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Copy file name to clipboardExpand all lines: articles/ai-services/autoscale.md
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ms.custom:
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- ignite-2023
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ms.topic: how-to
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ms.date: 01/20/2024
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ms.date: 01/10/2025
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---
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# Autoscale AI services limits
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This article provides guidance for how customers can access higher rate limits on their Azure AI services resources.
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This article provides guidance for how customers can access higher rate limits on certain Azure AI services resources.
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## Overview
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Each Azure AI services resource has a pre-configured static call rate (transactions per second) which limits the number of concurrent calls that customers can make to the backend service in a given time frame. The autoscale feature will automatically increase/decrease a customer's resource's rate limits based on near-real-time resource usage metrics and backend service capacity metrics.
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## Get started with the autoscale feature
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This feature is disabled by default for every new resource. Follow these instructions to enable it.
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This feature is disabled by default for every new resource. [If your resource supports autoscale](#which-services-support-the-autoscale-feature), follow these instructions to enable it:
Autoscale feature is available in the paid subscription tier of the following services:
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*[Azure AI Vision](computer-vision/index.yml)
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*[Language](language-service/overview.md) (only available for sentiment analysis, key phrase extraction, named entity recognition, and text analytics for health)
### Can I test this feature using a free subscription?
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No, the autoscale feature isn't available to free tier subscriptions.
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### Does enabling the autoscale feature mean my resource will never be throttled again?
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No, you may still get `429` errors for rate limit excess. If your application triggers a spike, and your resource reports a `429` response, autoscale checks the available capacity projection section to see whether the current capacity can accommodate a rate limit increase and respond within five minutes.
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Yes, you can disable the autoscale feature through Azure portal or CLI and return to your default call rate limit setting. If your resource was previously approved for a higher default TPS, it goes back to that rate. It can take up to five minutes for the changes to go into effect.
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### Which services support the autoscale feature?
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Autoscale feature is available for the following services:
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*[Azure AI Vision](computer-vision/index.yml)
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*[Language](language-service/overview.md) (only available for sentiment analysis, key phrase extraction, named entity recognition, and text analytics for health)
Copy file name to clipboardExpand all lines: articles/ai-services/diagnostic-logging.md
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manager: nitinme
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ms.service: azure-ai-services
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ms.topic: how-to
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ms.date: 01/20/2024
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ms.date: 01/10/2025
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ms.author: pafarley
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---
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# Enable diagnostic logging for Azure AI services
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This guide provides step-by-step instructions to enable diagnostic logging for an Azure AI service. These logs provide rich, frequent data about the operation of a resource that are used for issue identification and debugging. Before you continue, you must have an Azure account with a subscription to at least one Azure AI service, such as [Speech Services](./speech-service/overview.md).
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This guide provides step-by-step instructions to enable diagnostic logging for an Azure AI service. These logs provide rich, frequent data about the operation of a resource that are used for issue identification and debugging. Before you continue, you must have an Azure account with a subscription to at least one Azure AI service, such as [Azure AI Speech](./speech-service/overview.md).
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## Prerequisites
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To enable diagnostic logging, you'll need somewhere to store your log data. This tutorial uses Azure Storage and Log Analytics.
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To enable diagnostic logging, you need to select a location to store your log data. This tutorial uses Azure Storage and Log Analytics.
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*[Azure storage](/azure/azure-monitor/essentials/resource-logs#send-to-azure-storage) - Retains diagnostic logs for policy audit, static analysis, or backup. The storage account does not have to be in the same subscription as the resource emitting logs as long as the user who configures the setting has appropriate Azure RBAC access to both subscriptions.
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*[Azure storage](/azure/azure-monitor/essentials/resource-logs#send-to-azure-storage) - Retains diagnostic logs for policy audit, static analysis, or backup. The storage account doesn't have to be in the same subscription as the resource emitting logs as long as the user who configures the setting has appropriate Azure role-based access control (RBAC) access to both subscriptions.
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*[Log Analytics](/azure/azure-monitor/essentials/resource-logs#send-to-log-analytics-workspace) - A flexible log search and analytics tool that allows for analysis of raw logs generated by an Azure resource.
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> [!NOTE]
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> *Additional configuration options are available. To learn more, see [Collect and consume log data from your Azure resources](/azure/azure-monitor/essentials/platform-logs-overview).
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> *Other configuration options are available. To learn more, see [Collect and consume log data from your Azure resources](/azure/azure-monitor/essentials/platform-logs-overview).
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> * "Trace" in diagnostic logging is only available for [Custom question answering](./qnamaker/how-to/get-analytics-knowledge-base.md?tabs=v2).
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## Enable diagnostic log collection
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Let's start by enabling diagnostic logging using the Azure portal.
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Start by enabling diagnostic logging using the Azure portal.
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> [!NOTE]
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> To enable this feature using PowerShell or the Azure CLI, use the instructions provided in [Collect and consume log data from your Azure resources](/azure/azure-monitor/essentials/platform-logs-overview).
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1. Navigate to the Azure portal. Then locate and select an Azure AI services resource. For example, your subscription to Speech Services.
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2. Next, from the left-hand navigation menu, locate **Monitoring** and select **Diagnostic settings**. This screen contains all previously created diagnostic settings for this resource.
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2. Next, from the left-hand navigation menu, locate **Monitoring**, and select **Diagnostic settings**. This screen contains all previously created diagnostic settings for this resource.
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3. If there is a previously created resource that you'd like to use, you can select it now. Otherwise, select **+ Add diagnostic setting**.
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4. Enter a name for the setting. Then select **Archive to a storage account** and **Send to log Analytics**.
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5. When prompted to configure, select the storage account and OMS workspace that you'd like to use to store you diagnostic logs. **Note**: If you don't have a storage account or OMS workspace, follow the prompts to create one.
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6. Select **Audit**, **RequestResponse**, and **AllMetrics**. Then set the retention period for your diagnostic log data. If a retention policy is set to zero, events for that log category are stored indefinitely.
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7. Select **Save**.
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It can take up to two hours before logging data is available to query and analyze. So don't worry if you don't see anything right away.
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It can take up to two hours before logging data is available to query and analyze, so don't worry if you don't see anything right away.
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## View and export diagnostic data from Azure Storage
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by OperationName
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```
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Run this query to view the volume of operations over time split by OperationName with counts binned for every 10s.
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Run this query to view the volume of operations over time split by OperationName with counts binned for every 10 seconds.
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```kusto
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AzureDiagnostics
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## Next steps
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* To understand how to enable logging, as well as the metrics and log categories that are supported by the various Azure services, read the [Overview of metrics](/azure/azure-monitor/data-platform) in Microsoft Azure and the [Overview of Azure Diagnostic Logs](/azure/azure-monitor/essentials/platform-logs-overview).
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* To understand how to enable logging and the metrics and log categories that are supported by the various Azure services, read the [Overview of metrics](/azure/azure-monitor/data-platform) in Microsoft Azure and the [Overview of Azure Diagnostic Logs](/azure/azure-monitor/essentials/platform-logs-overview).
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* Read these articles to learn about event hubs:
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*[What is Azure Event Hubs?](/azure/event-hubs/event-hubs-about)
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*[Get started with Event Hubs](/azure/event-hubs/event-hubs-dotnet-standard-getstarted-send)
Copy file name to clipboardExpand all lines: articles/ai-services/rotate-keys.md
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ms.author: pafarley
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# Rotate keys in Azure AI services
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Each Azure AI services resource has two API keys to enable secret rotation. This is a security precaution that lets you regularly change the keys that can access your service, protecting the privacy of your resource if a key gets leaked.
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Each Azure AI services resource has two API keys to enable secret rotation. This is a security precaution that lets you regularly change the keys that can be used to access your service, protecting the privacy of your resource if a key gets leaked.
Copy file name to clipboardExpand all lines: articles/ai-services/security-controls-policy.md
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title: Azure Policy Regulatory Compliance controls for Azure AI services
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description: Lists Azure Policy Regulatory Compliance controls available for Azure AI services. These built-in policy definitions provide common approaches to managing the compliance of your Azure resources.
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ms.date: 02/06/2024
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ms.date: 01/10/2025
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ms.topic: sample
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author: PatrickFarley
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# Azure Policy Regulatory Compliance controls for Azure AI services
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[Regulatory Compliance in Azure Policy](/azure/governance/policy/concepts/regulatory-compliance)
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provides Microsoft created and managed initiative definitions, known as _built-ins_, for the
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**compliance domains** and **security controls** related to different compliance standards. This
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page lists the **compliance domains** and **security controls** for Azure AI services. You can
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assign the built-ins for a **security control** individually to help make your Azure resources
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compliant with the specific standard.
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[Regulatory Compliance in Azure Policy](/azure/governance/policy/concepts/regulatory-compliance) provides Microsoft-created and managed initiative definitions, known as _built-ins_, for the **compliance domains** and **security controls** related to different compliance standards. This page lists the **compliance domains** and **security controls** for Azure AI services. You can assign the built-ins for a **security control** individually to help make your Azure resources compliant with the specific standard.
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