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articles/ai-services/openai/concepts/model-retirements.md

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description: Learn about the model deprecations and retirements in Azure OpenAI.
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ms.service: azure-ai-openai
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ms.topic: conceptual
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ms.date: 04/24/2024
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ms.date: 05/01/2024
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ms.custom:
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manager: nitinme
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author: mrbullwinkle

articles/ai-services/openai/concepts/models.md

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> [!IMPORTANT]
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>
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> - `gpt-4` versions 1106-Preview and 0125-Preview will be upgraded with a stable version of `gpt-4` in the future. The deployment upgrade of `gpt-4` 1106-Preview to `gpt-4` 0125-Preview scheduled for March 8, 2024 is no longer taking place. Deployments of `gpt-4` versions 1106-Preview and 0125-Preview set to "Auto-update to default" and "Upgrade when expired" will start to be upgraded after the stable version is released. For each deployment, a model version upgrade takes place with no interruption in service for API calls. Upgrades are staged by region and the full upgrade process is expected to take 2 weeks. Deployments of `gpt-4` versions 1106-Preview and 0125-Preview set to "No autoupgrade" will not be upgraded and will stop operating when the preview version is upgraded in the region.
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> - `gpt-4` versions 1106-Preview and 0125-Preview will be upgraded with a stable version of `gpt-4` in the future. Deployments of `gpt-4` versions 1106-Preview and 0125-Preview set to "Auto-update to default" and "Upgrade when expired" will start to be upgraded after the stable version is released. For each deployment, a model version upgrade takes place with no interruption in service for API calls. Upgrades are staged by region and the full upgrade process is expected to take 2 weeks. Deployments of `gpt-4` versions 1106-Preview and 0125-Preview set to "No autoupgrade" will not be upgraded and will stop operating when the preview version is upgraded in the region. See [Azure OpenAI model retirements and deprecations](./model-retirements.md) for more information on the timing of the upgrade.
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## GPT-3.5
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articles/ai-services/openai/includes/gpt-4-turbo.md

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### Differences between OpenAI and Azure OpenAI GPT-4 Turbo with Vision GA model
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- OpenAI's version of the latest `0409` turbo model supports JSON mode and function calling for all inference requests.
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- Azure OpenAI's version of the latest `turbo-2024-04-09` currently doesn't support the use of JSON mode and function calling when making inference requests with image (vision) input. Text based input requests do support JSON mode and function calling.
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- Azure OpenAI's version of the latest `turbo-2024-04-09` currently doesn't support the use of JSON mode and function calling when making inference requests with image (vision) input. Text based input requests (requests without `image_url` and inline images) do support JSON mode and function calling.
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### Differences from gpt-4 vision-preview
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articles/ai-services/openai/whats-new.md

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- ignite-2023
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- references_regions
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ms.topic: whats-new
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ms.date: 04/18/2024
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ms.date: 05/01/2024
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recommendations: false
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---
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articles/aks/learn/quick-kubernetes-deploy-bicep.md

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title: 'Quickstart: Deploy an Azure Kubernetes Service (AKS) cluster using Bicep'
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description: Learn how to quickly deploy a Kubernetes cluster using a Bicep file and deploy an application in Azure Kubernetes Service (AKS).
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ms.topic: quickstart
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ms.date: 12/27/2023
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ms.date: 04/28/2024
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author: tamram
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articles/automation/change-tracking/guidance-migration-log-analytics-monitoring-agent.md

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services: automation
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ms.subservice: change-inventory-management
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ms.topic: conceptual
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ms.date: 05/01/2024
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ms.author: sudhirsneha
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---
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## Onboarding to Change tracking and inventory using Azure Monitoring Agent
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### [Using Azure portal - for single VM](#tab/ct-single-vm)
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### [Using Azure portal - Azure single VM](#tab/ct-single-vm)
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> [!NOTE]
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> To onboard Arc-enabled VMs, use the PowerShell Script. For more information, see the steps listed in tab Using PowerShell script - Arc-enabled VMs.
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To onboard through Azure portal, follow these steps:
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1. Sign in to the [Azure portal](https://portal.azure.com) and select your virtual machine
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1. Under **Operations** , select **Change tracking**.
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:::image type="content" source="media/guidance-migration-log-analytics-monitoring-agent/switch-versions-inline.png" alt-text="Screenshot that shows switching between log analytics and Azure Monitoring Agent after a successful migration." lightbox="media/guidance-migration-log-analytics-monitoring-agent/switch-versions-expanded.png":::
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### [Using Azure portal - for Automation account](#tab/ct-at-scale)
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### [Using Azure portal - Automation account](#tab/ct-at-scale)
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1. Sign in to [Azure portal](https://portal.azure.com) and select your Automation account.
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1. Under **Configuration Management**, select **Change tracking** and then select **Configure with AMA**.
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:::image type="content" source="media/guidance-migration-log-analytics-monitoring-agent/switch-versions-inline.png" alt-text="Screenshot that shows switching between log analytics and Azure Monitoring Agent after a successful migration." lightbox="media/guidance-migration-log-analytics-monitoring-agent/switch-versions-expanded.png":::
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### [Using PowerShell script](#tab/ps-policy)
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### [Using PowerShell script - Arc-enabled VMs](#tab/ps-policy)
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To onboard Arc-enabled VMs, follow the steps:
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#### Prerequisites
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#### Migration guidance
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1. Install the script and run it to conduct migrations.
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1. Ensure the new workspace resource ID is different from the one associated with the Change Tracking and Inventory using the LA version.
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1. Migrate settings for the following data types:
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- Windows Services
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- Linux Files
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- Windows Files
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- Windows Registry
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- Linux Daemons
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1. Generate and associate a new DCR to transfer the settings to the Change Tracking and Inventory using AMA.
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#### Onboard at scale
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Use the [script](https://github.com/mayguptMSFT/AzureMonitorCommunity/blob/master/Azure%20Services/Azure%20Monitor/Agents/Migration%20Tools/DCR%20Config%20Generator/CTDcrGenerator/CTWorkSpaceSettingstoDCR.ps1) to migrate Change tracking workspace settings to a data collection rule.
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#### Parameters
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**Parameter** | **Required** | **Description** |
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--- | --- | --- |
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`InputWorkspaceResourceId`| Yes | Resource ID of the workspace associated with Change Tracking & Inventory with Log Analytics. |
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`OutputWorkspaceResourceId`| Yes | Resource ID of the workspace associated with Change Tracking & Inventory with Azure Monitoring Agent. |
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`OutputDCRName`| Yes | Custom name of the new DCR created. |
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`OutputDCRLocation`| Yes | Azure location of the output workspace ID. |
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`OutputDCRTemplateFolderPath`| Yes | Folder path where DCR templates are created. |
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1. Install the [script](https://github.com/mayguptMSFT/AzureMonitorCommunity/blob/master/Azure%20Services/Azure%20Monitor/Agents/Migration%20Tools/DCR%20Config%20Generator/CTDcrGenerator/CTWorkSpaceSettingstoDCR.ps1) and run it to conduct migrations. The script does the following:
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1. It ensures the new workspace resource ID is different from the one associated with the Change Tracking and Inventory using the LA version.
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1. It migrates the settings for the following data types:
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- Windows Services
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- Linux Files
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- Windows Files
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- Windows Registry
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- Linux Daemons
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1. The script consists of the following **Parameters** that require an input from you.
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**Parameter** | **Required** | **Description** |
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--- | --- | --- |
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`InputWorkspaceResourceId`| Yes | Resource ID of the workspace associated with Change Tracking & Inventory with Log Analytics. |
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`OutputWorkspaceResourceId`| Yes | Resource ID of the workspace associated with Change Tracking & Inventory with Azure Monitoring Agent. |
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`OutputDCRName`| Yes | Custom name of the new DCR created. |
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`OutputDCRLocation`| Yes | Azure location of the output workspace ID. |
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`OutputDCRTemplateFolderPath`| Yes | Folder path where DCR templates are created. |
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1. A DCR template is generated when you run the above script and the template is available in `OutputDCRTemplateFolderPath`. You have to associate the new DCR to transfer the settings to the Change Tracking and Inventory using AMA.
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1. Sign in to [Azure portal](https://portal.azure.com) and go to **Monitor** and under **Settings**, select **Data Collection Rules**.
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1. Select the data collection rule that you have created in Step 1 from the listing page.
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1. In the data collection rule page, under **Configurations**, select **Resources** and then select **Add**.
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1. In the Select a scope, from Resource types, select Machines-Azure Arc that is connected to the subscription and then select Apply to associate the ctdcr created in Step 1 to the Arc-enabled machine and it will also install the Azure Monitoring Agent extension. For more information, see [Enable Change Tracking and Inventory - for Arc-enabled VMs - using portal/CLI](enable-vms-monitoring-agent.md#enable-change-tracking-and-inventory).
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Install the Change Tracking extension as per the OS type for the Arc-enabled VM.
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**Linux**
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```azurecli
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az connectedmachine extension create --name ChangeTracking-Linux --publisher Microsoft.Azure.ChangeTrackingAndInventory --type-handler-version 2.20 --type ChangeTracking-Linux --machine-name XYZ --resource-group XYZ-RG --location X --enable-auto-upgrade
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```
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**Windows**
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```azurecli
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az connectedmachine extension create --name ChangeTracking-Windows --publisher Microsoft.Azure.ChangeTrackingAndInventory --type-handler-version 2.20 --type ChangeTracking-Windows --machine-name XYZ --resource-group XYZ-RG --location X --enable-auto-upgrade
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```
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If the CT logs table schema does not exist, the script mentioned in Step 1 will fail. To troubleshoot, run the following script -
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```azurepowershell-interactive
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$psWorkspace = Get-AzOperationalInsightsWorkspace -ResourceGroupName $resourceGroup -Name $laws
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# Enabling CT solution on LA ws
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New-AzMonitorLogAnalyticsSolution -Type ChangeTracking -ResourceGroupName $resourceGroup -Location $psWorkspace.Location -WorkspaceResourceId $psWorkspace.ResourceId
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```
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---
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### Compare data across Log analytics Agent and Azure Monitoring Agent version
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After you complete the onboarding to Change tracking with AMA version, select **Switch to CT with AMA** on the landing page to switch across the two versions and compare the following events.

articles/azure-app-configuration/TOC.yml

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href: quickstart-azure-functions-csharp.md
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- name: Feature management
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- name: Manage feature flags
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href: manage-feature-flags.md
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- name: Feature management
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articles/azure-app-configuration/index.yml

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# linkListType: architecture | concept | deploy | download | get-started | how-to-guide | learn | overview | quickstart | reference | tutorial | video | whats-new
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- text: Use feature flags in ASP.NET Core
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- text: Use feature flags in Spring Boot

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