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@@ -25,15 +25,14 @@ TLS versions 1.0 and 1.1 also don't support the modern encryption methods and ci
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As a part of this effort, you can expect the following changes to Azure Cache for Redis:
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-_Phase 1_: Azure Cache for Redis stops offering TLS 1.0/1.1 as an option for _MinimumTLSVersion_ setting for new cache creates. Existing cache instances won't be updated at this point. You can't set the _MinimumTLSVersion_ to 1.0 or 1.1 for your existing cache.
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-_Phase 2_: Azure Cache for Redis stops supporting TLS 1.1 and TLS 1.0 starting March 1, 2025. After this change, your application must use TLS 1.2 or later to communicate with your cache. The Azure Cache for Redis service remains available while we update the _MinimumTLSVersion_ for all caches to 1.2.
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-_Phase 2_: Azure Cache for Redis stops supporting TLS 1.1 and TLS 1.0 starting April 1, 2025. After this change, your application must use TLS 1.2 or later to communicate with your cache. The Azure Cache for Redis service remains available while we update the _MinimumTLSVersion_ for all caches to 1.2.
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| Date | Description |
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|--|--|
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| September 2023 | TLS 1.0/1.1 retirement announcement |
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| March 1, 2024 | Beginning March 1, 2024, you can't create new caches with the Minimum TLS version set to 1.0 or 1.1 and you can't set the _MinimumTLSVersion_ to 1.0 or 1.1 for your existing cache. The minimum TLS version aren't updated automatically for existing caches at this point. |
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| March 1, 2024 | Beginning March 1, 2024, you can't create new caches with the Minimum TLS version set to 1.0 or 1.1 and you can't set the _MinimumTLSVersion_ to 1.0 or 1.1 for your existing cache. The minimum TLS versions aren't updated automatically for existing caches at this point. |
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| March 31, 2025 | Ensure that all your applications are connecting to Azure Cache for Redis using TLS 1.2 and Minimum TLS version on your cache settings is set to 1.2. |
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| Starting April 1, 2025 | Minimum TLS version for all cache instances is updated to 1.2. This means Azure Cache for Redis instances *reject* connections using TLS 1.0 or 1.1 at this point. |
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| Starting April 1, 2025 | Minimum TLS version for all cache instances is updated to 1.2. This means Azure Cache for Redis instances reject connections using TLS 1.0 or 1.1 at this point. |
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As part of this change, Azure Cache for Redis removes support for older cipher suites that aren't secure. Supported cipher suites are restricted to the following suites when the cache is configured with a minimum of TLS 1.2:
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@@ -44,9 +43,9 @@ The following sections provide guidance about how to detect dependencies on thes
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## Check TLS versions supported by your Azure Cache for Redis
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You can verify that **Minimum TLS version** value is set to TLS 1.2 in the [Advanced settings](cache-configure.md#advanced-settings) of your cache in the Azure portal. If it is any value other than TLS 1.2, then ensure you follow the instructions to[Configure your Azure Cache for Redis to use TLS 1.2](#configure-your-azure-cache-for-redis-to-use-tls-12). If the value is TLS 1.2, and your client application is able to connect without any errors, then no action is needed.
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You can verify that **Minimum TLS version** value is set to TLS 1.2 in the [Advanced settings](cache-configure.md#advanced-settings) of your cache in the Azure portal. If it is any value other than TLS 1.2, then ensure you follow the instructions in section[Configure your Azure Cache for Redis to use TLS 1.2](#configure-your-azure-cache-for-redis-to-use-tls-12). If the value is TLS 1.2, and your client application is able to connect without any errors, then no action is needed.
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You can also use this PowerShell script to verify the minimum TLS version supported by your Azure Cache for Redis endpoint. If your Redis instance is virtual network (VNet) injected, you have to run this script from a Virtual Machine in your VNet that has access to the Azure Cache for Redis endpoint. If the result shows `Tls Enabled` and/or `Tls 11 Enabled`, then ensure you follow the instructions to[Configure your Azure Cache for Redis to use TLS 1.2](#configure-your-azure-cache-for-redis-to-use-tls-12). If the result shows only `Tls12 Enabled` and your client application is able to connect without any errors, then no action is needed.
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You can also use this PowerShell script to verify the minimum TLS version supported by your Azure Cache for Redis endpoint. If your Redis instance is virtual network (VNet) injected, you have to run this script from a Virtual Machine in your VNet that has access to the Azure Cache for Redis endpoint. If the result shows `Tls Enabled` and/or `Tls 11 Enabled`, then ensure you follow the instructions in section[Configure your Azure Cache for Redis to use TLS 1.2](#configure-your-azure-cache-for-redis-to-use-tls-12). If the result shows only `Tls12 Enabled` and your client application is able to connect without any errors, then no action is needed.
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```powershell
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param(
@@ -106,8 +105,6 @@ You can configure TLS 1.2 on the cache by setting the **Minimum TLS version** va
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1. Select **1.2** in the **Minimum TLS version** in the working pane. Then, select **Save**.
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:::image type="content" source="media/cache-remove-tls-10-11/change-redis-tls-version.png" alt-text="Screenshot showing the Set TLS 1.2 for cache on Azure portal":::
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You can also do the same using PowerShell. You need the Az.RedisCache module already installed before running the command.
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>[!NOTE]
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>Although these addresses are static, it's possible that we'll need to change them from time to time. All Application Insights traffic represents outbound traffic except for availability monitoring and webhooks, which require inbound firewall rules.
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You need to open some **outgoing ports** in your server's firewall to allow the Application Insights SDK and/or Status Monitor to send data to the portal:
To allow the Application Insights SDK/agent to send data to the Application Insights resource, you need to allow access to the regional endpoint defined in your connection string and open the **outgoing port 443** in your firewall. To learn more about the endpoint suffix, see [Connection strings in Application Insights](/azure/azure-monitor/app/connection-strings#connection-string-with-an-endpoint-suffix).
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### [Cost Management and Billing](../cost-management-billing/index.yml)
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ms.service: azure-communication-services
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---
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# Artificial intelligence overview
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# Artificial intelligence (AI) overview
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AI technologies are useful for many communication experiences. AI can help humans communicate better and accomplish their mission more efficiently, for example, a banking employee may use an AI generated meeting summary to help them follow up. AI can reduce human workloads and enable more flexible customer engagement, such as operating a 24/7 phone bot that customers call to check their account balance.
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Artificial intelligence (AI) technologies are useful for many communication experiences. AI can help humans communicate better and accomplish their mission more efficiently, for example, a banking employee may use an AI generated meeting summary to help them follow up. AI can reduce human workloads and enable more flexible customer engagement, such as operating a 24/7 phone bot that customers call to check their account balance.
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More examples include:
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- Operate a chat or voice bot that responds to human conversation.
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### Direct Integrations
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-**[Advanced message analysis](../concepts/advanced-messaging/message-analysis/message-analysis.md)** The Azure Communication Services messaging APIs for WhatsApp provide a built-in integration with Azure OpenAI that analyzes and annotates messages. This integration can detect the user's language, recognize their intent, and extract key phrases.
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-**[Azure Bot Service: Chat channel integration](../quickstarts/chat/quickstart-botframework-integration.md)** - The Azure Communication Services chat system is directly integrated with Azure Bot Service. This integration simplifies creating chat bots that engage with human users.
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-**[Advanced message analysis](../concepts/advanced-messaging/message-analysis/message-analysis.md)**: The Azure Communication Services messaging APIs for WhatsApp provide a built-in integration with Azure OpenAI that analyzes and annotates messages. This integration can detect the user's language, recognize their intent, and extract key phrases.
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-**[Azure Bot Service: Chat channel integration](../quickstarts/chat/quickstart-botframework-integration.md)**: The Azure Communication Services chat system is directly integrated with Azure Bot Service. This integration simplifies creating chat bots that engage with human users.
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### Accessors
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All Azure Communication Services messaging capabilities are accessible through REST APIs, server-oriented SDKs, and Event Grid notifications. You can use these SDKs to export content to an external datastore and attach a language model to summarize conversations. Or you can use the SDKs to integrate a bot that directly engages with human users. For example, this [GitHub sample](https://github.com/Azure-Samples/communication-services-javascript-quickstarts/tree/main/chat-nlp-analysis) shows how Azure Communication Services APIs for chat can be accessed through REST APIs and then analyzed by Azure OpenAI.
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## Voice, video, and telephony
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This section summarizes features for integrating AI into Azure Communication voice and video calling.
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This section summarizes features for integrating AI into Azure Communication voice and video calling.
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### Direct Integrations
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-**[Call Automation REST APIs and SDKs](../concepts/call-automation/call-automation.md)**- Azure Communication Services has simple APIs for [synthesizing](../concepts/call-automation/play-action.md) and [recognizing](../concepts/call-automation/recognize-action.md) speech. The most common scenario for these APIs is implementing voice bots, which is sometimes called interactive voice response (IVR).
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-**[Microsoft Copilot Studio](/microsoft-copilot-studio/voice-overview)** - Copilot Studio is directly integrated with Azure Communication Services telephony. This integration is designed for voice bots and IVR.
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-**[Client captions](../concepts/voice-video-calling/closed-captions.md)** The Calling client SDK provides APIs for real-time closed captions, optimized for accessibility.
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-**[Copilot in the Azure portal](/azure/communication-services/concepts/voice-video-calling/call-diagnostics#copilot-in-azure-for-call-diagnostics)** - You can use Copilot in the Azure portal to ask questions about Azure Communication Services. Copilot uses Azure technical documentation to answer your questions and is best used for asking questions about error codes and API behavior.
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-**[Client background effects](../quickstarts/voice-video-calling/get-started-video-effects.md?pivots=platform-web)** - The Calling client SDKs provide APIs for blurring or replacing a user's background.
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-**[Client noise enhancement and effects](../tutorials/audio-quality-enhancements/add-noise-supression.md?pivots=platform-web)** - The Calling client SDK integrates a [DeepVQE](https://arxiv.org/abs/2306.03177) machine learning model to improve audio quality through echo cancellation and background noise suppression. This transformation is toggled on and off by using the client SDK.
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-**[Call Automation REST APIs and SDKs](../concepts/call-automation/call-automation.md)**: Azure Communication Services has simple APIs for [synthesizing](../concepts/call-automation/play-action.md) and [recognizing](../concepts/call-automation/recognize-action.md) speech. The most common scenario for these APIs is implementing voice bots, which is sometimes called interactive voice response (IVR).
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-**[Microsoft Copilot Studio](/microsoft-copilot-studio/voice-overview)**: Copilot Studio is directly integrated with Azure Communication Services telephony. This integration is designed for voice bots and IVR.
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-**[Client captions](../concepts/voice-video-calling/closed-captions.md)**: The Calling client SDK provides APIs for real-time closed captions, optimized for accessibility.
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-**[Copilot in the Azure portal](/azure/communication-services/concepts/voice-video-calling/call-diagnostics#copilot-in-azure-for-call-diagnostics)**: You can use Copilot in the Azure portal to ask questions about Azure Communication Services. Copilot uses Azure technical documentation to answer your questions and is best used for asking questions about error codes and API behavior.
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-**[Client background effects](../quickstarts/voice-video-calling/get-started-video-effects.md?pivots=platform-web)**: The Calling client SDKs provide APIs for blurring or replacing a user's background.
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-**[Client noise enhancement and effects](../tutorials/audio-quality-enhancements/add-noise-supression.md?pivots=platform-web)**: The Calling client SDK integrates a [DeepVQE](https://arxiv.org/abs/2306.03177) machine learning model to improve audio quality through echo cancellation and background noise suppression. This transformation is toggled on and off by using the client SDK.
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### Accessors
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Similar to Azure Communication Services messaging, there are REST APIs for many voice and video calling features. However the real-time nature of calling requires closed source SDKs and more complex APIs such as websocket streaming.
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-**[Call Automation REST APIs and SDKs](../concepts/call-automation/call-automation.md)** - Services and AI applications use Call Automation REST APIs to answer, route, and manage all types of Azure voice and video calls.
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-**[Service-to-service audio streaming](../concepts/call-automation/audio-streaming-concept.md)** - AI applications use Azure's service-to-service WebSockets API to stream audio data. This works in both directions, your AI can listen to a call, and speak.
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-**[Service-to-service real-time transcription](../concepts/call-automation/real-time-transcription.md)** - AI applications use Azure's service-to-service WebSockets API to stream a real-time, Azure-generated transcription. Compared to audio or video content, transcript data is often easier for AI models to reason upon.
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-**[Client raw audio and video](../concepts/voice-video-calling/media-access.md)** - The Calling client SDK provides APIs for accessing and modifying the raw audio and video feed. An example scenario is taking the video feed, using computer vision to distinguish the human speaker from their background, and customizing that background.
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-**[Call Automation REST APIs and SDKs](../concepts/call-automation/call-automation.md)**: Services and AI applications use Call Automation REST APIs to answer, route, and manage all types of Azure voice and video calls.
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-**[Service-to-service audio streaming](../concepts/call-automation/audio-streaming-concept.md)**: AI applications use Azure's service-to-service WebSockets API to stream audio data. This works in both directions, your AI can listen to a call, and speak.
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-**[Service-to-service real-time transcription](../concepts/call-automation/real-time-transcription.md)**: AI applications use Azure's service-to-service WebSockets API to stream a real-time, Azure-generated transcription. Compared to audio or video content, transcript data is often easier for AI models to reason upon.
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-**[Call recording](../concepts/voice-video-calling/call-recording.md)**: You can record Azure calls in your own datastore and then direct AI services to process that content.
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-**[Client raw audio and video](../concepts/voice-video-calling/media-access.md)**: The Calling client SDK provides APIs for accessing and modifying the raw audio and video feed. An example scenario is taking the video feed, using computer vision to distinguish the human speaker from their background, and customizing that background.
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