

-| Japanese | `ja` |

-| Kannada | `kn` |

-| Kazakh | `kk` |

-| Khmer | `km` |

-| Klingon | `tlh-Latn` |

-| Klingon (plqaD) | `tlh-Piqd` |

-| Korean | `ko` |

-| Kurdish (Central) | `ku` |

-| Kurdish (Northern) | `kmr` |

-| Lao | `lo` |

-| Latvian | `lv` |

-| Lithuanian | `lt` |

-| Malagasy | `mg` |

-| Malay | `ms` |

-| Malayalam | `ml` |

-| Maltese | `mt` |

-| Maori | `mi` |

-| Marathi | `mr` |

-| Myanmar | `my` |

-| Nepali | `ne` |

-| Norwegian | `nb` |

-| Odia | `or` |

-| Pashto | `ps` |

-| Persian | `fa` |

-| Polish | `pl` |

-| Portuguese (Brazil) | `pt` |

-| Portuguese (Portugal) | `pt-pt` |

-| Punjabi | `pa` |

-| Queretaro Otomi | `otq` |

-| Romanian | `ro` |

-| Russian | `ru` |

-| Samoan | `sm` |

-| Serbian (Cyrillic) | `sr-Cyrl` |

-| Serbian (Latin) | `sr-Latn` |

-| Slovak | `sk` |

-| Slovenian | `sl` |

-| Spanish | `es` |

-| Swahili | `sw` |

-| Swedish | `sv` |

-| Tahitian | `ty` |

-| Tamil | `ta` |

-| Telugu | `te` |

-| Thai | `th` |

-| Tigrinya | `ti` |

-| Tongan | `to` |

-| Turkish | `tr` |

-| Ukrainian | `uk` |

-| Urdu | `ur` |

-| Vietnamese | `vi` |

-| Welsh | `cy` |

-| Yucatec Maya | `yua` |

-## Speaker recognition

-Speaker recognition is mostly language agnostic. We built a universal model for text-independent speaker recognition by combining various data sources from multiple languages. We've tuned and evaluated the model on the languages and locales that appear in the following table. For more information on speaker recognition, see the [overview](speaker-recognition-overview.md).

-| Language | Locale (BCP-47) | Text-dependent verification | Text-independent verification | Text-independent identification |

-|-|-|-|-|-|

-|English (US) | `en-US` | Yes | Yes | Yes |

-|Chinese (Mandarin, simplified) | `zh-CN` | n/a | Yes | Yes|

-|English (Australia) | `en-AU` | n/a | Yes | Yes|

-|English (Canada) | `en-CA` | n/a | Yes | Yes|

-|English (India) | `en-IN` | n/a | Yes | Yes|

-|English (UK) | `en-GB` | n/a | Yes | Yes|

-|French (Canada) | `fr-CA` | n/a | Yes | Yes|

-|French (France) | `fr-FR` | n/a | Yes | Yes|

-|German (Germany) | `de-DE` | n/a | Yes | Yes|

-|Italian | `it-IT` | n/a | Yes | Yes|

-|Japanese | `ja-JP` | n/a | Yes | Yes|

-|Portuguese (Brazil) | `pt-BR` | n/a | Yes | Yes|

-|Spanish (Mexico) | `es-MX` | n/a | Yes | Yes|

-|Spanish (Spain) | `es-ES` | n/a | Yes | Yes|

-## Custom keyword and keyword verification

-The following table outlines supported languages for custom keyword and keyword verification.

-| Language | Locale (BCP-47) | Custom keyword | Keyword verification |

-| -- | | -- | -- |

-| Chinese (Mandarin, Simplified) | zh-CN | Yes | Yes |

-| English (United States) | en-US | Yes | Yes |

-| Japanese (Japan) | ja-JP | No | Yes |

-| Portuguese (Brazil) | pt-BR | No | Yes |

-## Intent Recognition Pattern Matcher

-The Intent Recognizer Pattern Matcher supports the following locales:

-| Locale | Locale (BCP-47) |

-|--|--|

-| English (United States) | `en-US` |

-| Chinese (Cantonese, Traditional) | `zh-HK` |

-| Chinese (Mandarin, Simplified) | `zh-CN` |

-The Long Audio API supports a subset of [Public Neural Voices](./language-support.md#prebuilt-neural-voices) and [Custom Neural Voices](./language-support.md#custom-neural-voice).

-* Replace `<locale>` with the desired output locale. For more information, see [language support](language-support.md#prebuilt-neural-voices).

-> We are retiring the standard voices from September 1, 2021 through August 31, 2024. If you used a standard voice with your Speech resource prior to September 1, 2021 then you can continue to do so until August 31, 2024. All other Speech resources can only use prebuilt neural voices. You can choose from the supported [neural voice names](language-support.md#prebuilt-neural-voices). After August 31, the standard voices won't be supported with any Speech resource.

-1. Choose a supported [language](language-support.md#pronunciation-assessment) that you want to evaluate the pronunciation.

-Check the [public voices available](./language-support.md#prebuilt-neural-voices). You can also change the sample code above if you would like to fail over to a different voice or in a different region.

-| `language` | Identifies the spoken language that's being recognized. See [Supported languages](language-support.md#speech-to-text). | Required |

-> [Voices in preview](language-support.md#prebuilt-neural-voices-in-preview) are available in only these three regions: East US, West Europe, and Southeast Asia.

-If you're using a custom neural voice, the body of a request can be sent as plain text (ASCII or UTF-8). Otherwise, the body of each `POST` request is sent as [SSML](speech-synthesis-markup.md). SSML allows you to choose the voice and language of the synthesized speech that the text-to-speech feature returns. For a complete list of supported voices, see [Language and voice support for the Speech service](language-support.md#text-to-speech).

-| What languages are supported? | See [Speaker recognition language support](language-support.md#speaker-recognition). |

-| Speech-to-text | Analyzes sentiment and transcribes continuous real-time speech or batch audio recordings with intermediate results. | 3.4.0 | Generally available |

-| Custom speech-to-text | Using a custom model from the [Custom Speech portal](https://speech.microsoft.com/customspeech), transcribes continuous real-time speech or batch audio recordings into text with intermediate results. | 3.4.0 | Generally available |

-| Neural text-to-speech | Converts text to natural-sounding speech by using deep neural network technology, which allows for more natural synthesized speech. | 2.3.0 | Generally available |

-> When you construct a neural text-to-speech HTTP POST, the [SSML](speech-synthesis-markup.md) message requires a `voice` element with a `name` attribute. The value is the corresponding container locale and voice, which is also known as the [short name](language-support.md#prebuilt-neural-voices). For example, the `latest` tag would have a voice name of `en-US-AriaNeural`.

-* [Voice Gallery](https://aka.ms/speechstudio/voicegallery): Build apps and services that speak naturally. Choose from a broad portfolio of [languages, voices, and variants](language-support.md#prebuilt-neural-voices). Bring your scenarios to life with highly expressive and human-like neural voices.

-Use a humanlike neural voice or create your own custom neural voice unique to your product or brand. For a complete list of supported languages, locales, and voices, see [Language support](language-support.md). To learn more about using a prebuilt neural voice and a custom neural voice, see [Text-to-speech overview](text-to-speech.md).

-| `name` | Identifies the voice used for text-to-speech output. For a complete list of supported voices, see [Language support](language-support.md#text-to-speech). | Required |

-> This example uses the `en-US-JennyNeural` voice. For a complete list of supported voices, see [Language support](language-support.md#text-to-speech).

-| `name` | Identifies the voice used for text-to-speech output. For a complete list of supported voices, see [Language support](language-support.md#text-to-speech). | Required |

-|`style="advertisement-upbeat"`|Expresses an excited and high-energy tone for promoting a product or service.|

-|`style="sports-commentary"`|Expresses a relaxed and interesting tone for broadcasting a sports event.|

-|`style="sports-commentary-excited"`|Expresses an intensive and energetic tone for broadcasting exciting moments in a sports event.|

-The intensity of speaking style can be adjusted to better fit your use case. You specify a stronger or softer style with the `styledegree` attribute to make the speech more expressive or subdued. Speaking style degree adjustments are supported for Chinese (Mandarin, Simplified) neural voices.

-Apart from adjusting the speaking styles and style degree, you can also adjust the `role` parameter so that the voice imitates a different age and gender. For example, a male voice can raise the pitch and change the intonation to imitate a female voice, but the voice name won't be changed. Role adjustments are supported for these Chinese (Mandarin, Simplified) neural voices:

-* `zh-CN-XiaomoNeural`

-* `zh-CN-XiaoxuanNeural`

-* `zh-CN-YunxiNeural`

-* `zh-CN-YunyeNeural`

-[Language support: Voices, locales, languages](language-support.md)

-Speech-to-text, also known as speech recognition, enables real-time or offline transcription of audio streams into text. For a full list of available speech-to-text languages, see [Language and voice support for the Speech service](language-support.md#speech-to-text).

-Customization options vary by language or locale. To verify support, see [Language and voice support for the Speech service](./language-support.md).

-For a list of languages supported for speech translation, see [Language and voice support](language-support.md#speech-translation).

-These examples presume that you're testing in English. However, Speech service supports speech synthesis in many languages. You can pull down a full list of voices either by running the following command or by visiting the [language support page](./language-support.md).

-> For a list of all supported languages and their corresponding locale codes, see [Language and voice support for the Speech service](language-support.md).

-Text-to-speech enables your applications, tools, or devices to convert text into humanlike synthesized speech. The text-to-speech capability is also known as speech synthesis. Use humanlike prebuilt neural voices out of the box, or create a custom neural voice that's unique to your product or brand. For a full list of supported voices, languages, and locales, see [Language and voice support for the Speech service](language-support.md#text-to-speech).

-* **Real-time speech synthesis**: Use the [Speech SDK](./get-started-text-to-speech.md) or [REST API](rest-text-to-speech.md) to convert text-to-speech by using [prebuilt neural voices](language-support.md#text-to-speech) or [custom neural voices](custom-neural-voice.md).

- For a full list of platform neural voices, see [Language and voice support for the Speech service](language-support.md#text-to-speech).

- By using viseme events in Speech SDK, you can generate facial animation data. This data can be used to animate faces in lip-reading communication, education, entertainment, and customer service. Viseme is currently supported only for the `en-US` (US English) [neural voices](language-support.md#text-to-speech).

-You can choose from any of the languages mentioned in the [speech-to-text](language-support.md#speech-to-text) table. The following example changes the language to German.

-1. Open the Windows Voice Assistant Client app, select the **Settings** button (upper-right gear icon), and enter **de-de** in the **Language** field. This is the locale value mentioned in the [speech-to-text](language-support.md#speech-to-text) table.

-The following example adds SSML to the echo bot reply so that the German voice Stefan Apollo (a male voice) is used instead of the default female voice. See the [list of standard voices](how-to-migrate-to-prebuilt-neural-voice.md) and [list of neural voices](language-support.md#prebuilt-neural-voices) that are supported for your language.

-| `GetLanguagesForSpeak` | [Microsoft Speech Service](../speech-service/language-support.md#text-to-speech) |

-Release note for `3.4.0-amd64`:

-* Support for latest model versions.

-| `latest` | | `sha256:d436d62c423d7a3062a2b13b7f774e4c50a32887c987ec5d4476224810c62086`|

-| `3.4.0-amd64` | | `sha256:d436d62c423d7a3062a2b13b7f774e4c50a32887c987ec5d4476224810c62086`|

-# [Previous version](#tab/previous)

-Release notes for `v2.3.0`:

-| `2.3.0-amd64-<locale-and-voice>` | Replace `<locale>` with one of the available locales, listed below. For example `2.3.0-amd64-en-us-arianeural`. |

-| v2.3.0 Locales and voices | Notes |

-* A new version of the Language API (`2022-07-15-preview`) has been released. It provides:

- * Automatic language detection for asynchronous tasks.

- <your-language-resource-endpoint>/language/:analyze-text?api-version=2022-07-15-preview`

-* [Speech Service: Speech-to-Text](./speech-service/language-support.md#speech-to-text)

-* [Speech Service:Text-to-Speech](./speech-service/language-support.md#text-to-speech)

-* [Speech Service: Speech Translation](./speech-service/language-support.md#speech-translation)

-### Using the REST API

-### Using PowerShell

-### Using the Azure CLI

-### Using the REST API

-### Using PowerShell

-### Using the Azure CLI

-* [Create a new resource using an ARM template](create-account-resource-manager-template.md)

-* Has an _event_ ID. If you already have an event ID, you should submit that. If you do not have an event ID, do not send one, Personalizer creates one for you and returns it in the response of the Rank request. The ID is associated with the Rank event, not the user. If you create an ID, a GUID works best.

-1. Copy the Baltimore CyberTrust Root certificate details from [https://baltimore-cybertrust-root.chain-demos.digicert.com/info/https://docsupdatetracker.net/index.html](https://baltimore-cybertrust-root.chain-demos.digicert.com/info/https://docsupdatetracker.net/index.html) into a text file. Save the file using the file extension *.cer*.

-> [Import Cassandra data into Azure Cosmos DB](migrate-data.md)

-* [Change feed processor start time](#starting-time)

- pip install --pre azure-cosmos

-> [Import data into Azure Cosmos DB for the SQL API](../import-data.md)

-## Spring Boot support policy

-Azure Spring Data Cosmos supports multiple [Spring Boot Versions](https://aka.ms/spring/versions). For complete list of currently supported versions, please visit our [Spring Version Mapping](https://aka.ms/spring/versions).

-Spring Boot releases are marked as "End of Life" when they are no longer supported or released in any form. If you are running an EOL version, you should upgrade as soon as possible.

-Please note that a version can be out of support before it is marked as "End of Life." During this time you should only expect releases for critical bugs or security issues.

-For more information on Spring Boot supported versions, please visit [Spring Boot Supported Versions](https://github.com/spring-projects/spring-boot/wiki/Supported-Versions).

-> [!IMPORTANT]

-> * The 3.5.0 release supports Spring Boot 2.4.3 and above.

-* Spring Data 2.3 is currently supported, Spring Data 2.4 is not supported currently.

-Set-AzDataFactoryV2 -InputObject $dataFactory -Force

-Gets the current date when this job starts to run. You can pass an optional timezone in the form of 'GMT', 'PST', 'UTC', 'America/Cayman'. The local timezone is used as the default. Refer to Java's `SimpleDateFormat` class for available formats. [https://docs.oracle.com/javase/8/docs/api/java/text/SimpleDateFormat.html](https://docs.oracle.com/javase/8/docs/api/java/text/SimpleDateFormat.html).

- :::image type="content" source="./media/doc-common-process/get-started-page.png" alt-text="Screenshot that shows the ADF home page.":::

-> You will need to enable multifactor authentication for the user who manages the VMs and images that are deployed on your device from the cloud. The cloud operations will fail if the user doesn't have multifactor authentication enabled. For steps to enable multifactor authentication click [here](/azure/active-directory/authentication/tutorial-enable-azure-mfa.md)

-The relevant API documentation is available in [the Adaptive application Controls section of Defender for Cloud's API docs](/rest/api/securitycenter/adaptiveapplicationcontrols).

-For full details and usage examples, see the [API documentation](/rest/api/securitycenter/).

-You can also manage your email notifications through the supplied REST API. For full details see the [SecurityContacts API documentation](/rest/api/securitycenter/securitycontacts).

-Continuous export can be configured and managed via the Microsoft Defender for Cloud [automations API](/rest/api/securitycenter/automations). Use this API to create or update rules for exporting to any of the following possible destinations:

-Learn more about the automations API in the [REST API documentation](/rest/api/securitycenter/automations).

-For another example of using the securityCenter property, see [this section of the REST API documentation](/rest/api/securitycenter/assessmentsmetadata/createinsubscription#examples).

-| [Microsoft Defender for Cloud REST API](/rest/api/securitycenter/) | Security alerts, security recommendations, and more. |

-Yes. The results are under [Sub-Assessments REST API](/rest/api/securitycenter/subassessments/list/). Also, you can use Azure Resource Graph (ARG), the Kusto-like API for all of your resources: a query can fetch a specific scan.

-To set up the scanner, you'll need to enable **Microsoft Defender for container registries** and the CI/CD integration. When your CI/CD workflows push images to your registries, you can view registry scan results and a summary of CI/CD scan results.

-Yes. The results are under [Sub-Assessments REST API](/rest/api/securitycenter/subassessments/list/). Also, you can use Azure Resource Graph (ARG), the Kusto-like API for all of your resources: a query can fetch a specific scan.

-| REST API | [Pricings API](/rest/api/securitycenter/pricings) |

-You can also enable the MDE unified solution at scale through the supplied REST API version 2022-05-01. For full details see the [API documentation](/rest/api/securitycenter/settings/update?tabs=HTTP).

-Learn more at [JIT network access policies](/rest/api/securitycenter/jitnetworkaccesspolicies).

-Learn more at [JIT network access policies](/rest/api/securitycenter/jitnetworkaccesspolicies).

-> Alternatively, you can use the Defender for Cloud REST API method [Assessments - Get](/rest/api/securitycenter/assessments/get).

-|Pricing:|The **CSPM plan** is free.<br>The **[Defender for SQL](defender-for-sql-introduction.md)** plan is billed at the same price as Azure resources.<br>The **[Defender for Containers](defender-for-containers-introduction.md)** plan is free during the preview. After which, it will be billed for AWS at the same price as for Azure resources.<br>For every AWS machine connected to Azure with [Azure Arc-enabled servers](../azure-arc/servers/overview.md), the **Defender for Servers** plan is billed at the same price as the [Microsoft Defender for Servers](defender-for-servers-introduction.md) plan for Azure machines. If an AWS EC2 doesn't have the Azure Arc agent deployed, you won't be charged for that machine.|

-Yes. To create, edit, or delete Defender for Cloud cloud connectors with a REST API, see the details of the [Connectors API](/rest/api/securitycenter/security-connectors).

-We've added the following two fields to the [Assessments REST API](/rest/api/securitycenter/assessments):

-Learn more about the [Assessments REST API](/rest/api/securitycenter/assessments).

-You can now access your score via the [secure score API](/rest/api/securitycenter/securescores/). The API methods provide the flexibility to query the data and build your own reporting mechanism of your secure scores over time. For example:

-You can now access your score via the [secure score API](/rest/api/securitycenter/securescores/) (currently in preview). The API methods provide the flexibility to query the data and build your own reporting mechanism of your secure scores over time. For example, you can use the **Secure Scores** API to get the score for a specific subscription. In addition, you can use the **Secure Score Controls** API to list the security controls and the current score of your subscriptions.

-You can access your score via the secure score API. The API methods provide the flexibility to query the data and build your own reporting mechanism of your secure scores over time. For example, you can use the [Secure Scores API](/rest/api/securitycenter/securescores) to get the score for a specific subscription. In addition, you can use the [Secure Score Controls API](/rest/api/securitycenter/securescorecontrols) to list the security controls and the current score of your subscriptions.

-These three APIs exposed old formats of assessments and will be replaced by the [Assessments APIs](/rest/api/securitycenter/assessments) and [SubAssessments APIs](/rest/api/securitycenter/sub-assessments). All data that is exposed by these legacy APIs will also be available in the new APIs.

-6. Confirm that you see the site but no events have been posted to it yet.

-1. Select **+ Container**. Give you container a name, and use any access level, and select **Create**.

-There can be at most 5 concurrent readers on a partition per consumer group; however **it's recommended that there's only one active receiver on a partition per consumer group**. Within a single partition, each reader receives all of the messages. If you have multiple readers on the same partition, then you process duplicate messages. You need to handle this in your code, which may not be trivial. However, it's a valid approach in some scenarios.

-> * IPv6 support for ExpressRoute Global Reach is now in Public Preview. See [Enable Global Reach](expressroute-howto-set-global-reach.md) to learn more.

-> [!NOTE]

-> IPv6 support for ExpressRoute Global Reach is now in Public Preview. See [Enable Global Reach](expressroute-howto-set-global-reach.md) for steps to configure this feature using PowerShell.

-> [!NOTE]

-> IPv6 support for ExpressRoute Global Reach is now in Public Preview.

- > IPv6 support for ExpressRoute Global Reach is now in Public Preview. If you want to enable this feature for test workloads, select "Both" for the *Subnets* field and include a **/125 IPv6** subnet for the *Global Reach IPv6 subnet*.

- > IPv6 support for ExpressRoute Global Reach is now in Public Preview. If you want to enable this feature for test workloads, select "Both" for the *Subnets* field and include a **/125 IPv6** subnet for the *Global Reach IPv6 subnet*.

-> [!NOTE]

-> Global Reach does **not** support configuration updates at this time. This means that if you create a Global Reach connection using the following instructions, you must delete and recreate the connection with any configuration updates. Attempting to update an existing Global Reach connection will put your ExpressRoute circuit in a failed state.

->

- > IPv6 support for ExpressRoute Global Reach is now in Public Preview. To add an IPv6 Global Reach connection, you must specify a /125 IPv6 subnet for *-AddressPrefix* and an *-AddressPrefixType* of *IPv6*.

- > [!NOTE]

- > IPv6 support for ExpressRoute Global Reach is now in Public Preview. To add an IPv6 Global Reach connection, you must specify a /125 IPv6 subnet for *-AddressPrefix* and an *-AddressPrefixType* of *IPv6*.

-> IPv6 support for ExpressRoute Global Reach is now in Public Preview. To delete an IPv6 Global Reach connection, you must specify an *-AddressPrefixType* of *IPv6* like in the following command.

-The Azure public peering path enables you to connect to all services hosted in Azure over their public IP addresses. These include services listed in the [ExpessRoute FAQ](expressroute-faqs.md) and any services hosted by ISVs on Microsoft Azure. Connectivity to Microsoft Azure services on public peering is always initiated from your network into the Microsoft network. You must use Public IP addresses for the traffic destined to Microsoft network.

-description: In this article, you learn about geo-filtering policy for Azure Front Door

-# Geo-filtering on a domain for Azure Front Door

-By default, Azure Front Door will respond to all user requests regardless of the location where the request is coming from. In some scenarios, you may want to restrict the access to your web application by countries/regions. The Web application firewall (WAF) service in Front Door enables you to define a policy using custom access rules for a specific path on your endpoint to either allow or block access from specified countries/regions.

-A WAF policy contains a set of custom rules. The rule consists of match conditions, an action, and a priority. In a match condition, you define a match variable, operator, and match value. For a geo filtering rule, a match variable is REMOTE_ADDR, the operator is GeoMatch, and the value is a two letter country/region code of interest. "ZZ" country code or "Unknown" country captures IP addresses that are not yet mapped to a country in our dataset. You may add ZZ to your match condition to avoid false positives. You can combine a GeoMatch condition and a REQUEST_URI string match condition to create a path-based geo-filtering rule.

-You can configure a geo-filtering policy for your Front Door by using [Azure PowerShell](front-door-tutorial-geo-filtering.md) or by using a [quickstart template](https://github.com/Azure/azure-quickstart-templates/tree/master/quickstarts/microsoft.network/front-door-geo-filtering).

-> [!IMPORTANT]

-> Include the country code **ZZ** whenever you use geo-filtering. The **ZZ** country code (or *Unknown* country) captures IP addresses that are not yet mapped to a country in our dataset. This avoids false positives.

-## Country/Region code reference

-|Country/Region code | Country/Region name |

-| -- | -- |

-| AD | Andorra |

-| AE | United Arab Emirates|

-| AF | Afghanistan|

-| AG | Antigua and Barbuda|

-| AL | Albania|

-| AM | Armenia|

-| AO | Angola|

-| AR | Argentina|

-| AS | American Samoa|

-| AT | Austria|

-| AU | Australia|

-| AZ | Azerbaijan|

-| BA | Bosnia and Herzegovina|

-| BB | Barbados|

-| BD | Bangladesh|

-| BE | Belgium|

-| BF | Burkina Faso|

-| BG | Bulgaria|

-| BH | Bahrain|

-| BI | Burundi|

-| BJ | Benin|

-| BL | Saint Barthélemy|

-| BN | Brunei Darussalam|

-| BO | Bolivia|

-| BR | Brazil|

-| BS | Bahamas|

-| BT | Bhutan|

-| BW | Botswana|

-| BY | Belarus|

-| BZ | Belize|

-| CA | Canada|

-| CD | Democratic Republic of the Congo|

-| CG | Republic of the Congo |

-| CF | Central African Republic|

-| CH | Switzerland|

-| CI | Cote d'Ivoire|

-| CL | Chile|

-| CM | Cameroon|

-| CN | China|

-| CO | Colombia|

-| CR | Costa Rica|

-| CU | Cuba|

-| CV | Cabo Verde|

-| CY | Cyprus|

-| CZ | Czech Republic|

-| DE | Germany|

-| DK | Denmark|

-| DO | Dominican Republic|

-| DZ | Algeria|

-| EC | Ecuador|

-| EE | Estonia|

-| EG | Egypt|

-| ES | Spain|

-| ET | Ethiopia|

-| FI | Finland|

-| FJ | Fiji|

-| FM | Micronesia, Federated States of|

-| FR | France|

-| GB | United Kingdom|

-| GE | Georgia|

-| GF | French Guiana|

-| GH | Ghana|

-| GN | Guinea|

-| GP | Guadeloupe|

-| GR | Greece|

-| GT | Guatemala|

-| GY | Guyana|

-| HK | Hong Kong SAR|

-| HN | Honduras|

-| HR | Croatia|

-| HT | Haiti|

-| HU | Hungary|

-| ID | Indonesia|

-| IE | Ireland|

-| IL | Israel|

-| IN | India|

-| IQ | Iraq|

-| IR | Iran, Islamic Republic of|

-| IS | Iceland|

-| IT | Italy|

-| JM | Jamaica|

-| JO | Jordan|

-| JP | Japan|

-| KE | Kenya|

-| KG | Kyrgyzstan|

-| KH | Cambodia|

-| KI | Kiribati|

-| KN | Saint Kitts and Nevis|

-| KP | Korea, Democratic People's Republic of|

-| KR | Korea, Republic of|

-| KW | Kuwait|

-| KY | Cayman Islands|

-| KZ | Kazakhstan|

-| LA | Lao People's Democratic Republic|

-| LB | Lebanon|

-| LI | Liechtenstein|

-| LK | Sri Lanka|

-| LR | Liberia|

-| LS | Lesotho|

-| LT | Lithuania|

-| LU | Luxembourg|

-| LV | Latvia|

-| LY | Libya |

-| MA | Morocco|

-| MD | Moldova, Republic of|

-| MG | Madagascar|

-| MK | North Macedonia|

-| ML | Mali|

-| MM | Myanmar|

-| MN | Mongolia|

-| MO | Macao SAR|

-| MQ | Martinique|

-| MR | Mauritania|

-| MT | Malta|

-| MV | Maldives|

-| MW | Malawi|

-| MX | Mexico|

-| MY | Malaysia|

-| MZ | Mozambique|

-| NA | Namibia|

-| NE | Niger|

-| NG | Nigeria|

-| NI | Nicaragua|

-| NL | Netherlands|

-| NO | Norway|

-| NP | Nepal|

-| NR | Nauru|

-| NZ | New Zealand|

-| OM | Oman|

-| PA | Panama|

-| PE | Peru|

-| PH | Philippines|

-| PK | Pakistan|

-| PL | Poland|

-| PR | Puerto Rico|

-| PT | Portugal|

-| PW | Palau|

-| PY | Paraguay|

-| QA | Qatar|

-| RE | Reunion|

-| RO | Romania|

-| RS | Serbia|

-| RU | Russian Federation|

-| RW | Rwanda|

-| SA | Saudi Arabia|

-| SD | Sudan|

-| SE | Sweden|

-| SG | Singapore|

-| SI | Slovenia|

-| SK | Slovakia|

-| SN | Senegal|

-| SO | Somalia|

-| SR | Suriname|

-| SS | South Sedan|

-| SV | El Salvador|

-| SY | Syrian Arab Republic|

-| SZ | Swaziland|

-| TC | Turks and Caicos Islands|

-| TG | Togo|

-| TH | Thailand|

-| TN | Tunisia|

-| TR | Turkey|

-| TT | Trinidad and Tobago|

-| TW | Taiwan|

-| TZ | Tanzania, United Republic of|

-| UA | Ukraine|

-| UG | Uganda|

-| US | United States|

-| UY | Uruguay|

-| UZ | Uzbekistan|

-| VC | Saint Vincent and the Grenadines|

-| VE | Venezuela|

-| VG | Virgin Islands, British|

-| VI | Virgin Islands, U.S.|

-| VN | Vietnam|

-| ZA | South Africa|

-| ZM | Zambia|

-| ZW | Zimbabwe|

-## Next steps

-description: Learn about the Apache Hadoop components and versions in Azure HDInsight.

-HDInsight bundles Apache Hadoop environment components and HDInsight platform into a package that is deployed on a cluster. For more information, see [how HDInsight versioning works](hdinsight-overview-versioning.md).

-**Support expiration** means that Microsoft no longer provides support for the specific HDInsight version. And it may no longer available through the Azure portal for cluster creation.

-**Retirement** means that existing clusters of an HDInsight version continue to run as is. New clusters of this version can't be created through any means, which includes the CLI and SDKs. Other control plane features, such as manual scaling and autoscaling, are not guaranteed to work after retirement date. Support isn't available for retired versions.

-Standard support includes the following:

-Basic support provides limited servicing to the HDInsight Resource provider. HDInsight images and open-source software (OSS) components will not be serviced. Only critical security fixes will be patched on HDInsight clusters.

-Basic support includes the following:

-Basic support does not include the following:

-Microsoft does not encourage creating analytics pipelines or solutions on clusters in basic support. We recommend migrating existing clusters to the most recent fully supported version.

-For additional release notes on the latest versions of HDInsight, see [HDInsight release notes](hdinsight-release-notes.md).

-The FHIR specification defines a set of search parameters for all resources and search parameters that are specific to a resource(s). However, there are scenarios where you might want to search against an element in a resource that isnΓÇÖt defined by the FHIR specification as a standard search parameter. This article describes how you can define your own [search parameters](https://www.hl7.org/fhir/searchparameter.html) to be used in the FHIR service in Azure Health Data Services (hereby called FHIR service).

-> Each time you create, update, or delete a search parameter youΓÇÖll need to run a [reindex job](how-to-run-a-reindex.md) to enable the search parameter to be used in production. Below we will outline how you can test search parameters before reindexing the entire FHIR service.

-To create a new search parameter, you `POST` the `SearchParameter` resource to the database. The code example below shows how to add the [US Core Race SearchParameter](http://hl7.org/fhir/us/core/STU3.1.1/SearchParameter-us-core-race.html) to the `Patient` resource.

-> The new search parameter will appear in the capability statement of the FHIR service after you POST the search parameter to the database **and** reindex your database. Viewing the `SearchParameter` in the capability statement is the only way tell if a search parameter is supported in your FHIR service. If you can find the search parameter by searching for the search parameter but cannot see it in the capability statement, you still need to index the search parameter. You can POST multiple search parameters before triggering a reindex operation.

-Important elements of a `SearchParameter`:

-* **url**: A unique key to describe the search parameter. Many organizations, such as HL7, use a standard URL format for the search parameters that they define, as shown above in the US Core race search parameter.

-* **code**: The value stored in **code** is what youΓÇÖll use when searching. For the example above, you would search with `GET {FHIR_URL}/Patient?race=<code>` to get all patients of a specific race. The code must be unique for the resource(s) the search parameter applies to.

-* **base**: Describes which resource(s) the search parameter applies to. If the search parameter applies to all resources, you can use `Resource`; otherwise, you can list all the relevant resources.

-* **type**: Describes the data type for the search parameter. Type is limited by the support for the FHIR service. This means that you canΓÇÖt define a search parameter of type Special or define a [composite search parameter](overview-of-search.md) unless it's a supported combination.

-* **expression**: Describes how to calculate the value for the search. When describing a search parameter, you must include the expression, even though it isn't required by the specification. This is because you need either the expression or the xpath syntax and the FHIR service ignores the xpath syntax.

-## Test search parameters

-While you canΓÇÖt use the search parameters in production until you run a reindex job, there are a few ways to test your search parameters before reindexing the entire database.

-First, you can test your new search parameter to see what values will be returned. By running the command below against a specific resource instance (by inputting their ID), you'll get back a list of value pairs with the search parameter name and the value stored. This will include all of the search parameters for the resource and you can scroll through to find the search parameter you created. Running this command won't change any behavior in your FHIR service.

- },

-...

-Once you see that your search parameter is displaying as expected, you can reindex a single resource to test searching with the element. First you'll reindex a single resource:

-Running this, sets the indices for any search parameters for the specific resource that you defined for that resource type. This does make an update to the FHIR service. Now you can search and set the use partial indices header to true, which means that it will return results where any of the resources has the search parameter indexed, even if not all resources of that type have it indexed.

-POST https://{{FHIR_URL}/Patient/{{PATIENT_ID}}/$reindex

-And then search for patients that have a specific race:

-GET https://{{FHIR_URL}}/Patient?race=2028-9

-After you have tested and are satisfied that your search parameter is working as expected, run or schedule your reindex job so the search parameters can be used in the FHIR service for production use cases.

-To update a search parameter, use `PUT` to create a new version of the search parameter. You must include the `SearchParameter ID` in the `id` element of the body of the `PUT` request and in the `PUT` call.

-> If you don't know the ID for your search parameter, you can search for it. Using `GET {{FHIR_URL}}/SearchParameter` will return all custom search parameters, and you can scroll through the search parameter to find the search parameter you need. You could also limit the search by name. With the example below, you could search for name using `USCoreRace: GET {{FHIR_URL}}/SearchParameter?name=USCoreRace`.

-PUT {{FHIR_URL}}/SearchParameter/{SearchParameter ID}

- "id" : "SearchParameter ID",

-The result will be an updated `SearchParameter` and the version will increment.

-> Be careful when updating SearchParameters that have already been indexed in your database. Changing an existing SearchParameterΓÇÖs behavior could have impacts on the expected behavior. We recommend running a reindex job immediately.

-Delete {{FHIR_URL}}/SearchParameter/{SearchParameter ID}

-> Be careful when deleting SearchParameters that have already been indexed in your database. Changing an existing SearchParameterΓÇÖs behavior could have impacts on the expected behavior. We recommend running a reindex job immediately.

-In this article, youΓÇÖve learned how to create a search parameter. Next you can learn how to reindex your FHIR service. For more information, see

-There are scenarios where you may have search or sort parameters in the FHIR service in Azure Health Data Services (hereby called FHIR service) that haven't yet been indexed. This scenario is relevant when you define your own search parameters. Until the search parameter is indexed, it can't be used in search. This article covers an overview of how to run a reindex job to index any search or sort parameters that haven't yet been indexed in your database.

-> It's important that you read this entire article before getting started. A reindex job can be very performance intensive. This article includes options for how to throttle and control the reindex job.

-To start a reindex job, use the following code example:

-POST {{FHIR URL}}/$reindex

-If the request is successful, a status of **201 Created** gets returned. The result of this message will look like:

-> To check the status of or to cancel a reindex job, you'll need the reindex ID. This is the ID of the resulting Parameters resource. In the example above, the ID for the reindex job would be `560c7c61-2c70-4c54-b86d-c53a9d29495e`.

-`GET {{FHIR URL}}/_operations/reindex/{{reindexJobId}`

-The status of the reindex job result is shown below:

- "{LIST OF IMPACTED RESOURCES}"

- },

- {

-The following information is shown in the reindex job result:

-* **totalResourcesToReindex**: Includes the total number of resources that are being reindexed as part of the job.

-* **resourcesSuccessfullyReindexed**: The total that have already been successfully reindexed.

-* **progress**: Reindex job percent complete. Equals resourcesSuccessfullyReindexed/totalResourcesToReindex x 100.

-* **status**: States if the reindex job is queued, running, complete, failed, or canceled.

-* **resources**: Lists all the resource types impacted by the reindex job.

-If you need to cancel a reindex job, use a delete call and specify the reindex job ID:

-`Delete {{FHIR URL}}/_operations/reindex/{{reindexJobId}`

-A reindex job can be quite performance intensive. WeΓÇÖve implemented some throttling controls to help you manage how a reindex job will run on your database.

-Below is a table outlining the available parameters, defaults, and recommended ranges. You can use these parameters to either speedup the process (use more compute) or slow down the process (use less compute).

-| QueryDelayIntervalInMilliseconds | The delay between each batch of resources being kicked off during the reindex job. A smaller number will speed up the job while a higher number will slow it down. | 500 MS (.5 seconds) | 50 to 500000 |

-| MaximumResourcesPerQuery | The maximum number of resources included in the batch of resources to be reindexed. | 100 | 1-5000 |

-| MaximumConcurrency | The number of batches done at a time. | 1 | 1-10 |

-If you want to use any of the parameters above, you can pass them into the Parameters resource when you start the reindex job.

-In this article, you've learned how to start a reindex job. To learn how to define new search parameters that require the reindex job, see

-The Fast Healthcare Interoperability Resources (FHIR&#174;) specification defines the fundamentals of search for FHIR resources. This article will guide you through some key aspects to searching resources in FHIR. For complete details about searching FHIR resources, refer to [Search](https://www.hl7.org/fhir/search.html) in the HL7 FHIR Specification. Throughout this article, we'll give examples of search syntax. Each search will be against your FHIR server, which typically has a URL of `https://<WORKSPACE NAME>-<ACCOUNT-NAME>.fhir.azurehealthcareapis.com`. In the examples, we'll use the placeholder `{{FHIR_URL}}` for this URL.

-FHIR searches can be against a specific resource type, a specified [compartment](https://www.hl7.org/fhir/compartmentdefinition.html), or all resources. The simplest way to execute a search in FHIR is to use a `GET` request. For example, if you want to pull all patients in the database, you could use the following request:

-You can also search using `POST`, which is useful if the query string is too long. To search using `POST`, the search parameters can be submitted as a form body. This allows for longer, more complex series of query parameters that might be difficult to see and understand in a query string.

-If the search request is successful, you'll receive a FHIR bundle response with the type `searchset`. If the search fails, youΓÇÖll find the error details in the `OperationOutcome` to help you understand why the search failed.

-In the following sections, we'll cover the various aspects involved in searching. Once youΓÇÖve reviewed these details, refer to our [samples page](search-samples.md) that has examples of searches that you can make in the FHIR service in the Azure Health Data Services.

-When you do a search, you'll search based on various attributes of the resource. These attributes are called search parameters. Each resource has a set of defined search parameters. The search parameter must be defined and indexed in the database for you to successfully search against it.

-Each search parameter has a defined [data types](https://www.hl7.org/fhir/search.html#ptypes). The support for the various data types is outlined below:

-| **Search parameter type** | **Azure API for FHIR** | **FHIR service in Azure Health Data Services** | **Comment**|

-| composite | Partial | Partial | The list of supported composite types is described later in this article |

-There are [common search parameters](https://www.hl7.org/fhir/search.html#all) that apply to all resources. These are listed below, along with their support:

-| **Common search parameter** | **Azure API for FHIR** | **FHIR service in Azure Health Data Services** | **Comment**|

-| _id | Yes | Yes

-| _lastUpdated | Yes | Yes |

-| _tag | Yes | Yes |

-| _type | Yes | Yes |

-| _security | Yes | Yes |

-| _profile | Yes | Yes |

-| _has | Yes. | Yes | |

-| _query | No | No |

-| _filter | No | No |

-| _list | No | No |

-| _text | No | No |

-| _content | No | No |

-With FHIR service in Azure Health Data Services, we support almost all [resource-specific search parameters](https://www.hl7.org/fhir/searchparameter-registry.html) defined by the FHIR specification. The only search parameters we donΓÇÖt support are available in the links below:

-To see the search parameters in the capability statement, navigate to `CapabilityStatement.rest.resource.searchParam` to see the search parameters for each resource and `CapabilityStatement.rest.searchParam` to find the search parameters for all resources.

-> FHIR service in Azure Health Data Services does not automatically create or index any search parameters that are not defined by the FHIR specification. However, we do provide support for you to to define your own [search parameters](how-to-do-custom-search.md).

-Composite search allows you to search against value pairs. For example, if you were searching for a height observation where the person was 60 inches, you would want to make sure that a single component of the observation contained the code of height **and** the value of 60. You wouldn't want to get an observation where a weight of 60 and height of 48 was stored, even though the observation would have entries that qualified for value of 60 and code of height, just in different component sections.

-With the FHIR service for the Azure Health Data Services, we support the following search parameter type pairings:

-For more information, see the HL7 [Composite Search Parameters](https://www.hl7.org/fhir/search.html#composite).

-> Composite search parameters do not support modifiers per the FHIR specification.

-[Modifiers](https://www.hl7.org/fhir/search.html#modifiers) allow you to modify the search parameter. Below is an overview of all the FHIR modifiers and the support:

-| **Modifiers** | **Azure API for FHIR** | **FHIR service in Azure Health Data Services** | **Comment**|

-| :missing | Yes | Yes |

-| :exact | Yes | Yes |

-| :contains | Yes | Yes |

-| :text | Yes | Yes |

-| :type (reference) | Yes | Yes |

-| :not | Yes | Yes |

-| :below (uri) | Yes | Yes |

-| :above (uri) | Yes | Yes |

-| :in (token) | No | No |

-| :below (token) | No | No |

-| :above (token) | No | No |

-| :not-in (token) | No | No |

-For search parameters that have a specific order (numbers, dates, and quantities), you can use a [prefix](https://www.hl7.org/fhir/search.html#prefix) on the parameter to help with finding matches. The FHIR service in the Azure Health Data Services supports all prefixes.

-To help manage the returned resources, there are search result parameters that you can use in your search. For details on how to use each of the search result parameters, refer to the [HL7](https://www.hl7.org/fhir/search.html#return) website.

-| **Search result parameters** | **Azure API for FHIR** | **FHIR service in Azure Health Data Services** | **Comment**|

-| _elements | Yes | Yes |

-| _count | Yes | Yes | _count is limited to 1000 resources. If it's set higher than 1000, only 1000 will be returned and a warning will be returned in the bundle. |

-| _include | Yes | Yes | Included items are limited to 100. _include on PaaS and OSS on Cosmos DB don't include :iterate support [(#2137)](https://github.com/microsoft/fhir-server/issues/2137). |

-| _revinclude | Yes | Yes |Included items are limited to 100. _revinclude on PaaS and OSS on Cosmos DB don't include :iterate support [(#2137)](https://github.com/microsoft/fhir-server/issues/2137). There's also an incorrect status code for a bad request [#1319](https://github.com/microsoft/fhir-server/issues/1319) |

-| _summary | Yes | Yes |

-| _total | Partial | Partial | _total=none and _total=accurate |

-| _sort | Partial | Partial | sort=_lastUpdated is supported on Azure API for FHIR and the FHIR service. For the FHIR service and the OSS SQL DB FHIR servers, sorting by strings and dateTime fields are supported. For Azure API for FHIR and OSS Cosmos DB databases created after April 20, 2021, sort is supported on first name, last name, birthdate, and clinical date. |

-| _contained | No | No |

-| _containedType | No | No |

-| _score | No | No |

-> By default `_sort` sorts the record in ascending order. You can use the prefix `'-'` to sort in descending order. In addition, the FHIR service and the Azure API for FHIR only allow you to sort on a single field at a time.

-By default, the FHIR service in the Azure Health Data Services is set to lenient handling. This means that the server will ignore any unknown or unsupported parameters. If you want to use strict handling, you can use the **Prefer** header and set `handling=strict`.

-A [chained search](https://www.hl7.org/fhir/search.html#chaining) allows you to search using a search parameter on a resource referenced by another resource. For example, if you want to find encounters where the patientΓÇÖs name is Jane, use:

-Similarly, you can do a reverse chained search. This allows you to get resources where you specify criteria on other resources that refer to them. For more examples of chained and reverse chained search, refer to the [FHIR search examples](search-samples.md) page.

-As mentioned above, the results from a search will be a paged bundle. By default, the search will return 10 results per page, but this can be increased (or decreased) by specifying `_count`. Within the bundle, there will be a self link that contains the current result of the search. If there are more matches, the bundle will contain a next link. You can continue to use the next link to get the subsequent pages of results. `_count` is limited to 1000 items or less.

-Currently, FHIR service in Azure Health Data Services only supports the next link in bundles, and it doesnΓÇÖt support first, last, or previous links.

-Now that you've learned about the basics of search, see the search samples page for details about how to search using different search parameters, modifiers, and other FHIR search scenarios. To read about FHIR search examples, see

-Below are some examples of using Fast Healthcare Interoperability Resources (FHIR&#174;) search operations, including search parameters and modifiers, chain and reverse chain search, composite search, viewing the next entry set for search results, and searching with a `POST` request. For more information about search, see [Overview of FHIR Search](overview-of-search.md).

-### _include

-`_include` searches for resources that include the specified parameter of the resource. For example, you can search across `MedicationRequest` resources to find only the ones that include information about the prescriptions for a specific patient, which is the `reference` parameter `patient`. In the example below, this will pull all the `MedicationRequests` and all patients that are referenced from the `MedicationRequests`:

- GET [your-fhir-server]/MedicationRequest?_include=MedicationRequest:patient

-> **_include** and **_revinclude** are limited to 100 items.

-### _revinclude

-`_revinclude` allows you to search the opposite direction as `_include`. For example, you can search for patients and then reverse include all encounters that reference the patients:

-GET [your-fhir-server]/Patient?_revinclude=Encounter:subject

-### _elements

-`_elements` narrows down the search result to a subset of fields to reduce the response size by omitting unnecessary data. The parameter accepts a comma-separated list of base elements:

-GET [your-fhir-server]/Patient?_elements=identifier,active

-In this request, you'll get back a bundle of patients, but each resource will only include the identifier(s) and the patient's active status. Resources in this returned response will contain a `meta.tag` value of `SUBSETTED` to indicate that they're an incomplete set of results.

-### :not

-`:not` allows you to find resources where an attribute isn't true. For example, you could search for patients where the gender isn't female:

-GET [your-fhir-server]/Patient?gender:not=female

-As a return value, you would get all patient entries where the gender isn't female, including empty values (entries specified without gender). This is different than searching for Patients where gender is male, since that wouldn't include the entries without a specific gender.

-### :missing

-`:missing` returns all resources that don't have a value for the specified element when the value is `true`, and returns all the resources that contain the specified element when the value is `false`. For simple data type elements, `:missing=true` will match on all resources where the element is present with extensions but has an empty value. For example, if you want to find all `Patient` resources that are missing information on birth date, you can do:

-GET [your-fhir-server]/Patient?birthdate:missing=true

-### :exact

-`:exact` is used for `string` parameters, and returns results that match the parameter precisely, such as in casing and character concatenating.

-GET [your-fhir-server]/Patient?name:exact=Jon

-This request returns `Patient` resources that have the name exactly the same as `Jon`. If the resource had patients with names such as `Jonathan` or `joN`, the search would ignore and skip the resource as it doesn't exactly match the specified value.

-### :contains

-`:contains` is used for `string` parameters and searches for resources with partial matches of the specified value anywhere in the string within the field being searched. `contains` is case insensitive and allows character concatenating. For example:

-GET [your-fhir-server]/Patient?address:contains=Meadow

-This request would return you all `Patient` resources with `address` fields that have values that contain the string "Meadow". This means you could have addresses that include values such as "Meadowers" or "59 Meadow ST" returned as search results.

-To perform a series of search operations that cover multiple reference parameters, you can "chain" the series of reference parameters by appending them to the server request one by one using a period `.`. For example, if you want to view all `DiagnosticReport` resources with a `subject` reference to a `Patient` resource that includes a particular `name`:

- GET [your-fhir-server]/DiagnosticReport?subject:Patient.name=Sarah

-This request would return all the `DiagnosticReport` resources with a patient subject named "Sarah". The period `.` after the field `Patient` performs the chained search on the reference parameter of the `subject` parameter.

-Another common use of a regular search (not a chained search) is finding all encounters for a specific patient. `Patient`s will often have one or more `Encounter`s with a subject. To search for all `Encounter` resources for a `Patient` with the provided `id`:

-GET [your-fhir-server]/Encounter?subject=Patient/78a14cbe-8968-49fd-a231-d43e6619399f

-Using chained search, you can find all the `Encounter` resources that match a particular piece of `Patient` information, such as the `birthdate`:

-GET [your-fhir-server]/Encounter?subject:Patient.birthdate=1987-02-20

-This would allow not just searching `Encounter` resources for a single patient, but across all patients that have the specified birth date value.

-In addition, chained search can be done more than once in one request by using the symbol `&`, which allows you to search for multiple conditions in one request. In such cases, chained search "independently" searches for each parameter, instead of searching for conditions that only satisfy all the conditions at once:

-GET [your-fhir-server]/Patient?general-practitioner:Practitioner.name=Sarah&general-practitioner:Practitioner.address-state=WA

-This would return all `Patient` resources that have "Sarah" as the `generalPractitioner` and have a `generalPractitioner` that has the address with the state WA. In other words, if a patient had Sarah from the state NY and Bill from the state WA both referenced as the patient's `generalPractitioner`, the would be returned.

-For scenarios in which the search has to be an AND operation that covers all conditions as a group, refer to the **composite search** example below.

-## Reverse chain search

-Chain search lets you search for resources based on the properties of resources they refer to. Using reverse chain search, allows you do it the other way around. You can search for resources based on the properties of resources that refer to them, using `_has` parameter. For example, `Observation` resource has a search parameter `patient` referring to a Patient resource. To find all Patient resources that are referenced by `Observation` with a specific `code`:

-GET [base]/Patient?_has:Observation:patient:code=527

-This request returns Patient resources that are referred by `Observation` with the code `527`.

-In addition, reverse chain search can have a recursive structure. For example, if you want to search for all patients that have `Observation` where the observation has an audit event from a specific user `janedoe`, you could do:

-GET [base]/Patient?_has:Observation:patient:_has:AuditEvent:entity:agent:Practitioner.name=janedoe

-To search for resources that meet multiple conditions at once, use composite search that joins a sequence of single parameter values with a symbol `$`. The returned result would be the intersection of the resources that match all of the conditions specified by the joined search parameters. Such search parameters are called composite search parameters, and they define a new parameter that combines the multiple parameters in a nested structure. For example, if you want to find all `DiagnosticReport` resources that contain `Observation` with a potassium value less than or equal to 9.2:

-GET [your-fhir-server]/DiagnosticReport?result.code-value-quantity=2823-3$lt9.2

-This request specifies the component containing a code of `2823-3`, which in this case would be potassium. Following the `$` symbol, it specifies the range of the value for the component using `lt` for "less than or equal to" and `9.2` for the potassium value range.

-Composite search parameters can also be used to filter multiple component code value quantities with an OR. For example, to express the query to find diastolic blood pressure greater than 90 OR systolic blood pressure greater than 140:

-GET [your-fhir-server]/Observation?component-code-value-quantity=http://loinc.org|8462-4$gt90,http://loinc.org|8480-6$gt140

-## Search the next entry set

-The maximum number of entries that can be returned per a single search query is 1000. However, you might have more than 1000 entries that match the search query, and you might want to see the next set of entries after the first 1000 entries that were returned. In such case, you would use the continuation token `url` value in `searchset` as in the `Bundle` result below:

- "url": "[your-fhir-server]/Patient?_sort=_lastUpdated&ct=WzUxMDAxNzc1NzgzODc5MjAwODBd"

- "url": "[your-fhir-server]/Patient?_sort=_lastUpdated"

-And you would do a GET request for the provided URL under the field `relation: next`:

-GET [your-fhir-server]/Patient?_sort=_lastUpdated&ct=WzUxMDAxNzc1NzgzODc5MjAwODBd

-This will return the next set of entries for your search result. The `searchset` is the complete set of search result entries, and the continuation token `url` is the link provided by the server for you to retrieve the entries that don't show up on the first set because the restriction on the maximum number of entries returned for a search query.

-## Search using POST

-All of the search examples mentioned above have used `GET` requests. You can also do search operations using `POST` requests using `_search`:

-POST [your-fhir-server]/Patient/_search?_id=45

-This request would return all `Patient` resources with the `id` value of 45. Just as in GET requests, the server determines which of the set of resources meets the condition(s), and returns a bundle resource in the HTTP response.

-Another example of searching using POST where the query parameters are submitted as a form body is:

-POST [your-fhir-server]/Patient/_search

-In this article, you learned about how to search using different search parameters, modifiers, and other search tools for FHIR. For more information about FHIR search, see

-# What is the MedTech service?

-The MedTech service is an optional service of the Azure Health Data Services designed to ingest health data from multiple and disparate Internet of Medical Things (IoMT) devices and persisting the health data in a Fast Healthcare Interoperability Resources (FHIR&#174;) service.

-The MedTech service is important because health data collected from patients and health care consumers can be fragmented from access across multiple systems, device types, and formats. Managing healthcare data can be difficult, however, trying to gain insight from the data can be one of the biggest barriers to population and personal wellness understanding and sustaining health.

-The MedTech service transforms device data into FHIR-based Observation resources and then persists the transformed messages into the Azure Health Data Services FHIR service. Allowing for a unified approach to health data access, standardization, and trend capture enabling the discovery of operational and clinical insights, connecting new device applications, and enabling new research projects.

-Below is an overview of what the MedTech service does after IoMT device data is received. Each step will be further explained in the [The MedTech service data flows](./iot-data-flow.md) article.

-> [!NOTE]

-> Learn more about [Azure Event Hubs](../../event-hubs/index.yml) use cases, features and architectures.

-## Scalable

-The MedTech service is designed out-of-the-box to support growth and adaptation to the changes and pace of healthcare by using autoscaling features. The service enables developers to modify and extend the capabilities to support more device mapping template types and FHIR resources.

-## Configurable

-The MedTech service is configured by using [Device](./how-to-use-device-mappings.md) and [FHIR destination](./how-to-use-fhir-mappings.md) mappings. The mappings instruct the filtering and transformation of your IoMT device messages into the FHIR format.

-The different points for extension are:

-* Normalization: Health data from disparate devices can be aligned and standardized into a common format to make sense of the data from a unified lens and capture trends.

-* FHIR conversion: Health data is normalized and grouped by mapping commonalities to FHIR. Observations can be created or updated according to chosen or configured templates. Devices and health care consumers can be linked for enhanced insights and trend capture.

-> [!TIP]

-> Check out the [IoMT Connector Data Mapper](https://github.com/microsoft/iomt-fhir/tree/master/tools/data-mapper) tool for editing, testing, and troubleshooting MedTech service Device and FHIR destination mappings. Export mappings for uploading to the MedTech service in the Azure portal or use with the [open-source version](https://github.com/microsoft/iomt-fhir) of the MedTech service.

-## Extensible

-The MedTech service may also be used with our [open-source projects](./iot-git-projects.md) for ingesting IoMT device data from the following wearables:

-* Fitbit&#174;

-* Apple&#174;

-* Google&#174;

-The MedTech service may also be used with the following Microsoft solutions to provide more functionalities and insights:

- * [Azure Machine Learning Service](./iot-connector-machine-learning.md)

- * [Microsoft Power BI](./iot-connector-power-bi.md)

- * [Microsoft Teams](./iot-connector-teams.md)

-

-## Secure

-The MedTech service uses [Azure role-based access control (Azure RBAC)](../../role-based-access-control/overview.md) and a [system-assigned managed identity](../../active-directory/managed-identities-azure-resources/overview.md) for granular security and access control of your MedTech service assets.

-In this article, you learned about the MedTech service. To learn about the MedTech service data flows and how to deploy the MedTech service in the Azure portal, see

-1. Select file option to upload the root certificate file called _mytestrootcert_cert.pem_ that you generated previously:

- 

-1. Select **Individual Enrollments** as the **Connect Method** and **Certificates (X.509)** as the mechanism:

- 

-Navigate to the **Environmental Sensor Edge Device** template and select **Publish**. On the **Publish this device template to the application** panel, select **Publish** to publish the template:

-1. Navigate to the **Device Templates** tab in the left pane, select **+ New**:

- 

-1. Select the C500 device template from the list of preconfigured device templates as shown below:

- 

-1. Navigate to the **Device Templates** tab in the left pane, select **+ New**:

- 

- The page gives you an option to **Create a custom template** or **Use a preconfigured device template**.

-1. Select the RuuviTag Multisensor device template from the list of preconfigured device templates:

- 

-To create an Azure IoT Central application, select **Build** in the left menu. Choose one of the industry templates, or choose **Custom app** to create an application from scratch. This will load the Application Creation page. You must complete all the fields on this page and then choose **Create**. You find more information about each of the fields below.

-

-

-

- :::image type="content" source="media/howto-manage-devices-in-bulk/configure-job.png" alt-text="Screenshot that shows selections for creating a property job called Set Light Threshold":::

- :::image type="content" source="media/howto-manage-devices-in-bulk/job-wizard-delivery-options.png" alt-text="Screenshot of job wizard delivery options page":::

-1. Select **Next** to move to the **Schedule** page. The **Schedule** page lets you enable a schedule to run the job in the future:

- :::image type="content" source="media/howto-manage-devices-in-bulk/job-wizard-schedule.png" alt-text="Screenshot of job wizard schedule options page":::

- :::image type="content" source="media/howto-manage-devices-in-bulk/job-schedule-details.png" alt-text="Screenshot of scheduled job details page":::

- :::image type="content" source="media/howto-manage-devices-in-bulk/job-wizard-schedule-immediate.png" alt-text="Screenshot of job wizard review page":::

- :::image type="content" source="media/howto-manage-devices-in-bulk/export-1.png" alt-text="Screenshot showing export action settings.":::

-The following screenshot shows how the command response displays in the IoT Central UI when it receives the 202 response code:

-The following view shows the writable properties. When you enter the value and select **Save**, the initial status is **Pending**. When the device accepts the change, the status changes to **Accepted**.

-This tutorial is oriented toward a Windows-based workstation. However, you can perform the procedures on Linux. For a Linux example, see [How to provision for multitenancy](how-to-provision-multitenant.md).

-description: This tutorial shows how to provision devices for multitenancy with your Device Provisioning Service (DPS) instance

-# Tutorial: Provision for multitenancy

-This tutorial shows how to securely provision multiple simulated symmetric key devices to a group of IoT Hubs using an [allocation policy](concepts-service.md#allocation-policy). Allocation policies that are defined by the provisioning service support a variety of allocation scenarios. Two common scenarios are:

-* **Geolocation / GeoLatency**: As a device moves between locations, network latency is improved by having the device provisioned to the IoT hub that's closest to each location. In this scenario, a group of IoT hubs, which span across regions, are selected for enrollments. The **Lowest latency** allocation policy is selected for these enrollments. This policy causes the Device Provisioning Service to evaluate device latency and determine the closet IoT hub out of the group of IoT hubs.

-* **Multi-tenancy**: Devices used within an IoT solution may need to be assigned to a specific IoT hub or group of IoT hubs. The solution may require all devices for a particular tenant to communicate with a specific group of IoT hubs. In some cases, a tenant may own IoT hubs and require devices to be assigned to their IoT hubs.

-It's common to combine these two scenarios. For example, a multitenant IoT solution commonly assigns tenant devices using a group of IoT hubs that are scattered across different regions. These tenant devices can be assigned to the IoT hub in the group that has the lowest latency based on geographic location.

-This tutorial uses a simulated device sample from the [Azure IoT C SDK](https://github.com/Azure/azure-iot-sdk-c) to demonstrate how to provision devices in a multitenant scenario across regions. You will perform the following steps in this tutorial:

-> * Create a multitenant enrollment

-> * Simulate the devices to see that they are provisioned for the same tenant in the closest region.

-In this section, you'll create an Azure resource group, and two new regional IoT hub resources for a tenant. One IoT hub will be for the **West US 2** region and the other will be for the **East US** region.

->It's recommended that you use the same resource group for all resources created in this tutorial. This will make clean up easier after you are finished.

-## Create the multitenant enrollment

-In this section, you'll create a new enrollment group for the tenant devices.

- :::image type="content" source="./media/how-to-provision-multitenant/create-multitenant-enrollment.png" alt-text="Add multitenant enrollment group for symmetric key attestation.":::

-In this section, you'll create two regional Linux virtual machines (VMs). These VMs will run a device simulation sample from each region to demonstrate device provisioning for tenant devices from both regions.

-In this section, you'll clone the Azure IoT C SDK on each VM. The SDK contains a sample that simulates a tenant's device provisioning from each region.

-3. Now each tenant device has their own derived device key and unique registration ID to perform symmetric key attestation with the enrollment group during the provisioning process.

-8. Once the build succeeds, run **prov\_dev\_client\_sample.exe** on both VMs to simulate a tenant device from each region. Notice that each device is allocated to the tenant IoT hub closest to the simulated device's regions.

-> Deleting a resource group is irreversible. The resource group and all the resources contained in it are permanently deleted. Make sure that you do not accidentally delete the wrong resource group or resources. If you created the IoT Hub inside an existing resource group that contains resources you want to keep, only delete the IoT Hub resource itself instead of deleting the resource group.

-This section is oriented toward a Windows-based workstation. For a Linux example, see the set-up of the VMs in [How to provision for multitenancy](how-to-provision-multitenant.md).

-This quickstart demonstrates a solution for a Windows-based workstation. However, you can also perform the procedures on Linux. For a Linux example, see [How to provision for multitenancy](how-to-provision-multitenant.md).

-This quickstart demonstrates a solution for a Windows-based workstation. However, you can also perform the procedures on Linux. For a Linux example, see [How to provision for multitenancy](how-to-provision-multitenant.md).

-This section is oriented toward a Windows-based workstation. For a Linux example, see the set-up of the VMs in [How to provision for multitenancy](how-to-provision-multitenant.md).

-Follow these links to learn more about managing Azure IoT Hub:

-The previous command creates an IoT hub in the S1 pricing tier for which you are billed. For more information, see [Azure IoT Hub pricing](https://azure.microsoft.com/pricing/details/iot-hub/).

-You can use Azure CLI to [delete an individual resource](/cli/azure/resource), such as an IoT hub, or delete a resource group and all its resources, including any IoT hubs.

-To learn more about using an IoT hub, see the following articles:

-To complete this how-to, you need an Azure subscription. If you don't have an Azure subscription, create a [free account](https://azure.microsoft.com/free/?WT.mc_id=A261C142F) before you begin.

-If you are using the Cloud Shell, you are already logged in to your subscription. If you are running PowerShell locally instead, enter the following command to sign in to your Azure subscription:

-You can list all the IoT hubs in your subscription using the [Get-AzIotHub](/powershell/module/az.IotHub/Get-azIotHub) command:

-This example shows the S1 Standard IoT Hub you created in the previous step.

-You can delete the IoT hub using the [Remove-AzIotHub](/powershell/module/az.iothub/remove-aziothub) command:

-Alternatively, you can remove a resource group and all the resources it contains using the [Remove-AzResourceGroup](/powershell/module/az.Resources/Remove-azResourceGroup) command:

-Now you have deployed an IoT hub using a PowerShell cmdlet, if you want to explore further, check out the following articles:

-To learn more about developing for IoT Hub, see the following articles:

-To further explore the capabilities of IoT Hub, see:

-| `compute` | string | Name of the compute target to execute the job on. This can be either a reference to an existing compute in the workspace (using the `azureml:<compute_name>` syntax) or `local` to designate local execution. | | `local` |

-| `type` | string | The type of job input. Specify `uri_file` for input data that points to a single file source, or `uri_folder` for input data that points to a folder source. | `uri_file`, `uri_folder` | `uri_folder` |

-| `type` | string | The type of job output. For the default `uri_folder` type, the output will correspond to a folder. | `uri_folder` | `uri_folder` |

-| `type` | string | The type of job input. Specify `uri_file` for input data that points to a single file source, or `uri_folder` for input data that points to a folder source. | `uri_file`, `uri_folder` | `uri_folder` |

-| `type` | string | The type of job output. For the default `uri_folder` type, the output will correspond to a folder. | `uri_folder` | `uri_folder` |

-description: Find out how to link a work email account domain to Partner Center. Learn how to create a work account and use multiple accounts. See troubleshooting tips.

-# Company work accounts and Partner Center

-Partner Center uses company work accounts, also known as Azure Active Directory (Azure AD) tenants, for many purposes:

-If you link your company's work email account domain to your Partner Center account, your employees can sign in to Partner Center to manage marketplace offers by using their own work account usernames and passwords.

-## Check whether your company already has a work account

-If your company subscribes to a Microsoft cloud service such as Azure, Microsoft Intune, or Microsoft 365, you already have a work email account domain. You can use that work account with Partner Center.

-Follow these steps to check for a work account:

-1. Sign in to the [Azure portal](https://portal.azure.com).

-1. Search for and select **Azure Active Directory**, and then select **Custom domain names**.

-1. Search for your domain name in the list. If you already have a work account, the list will contain your domain name.

-If your company doesn't already have a work account, one will be created for you during the Partner Center enrollment process.

-## Set up multiple work accounts

-Before you decide to use an existing work account, consider how many users in the work account need to access Partner Center. If you have users in the work account who don't need to access Partner Center, you might want to consider creating multiple work accounts. That way, only users who need to access Partner Center are represented on a particular account.

-## Create a new work account

-To create a new work account for your company, take the following steps. You might need to request assistance from the person who has administrative permissions for your company's Microsoft Azure account.

-1. Sign in to the [Azure portal](https://portal.azure.com).

-1. Search for and select **Azure Active Directory**, and then select **Users**.

-1. Select **New user**, and then follow these steps to configure a new Azure work account:

- 1. Enter a name and work email address.

- 1. For **Directory role**, ensure the value meets the user requirement.

- 1. At the bottom, select **Show password**.

- 1. Make a note of the autogenerated password.

- 1. Complete the other required fields.

-1. Select **Create** to save the new user.

-The email address for the user account must be a verified domain name in your directory. To list all the verified domains in your directory, select **Azure Active Directory** > **Custom domain names**.

-To learn more about adding custom domains in Azure AD, see [Add or associate a domain in Azure AD](../active-directory/fundamentals/add-custom-domain.md).

-## Troubleshoot work email sign-in

-If you're having trouble signing in to your work account, find the scenario on the following diagram that best matches your situation, and take the recommended steps.

-## Next steps

-The current minor release is **14.3**. Refer to the [PostgreSQL documentation](https://www.postgresql.org/docs/14/static/release-14-3.html) to learn more about improvements and fixes in this release. New servers will be created with this minor version.

-> PostgreSQL community released an out of band version 14.4 to address a critical issue. See the [release notes](https://www.postgresql.org/docs/release/14.4/) and this [discussion thread](https://www.postgresql.org/message-id/165473835807.573551.1512237163040609764%40wrigleys.postgresql.org) for details and the workaround till your server is patched to 14.4.

-A PostgreSQL connection, even idle, can occupy about 10MB of memory. Also, creating new connections takes time. Most applications request many short-lived connections, which compounds this situation. The result is fewer resources available for your actual workload leading to decreased performance. A connection pooler that decreases idle connections and reuses existing connections will help avoid this. To learn more, visit our [blog post](https://techcommunity.microsoft.com/t5/azure-database-for-postgresql/not-all-postgres-connection-pooling-is-equal/ba-p/825717).

-1. Select **Add**.

-| guid | A series of 32 or 8-4-4-4-12 string representation of an UUID as defineddefa in [RFC 4122](https://tools.ietf.org/html/rfc4122). |

-Get started by [registering and scanning an Azure Data Lake Gen2 storage account](register-scan-adls-gen2.md).

-The package is not part of the [ARR samples repository](https://github.com/Azure/azure-remote-rendering), and it is not available from Unity's internal package registry.

-Remote Rendering works with both the **:::no-loc text="Universal render pipeline":::** and the **:::no-loc text="Standard render pipeline":::**. For performance reasons, the Universal render pipeline is recommended.

- * **Universal Windows Platform (UWP) development**

-> When working with the OpenXR version of the plugin, it has to be verified that the *Universal Render Pipeline* (URP) has version 10.5.1 or higher. To check that, open the *Package Manager* from the Unity *Windows* menu and refer to the *Universal RP* section:

-> [!IMPORTANT]

-> The **WMR (Windows Mixed Reality) plugin for Unity 2020.3** currently has a performance degradation with ARR. For a better experience, we suggest to either stay on Unity 2019.X or switch to the OpenXR version.

-> [!Note]

- Get the query key as well. It's a best practice to issue query requests with read-only access.

-+ **Key** is the unique document identifier. It's always a string, and it is required.

-Storage requirements do not vary as a result of your selection. For example, if you set the **Retrievable** attribute on multiple fields, storage requirements do not go up.

-The **Fields** tab shows the index schema. If you are writing queries and need to check whether a field is filterable or sortable, this tab shows you the attributes.

-Scroll to the bottom of the list to enter a new field. While you can always create a new field, in most cases, you cannot change existing fields. Existing fields have a physical representation in your search service and are thus non-modifiable, not even in code. To fundamentally change an existing field, create a new index, dropping the original.

-To clearly understand what you can and cannot edit during index design, take a minute to view index definition options. Grayed-out options are an indicator that a value cannot be modified or deleted.

-If you are using a free service, remember that you are limited to three indexes, indexers, and data sources. You can delete individual items in the portal to stay under the limit.

-Configure a [search indexer](search-indexer-overview.md) to index documents stored in SharePoint document libraries for full text search in Azure Cognitive Search. This article explains the configuration steps, followed by a deeper exploration of behaviors and scenarios you are likely to encounter.

-To set up the SharePoint indexer, you will need to perform some tasks in the Azure portal, and other tasks through the preview REST API.

-The following video shows how to set up the SharePoint indexer.

-If the SharePoint site is in the same tenant as the search service, you will need to enable the system-assigned managed identity for the search service in the Azure portal. If the SharePoint site is in a different tenant from the search service, skip this step.

-After selecting **Save** you will see an Object ID that has been assigned to your search service.

-+ Delegated permissions, where the indexer runs under the identity of the user or app that sent the request. Data access is limited to the sites and files to which the user has access. To support deleted permissions, the indexer requires a [device code prompt](../active-directory/develop/v2-oauth2-device-code.md) to log in on behalf of the user.

-Note that if your Azure Active Directory organization has [Conditional Access enabled](../active-directory/conditional-access/overview.md) and your administrator is not able to grant any device access for Delegated permissions, you should consider Application permissions instead. For more information, refer to [SharePoint Conditional Access policies](./search-indexer-troubleshooting.md#sharepoint-conditional-access-policies).

- Tenant admin consent is required when using application API permissions. Some tenants are locked down in such a way that tenant admin consent is required for delegated API permissions as well. If either of these are the case, youΓÇÖll need to have a tenant admin grant consent for this Azure AD application before creating the indexer.

- + In the menu that pops up, enter a description for the new client secret. Adjust the expiration date if necessary. If the secret expires it will need to be recreated and the indexer needs to be updated with the new secret.

-1. Provide the code that was provided in the error message.

-1. The SharePoint indexer will access the SharePoint content as the signed-in user. The user that logs in during this step will be that signed-in user. So, if you log in with a user account that doesnΓÇÖt have access to a document in the Document Library that you want to index, the indexer wonΓÇÖt have access to that document.

-If there are no updates to the data source object, the indexer can run on a schedule without any user interaction. However, every time the Azure Cognitive Search data source object is updated, you will need to sign in again in order for the indexer to run. For example, if you change the data source query, sign in again using the `https://microsoft.com/devicelogin` and a new code.

-| metadata_spo_site_library_item_id | Edm.String | The combination key of site ID, library ID and item ID which uniquely identifies an item in a document library for a site. |

-| defaultSiteLibrary | Index all the content from the sites default document library. |

-| allSiteLibraries | Index all the content from all the document libraries in a site. This will not index document libraries from a subsite. Those can be specified in the "query" though. |

-| useQuery | Only index content defined in the "query". |

-| includeLibrariesInSite | Index content from all libraries under the specified site in the connection string. These are limited to subsites of your site. The value should be the URI of the site or subsite. <br><br>Example: <br><br>```"container" : { "name" : "useQuery", "query" : "includeLibrariesInSite=https://mycompany.sharepoint.com/mysite" }``` |

-| includeLibrary | Index all content from this library. The value is the fully-qualified path to the library, which can be copied from your browser: <br><br>Example 1 (fully-qualified path): <br><br>```"container" : { "name" : "useQuery", "query" : "includeLibrary=https://mycompany.sharepoint.com/mysite/MyDocumentLibrary" }``` <br><br>Example 2 (URI copied from your browser): <br><br>```"container" : { "name" : "useQuery", "query" : "includeLibrary=https://mycompany.sharepoint.com/teams/mysite/MyDocumentLibrary/Forms/AllItems.aspx" }``` |

-| excludeLibrary | Do not index content from this library. The value is the fully-qualified path to the library, which can be copied from your browser: <br><br> Example 1 (fully-qualified path): <br><br>```"container" : { "name" : "useQuery", "query" : "includeLibrariesInSite=https://mysite.sharepoint.com/subsite1; excludeLibrary=https://mysite.sharepoint.com/subsite1/MyDocumentLibrary" }``` <br><br> Example 2 (URI copied from your browser): <br><br>```"container" : { "name" : "useQuery", "query" : "includeLibrariesInSite=https://mycompany.sharepoint.com/teams/mysite; excludeLibrary=https://mycompany.sharepoint.com/teams/mysite/MyDocumentLibrary/Forms/AllItems.aspx" }``` |

-By default, the SharePoint indexer stops as soon as it encounters a document with an unsupported content type (for example, an image). You can of course use the `excludedFileNameExtensions` parameter to skip certain content types. However, you may need to index documents without knowing all the possible content types in advance. To continue indexing when an unsupported content type is encountered, set the `failOnUnsupportedContentType` configuration parameter to false:

-The **Import data wizard** in the Azure portal creates multiple objects used for indexing and AI enrichment on a search service. If you are new to Azure Cognitive Search, it's one of the most powerful features at your disposal. With minimal effort, you can create an indexing or enrichment pipeline that exercises most of the functionality of Azure Cognitive Search.

-This article is not a step by step. For help using the wizard with built-in sample data, see the [Quickstart: Create a search index](search-get-started-portal.md) or [Quickstart: Create a text translation and entity skillset](cognitive-search-quickstart-blob.md).

-In the [Azure portal](https://portal.azure.com), open the search service page from the dashboard or [find your service](https://portal.azure.com/#blade/HubsExtension/BrowseResourceBlade/resourceType/Microsoft.Search%2FsearchServices) in the service list. In the service Overview page at the top, click **Import data**.

-The wizard opens fully expanded in the browser window so that you have more room to work. Several pages are quite dense.

-| [Data Source](/rest/api/searchservice/create-data-source) | Persists connection information to source data, including credentials. A data source object is used exclusively with indexers. |

-| [Skillset](/rest/api/searchservice/create-skillset) | Optional. A complete set of instructions for manipulating, transforming, and shaping content, including analyzing and extracting information from image files. Except for very simple and limited structures, it includes a reference to a Cognitive Services resource that provides enrichment. |

-If you are evaluating skillsets, the wizard will handle all of the output field mappings and add helper functions to create usable objects. Text split is added if you specify a parsing mode. Text merge is added if you chose image analysis so that the wizard can reunite text descriptions with image content. Shaper skills added to support valid projections if you chose the knowledge store option. All of the above tasks come with a learning curve. If you are new to enrichment, the ability to have these steps handled for you allows you to measure the value of a skill without having to invest much time and effort.

-The wizard is not without limitations. Constraints are summarized as follows:

-+ The wizard does not support iteration or reuse. Each pass through the wizard creates a new index, skillset, and indexer configuration. Only data sources can be persisted and reused within the wizard. To edit or refine other objects, either delete the objects and start over, or use the REST APIs or .NET SDK to modify the structures.

-+ A [knowledge store](knowledge-store-concept-intro.md), which can be created by the wizard, is limited to a few default projections and uses a default naming convention. If you want to customize names or projections, you will need to create the knowledge store through REST API or the SDKs.

-+ Public access to all networks must be enabled on the supported data source while the wizard is used, since the portal won't be able to access the data source during setup if public access is disabled. This means that if your data source has a firewall enabled, you must disable it, run the Import Data wizard and then enable it after wizard setup is completed. If this is not an option, you can create Azure Cognitive Search data source, indexer, skillset and index through REST API or the SDKs.

-Skillset configuration occurs after the data source definition because the type of data source will inform the availability of certain built-in skills. In particular, if you are indexing files from Blob Storage, your choice of parsing mode of those files will determine whether sentiment analysis is available.

-Skillsets are optional and there is a button at the bottom of the page to skip ahead if you don't want AI enrichment.

-1. Is the data type appropriate for the incoming data? Azure Cognitive Search supports the [entity data model (EDM) data types](/rest/api/searchservice/supported-data-types). For Azure SQL data, there is [mapping chart](search-howto-connecting-azure-sql-database-to-azure-search-using-indexers.md#TypeMapping) that lays out equivalent values. For more background, see [Field mappings and transformations](search-indexer-field-mappings.md).

- + **Retrievable** returns the field in search results. Every field that provides content to search results must have this attribute. Setting this field does not appreciably effect index size.

-Internally, the wizard also sets up the following, which is not visible in the indexer until after it is created:

-The best way to understand the benefits and limitations of the wizard is to step through it. The following quickstart will guide you through each step.

-1. Make sure that you've considered your environmental requirements and understand the gaps between the different agents. For more information, see [When should I migrate](../azure-monitor/agents/azure-monitor-agent-migration.md#when-should-i-migrate-to-the-azure-monitor-agent) in the Azure Monitor documentation.

-> * [Create a Service Bus namespace with queue and authorization rule](service-bus-resource-manager-namespace-auth-rule.md)

-> * [Create a Service Bus namespace with topic and subscription](service-bus-resource-manager-namespace-topic.md)

-> * [Create a Service Bus namespace](service-bus-resource-manager-namespace.md)

-> * [Create a Service Bus namespace with topic, subscription, and rule](service-bus-resource-manager-namespace-topic-with-rule.md)

-To run the deployment automatically, click the following button: Create a new resource group for the deployment so that you can easily cleanup later.

-1. Select **Notifications** at the top to see the status of the deployment. Wait until the deployment succeeds. Then, select **Go to resource group** in the notification message to navigate to the page for the resource group that contains the Service Bus namespace.

-2. Confirm that you see your Service Bus namespace in the list of resources.

-3. Select the namespace from the list to see the **Service Bus Namespace** page.

-2. Select **Delete resource group** from the toolbar.

-3. Type the name of the resource group, and select **Delete**.

-* [Manage Service Bus with PowerShell](service-bus-manage-with-ps.md)

-* [Manage Service Bus resources with the Service Bus Explorer](https://github.com/paolosalvatori/ServiceBusExplorer/releases)

-1. Under **Data management**, locate the **Lifecycle management** settings.

-1. Select the **Add a rule** button.

-1. On the **Details** tab, specify a name for your rule.

-1. Specify the rule scope: either **Apply rule to all blobs in your storage account**, or **Limit blobs with filters**.

-1. Select the types of blobs for which the rule is to be applied, and specify whether to include blob snapshots or versions.

-1. Next, specify the number of days to elapse after the object is modified or accessed.

-1. Specify that the object is to be moved to the Archive tier after the interval has elapsed.

- :::image type="content" source="media/archive-blob/lifecycle-policy-base-blobs-tab-portal.png" alt-text="Screenshot showing how to configure a lifecycle management policy - Base blob tab.":::

-1. If you chose to limit the blobs affected by the rule with filters, you can specify a filter, either with a blob prefix or blob index match.

-1. Select the **Add** button to add the rule to the policy.

- "daysAfterLastAccessTimeGreaterThan": 90

-> Changing a blob's tier doesn't affect its last modified time. If there is a [lifecycle management](./lifecycle-management-overview.md) policy in effect for the storage account, then rehydrating a blob with **Set Blob Tier** can result in a scenario where the lifecycle policy moves the blob back to the Archive tier after rehydration because the last modified time is beyond the threshold set for the policy.

-> To avoid this scenario, rehydrate the archived blob by copying it instead, as described in the [Copy an archived blob to an online tier](#copy-an-archived-blob-to-an-online-tier) section. Performing a copy operation creates a new instance of the blob with an updated last modified time, so it won't trigger the lifecycle management policy.

- "daysAfterModificationGreaterThan": 90

-Some data stays idle in the cloud and is rarely, if ever, accessed. The following lifecycle policy is configured to archive data shortly after it's ingested. This example transitions block blobs in a container named `archivecontainer` into an archive tier. The transition is accomplished by acting on blobs 0 days after last modified time:

- "tierToArchive": { "daysAfterModificationGreaterThan": 0 }

-### I manually rehydrated an archived blob. How do I prevent it from being moved back to the Archive tier temporarily?

-When a blob is moved from one access tier to another, its last modification time doesn't change. If you manually rehydrate an archived blob to hot tier, it would be moved back to archive tier by the lifecycle management engine. Disable the rule that affects this blob temporarily to prevent it from being archived again. Re-enable the rule when the blob can be safely moved back to archive tier. You may also copy the blob to another location if it needs to stay in hot or cool tier permanently.

- :::image type="content" source="media/lifecycle-management-policy-configure/last-access-tracking-enable.png" alt-text="Screenshot showing how to enable last access tracking in Azure portal":::

-The change feed produces several metadata and log files. These files are located in the **$blobchangefeed** container of the storage account.

-> [!NOTE]

-> In the current release, the $blobchangefeed container is visible only in Azure portal but not visible in Azure Storage Explorer. You currently cannot see the $blobchangefeed container when you call ListContainers API but you are able to call the ListBlobs API directly on the container to see the blobs

- $subnetid=(az network vnet subnet show --resource-group "myresourcegroup" --vnet-name "myvnet" --name "mysubnet" --query id --output tsv)

-The `Join-AzStorageAccount` cmdlet performs the equivalent of an offline domain join on behalf of the specified storage account. The script uses the cmdlet to create a [computer account](/windows/security/identity-protection/access-control/active-directory-accounts#manage-default-local-accounts-in-active-directory) in your AD domain. If for whatever reason you cannot use a computer account, you can alter the script to create a [service logon account](/windows/win32/ad/about-service-logon-accounts) instead. If you choose to run the command manually, you should select the account best suited for your environment.

-Replace the placeholder values with your own in the parameters below before executing it in PowerShell.

-> The domain join cmdlet will create an AD account to represent the storage account (file share) in AD. You can choose to register as a computer account or service logon account, see [FAQ](./storage-files-faq.md#security-authentication-and-access-control) for details. For computer accounts, there is a default password expiration age set in AD at 30 days. Similarly, the service logon account may have a default password expiration age set on the AD domain or Organizational Unit (OU).

-> For both account types, we recommend you check the password expiration age configured in your AD environment and plan to [update the password of your storage account identity](storage-files-identity-ad-ds-update-password.md) of the AD account before the maximum password age. You can consider [creating a new AD Organizational Unit (OU) in AD](/powershell/module/activedirectory/new-adorganizationalunit) and disabling password expiration policy on [computer accounts](/previous-versions/windows/it-pro/windows-server-2012-R2-and-2012/jj852252(v=ws.11)) or service logon accounts accordingly.

-1. Set the SPN to **cifs/your-storage-account-name-here.file.core.windows.net** either in the AD GUI or by running the `Setspn` command from the Windows command line as administrator (remember to replace the example text with your storage account name):

-2. Use PowerShell to set the AD account password to the value of the kerb1 key (you must have AD PowerShell cmdlets installed):

-Replace `<domain-object-identity>` and `<domain-name>` with your values, then run the following cmdlet to configure AES-256 support:

-You've now successfully enabled the feature on your storage account. To use the feature, you must assign share-level permissions. Continue to the next section.

-> This guidance is for Synapse Workspace dedicated sql pools only. For standalone dedicated sql pool (formerly SQL DW) please follow guidance [Restore sql pool from deleted server](../sql-data-warehouse/sql-data-warehouse-restore-from-deleted-server.md).

-$PointInTime=ΓÇ¥<DroppedDateTime>ΓÇ¥

-2. Navigate to your Synapse workspace.

-3. Under Getting Started -> Open Synapse Studio, select **Open**.

-6. Select **+ New** to create a new dedicated SQL pool.

-7. In the Additional Settings tab, select a Restore Point to restore from.

- If the dedicated SQL pool doesn't have any automatic restore points, wait a few hours or create a user defined restore point before restoring. For User-Defined Restore Points, select an existing one or create a new one.