Merge branch 'main' of https://github.com/MicrosoftDocs/azure-docs-pr into remove-horizon

Author: batamig

.openpublishing.publish.config.json

@@ -1257,6 +1257,7 @@
   "articles/stream-analytics/.openpublishing.redirection.stream-analytics.json",
   "articles/synapse-analytics/.openpublishing.redirection.synapse-analytics.json",
   "articles/virtual-machine-scale-sets/.openpublishing.redirection.virtual-machine-scale-sets.json",
-  "articles/virtual-machines/.openpublishing.redirection.virtual-machines.json"
+  "articles/virtual-machines/.openpublishing.redirection.virtual-machines.json",
+  "articles/operator-nexus/.openpublishing.redirection.operator-nexus.json"
 ]
 }

.openpublishing.redirection.azure-monitor.json

@@ -6463,6 +6463,11 @@
             "source_path_from_root": "/articles/azure-monitor/logs/resource-expression.md",
             "redirect_url": "/azure/azure-monitor/logs/cross-workspace-query",
             "redirect_document_id": false
+        },
+        {
+            "source_path_from_root": "/articles/azure-monitor/vm/vminsights-configure-workspace.md",
+            "redirect_url": "/azure/azure-monitor/vm/vminsights-enable-overview",
+            "redirect_document_id": false
         }
     ]
 }

.openpublishing.redirection.json

@@ -2770,6 +2770,11 @@
             "redirect_url": "/azure/container-registry/tutorial-customer-managed-keys",
             "redirect_document_id": false
         },
+        {
+            "source_path_from_root": "/articles/container-registry/container-registry-enable-conditional-access-policy.md",
+            "redirect_url": "/azure/container-registry/container-registry-configure-conditional-access.md",
+            "redirect_document_id": false 
+        },
         {
             "source_path": "articles/site-recovery/vmware-physical-secondary-disaster-recovery.md",
             "redirect_url": "/azure/site-recovery/vmware-physical-secondary-architecture",
@@ -3101,8 +3106,8 @@
             "redirect_document_id": false
         },
         {
-            "source_path": "active-directory/authentication/concept-mfa-plan.md",
-            "redirect_url": "active-directory/authentication/howto-mfa-getstarted",
+            "source_path": "articles/active-directory/authentication/concept-mfa-plan.md",
+            "redirect_url": "/entra/identity/authentication/howto-mfa-getstarted",
             "redirect_document_id": false
         },
         {
@@ -9622,6 +9627,11 @@
             "redirect_url": "/azure/azure-functions/functions-reference-python?pivots=python-mode-decorators#triggers-and-inputs",
             "redirect_document_id": false
         },
+        {
+            "source_path_from_root": "/articles/azure-functions/update-java-versions.md",
+            "redirect_url": "/azure/azure-functions/update-language-versions",
+            "redirect_document_id": false
+        },
         {
             "source_path_from_root": "/articles/azure-government/documentation-government-k8.md",
             "redirect_url": "/azure/azure-government",
@@ -15392,6 +15402,11 @@
             "redirect_url": "/azure/event-grid/scripts/event-grid-cli-subscribe-custom-topic",
             "redirect_document_id": false
         },
+        {
+            "source_path_from_root": "/articles/ai-studio/how-to/deploy-models.md",
+            "redirect_URL": "/azure/ai-studio/concepts/deployments-overview",
+            "redirect_document_id": true
+        },
         {
             "source_path_from_root": "/articles/notebooks/use-machine-learning-services-jupyter-notebooks.md",
             "redirect_url": "/azure/machine-learning/samples-notebooks",
@@ -23447,6 +23462,11 @@
             "redirect_url": "/azure/lighthouse/concepts/architecture",
             "redirect_document_id": true
         },
+        {
+            "source_path_from_root": "/articles/lighthouse/how-to/partner-earned-credit.md",
+            "redirect_url": "/azure/cost-management-billing/manage/link-partner-id",
+            "redirect_document_id": false
+        },
         {
             "source_path_from_root": "/articles/service-fabric-mesh/index.yml",
             "redirect_url": "/previous-versions/azure/service-fabric-mesh/service-fabric-mesh-overview",
@@ -25779,5 +25799,6 @@
             "redirect_url": "https://azure.microsoft.com/updates/preview-ai-toolchain-operator-addon-for-aks/",
             "redirect_document_id": false  
         }
+        
     ]
 }

articles/active-directory-b2c/configure-tokens.md

@@ -28,7 +28,7 @@ You can configure the token lifetime, including:
 
 - **Access and ID token lifetimes (minutes)** - The lifetime of the OAuth 2.0 bearer token and ID tokens. The default is 60 minutes (1 hour). The minimum (inclusive) is 5 minutes. The maximum (inclusive) is 1,440 minutes (24 hours).
 - **Refresh token lifetime (days)** - The maximum time period before which a refresh token can be used to acquire a new access token, if your application had been granted the `offline_access` scope. The default is 14 days. The minimum (inclusive) is one day. The maximum (inclusive) 90 days.
-- **Refresh token sliding window lifetime** - The refresh token sliding window type. `Bounded` indicates that the refresh token can be extended as specify in the **Lifetime length (days)**. `No expiry` indicates that the refresh token sliding window lifetime never expires.
+- **Refresh token sliding window lifetime** - The refresh token sliding window type. `Bounded` indicates that the refresh token can be extended as specified in the **Lifetime length (days)**. `No expiry` indicates that the refresh token sliding window lifetime never expires.
 - **Lifetime length (days)** - After this time period elapses the user is forced to reauthenticate, irrespective of the validity period of the most recent refresh token acquired by the application. The value must be greater than or equal to the **Refresh token lifetime** value.
 
 The following diagram shows the refresh token sliding window lifetime behavior.

articles/ai-services/computer-vision/concept-object-detection-40.md

@@ -24,6 +24,9 @@ Try out the capabilities of object detection quickly and easily in your browser
 > [!div class="nextstepaction"]
 > [Try Vision Studio](https://portal.vision.cognitive.azure.com/)
 
+> [!TIP]
+> You can use the Object detection feature through the [Azure OpenAI](/azure/ai-services/openai/overview) service. The **GPT-4 Turbo with Vision** model lets you chat with an AI assistant that can analyze the images you share, and the Vision Enhancement option uses Image Analysis to give the AI assistance more details (readable text and object locations) about the image. For more information, see the [GPT-4 Turbo with Vision quickstart](/azure/ai-services/openai/gpt-v-quickstart).
+
 ## Object detection example
 
 The following JSON response illustrates what the Analysis 4.0 API returns when detecting objects in the example image. 

articles/ai-services/computer-vision/concept-ocr.md

@@ -24,6 +24,9 @@ OCR traditionally started as a machine-learning-based technique for extracting t
 
 The new Computer Vision Image Analysis 4.0 REST API offers the ability to extract printed or handwritten text from images in a unified performance-enhanced synchronous API that makes it easy to get all image insights including OCR results in a single API operation. The Read OCR engine is built on top of multiple deep learning models supported by universal script-based models for [global language support](./language-support.md).
 
+> [!TIP]
+> You can use the OCR feature through the [Azure OpenAI](/azure/ai-services/openai/overview) service. The **GPT-4 Turbo with Vision** model lets you chat with an AI assistant that can analyze the images you share, and the Vision Enhancement option uses Image Analysis to give the AI assistance more details (readable text and object locations) about the image. For more information, see the [GPT-4 Turbo with Vision quickstart](/azure/ai-services/openai/gpt-v-quickstart).
+
 ## Text extraction example
 
 The following JSON response illustrates what the Image Analysis 4.0 API returns when extracting text from the given image.

articles/ai-services/computer-vision/how-to/background-removal.md

@@ -38,6 +38,7 @@ To authenticate against the Image Analysis service, you need an Azure AI Vision
 
 The SDK example assumes that you defined the environment variables `VISION_KEY` and `VISION_ENDPOINT` with your key and endpoint.
 
+<!--
 #### [C#](#tab/csharp)
 
 Start by creating a [VisionServiceOptions](/dotnet/api/azure.ai.vision.common.visionserviceoptions) object using one of the constructors. For example:
@@ -67,15 +68,16 @@ Where we used this helper function to read the value of an environment variable:
 [!code-cpp[](~/azure-ai-vision-sdk/docs/learn.microsoft.com/cpp/image-analysis/how-to/how-to.cpp?name=get_env_var)]
 
 #### [REST API](#tab/rest)
+-->
 
 Authentication is done by adding the HTTP request header **Ocp-Apim-Subscription-Key** and setting it to your vision key. The call is made to the URL `https://<endpoint>/computervision/imageanalysis:segment?api-version=2023-02-01-preview`, where `<endpoint>` is your unique Azure AI Vision endpoint URL. See [Select a mode ](./background-removal.md#select-a-mode) section for another query string you add to this URL.
 
----
 
 ## Select the image to analyze
 
 The code in this guide uses remote images referenced by URL. You may want to try different images on your own to see the full capability of the Image Analysis features.
 
+<!--
 #### [C#](#tab/csharp)
 
 Create a new **VisionSource** object from the URL of the image you want to analyze, using the static constructor [VisionSource.FromUrl](/dotnet/api/azure.ai.vision.common.visionsource.fromurl).
@@ -117,15 +119,17 @@ Create a new **VisionSource** object from the URL of the image you want to analy
 > You can also analyze a local image by passing in the full-path image file name (see [VisionSource::FromFile](/cpp/cognitive-services/vision/input-visionsource#fromfile)), or by copying the image into the SDK's input buffer (see  [VisionSource::FromImageSourceBuffer](/cpp/cognitive-services/vision/input-visionsource#fromimagesourcebuffer)). For more details, see [Call the Analyze API](./call-analyze-image-40.md?pivots=programming-language-cpp#select-the-image-to-analyze).
 
 #### [REST API](#tab/rest)
+-->
 
 When analyzing a remote image, you specify the image's URL by formatting the request body like this: `{"url":"https://learn.microsoft.com/azure/ai-services/computer-vision/images/windows-kitchen.jpg"}`. The **Content-Type** should be `application/json`.
 
 To analyze a local image, you'd put the binary image data in the HTTP request body. The **Content-Type** should be `application/octet-stream` or `multipart/form-data`.
 
----
+
 
 ## Select a mode
 
+<!--
 ### [C#](#tab/csharp)
 
 Create a new [ImageAnalysisOptions](/dotnet/api/azure.ai.vision.imageanalysis.imageanalysisoptions) object and set the property [SegmentationMode](/dotnet/api/azure.ai.vision.imageanalysis.imageanalysisoptions.segmentationmode#azure-ai-vision-imageanalysis-imageanalysisoptions-segmentationmode). This property must be set if you want to do segmentation. See [ImageSegmentationMode](/dotnet/api/azure.ai.vision.imageanalysis.imagesegmentationmode) for supported values.
@@ -151,6 +155,7 @@ Create a new [ImageAnalysisOptions](/cpp/cognitive-services/vision/imageanalysis
 [!code-cpp[](~/azure-ai-vision-sdk/docs/learn.microsoft.com/cpp/image-analysis/segmentation/segmentation.cpp?name=segmentation_mode)]
 
 ### [REST](#tab/rest)
+-->
 
 Set the query string *mode** to one of these two values. This query string is mandatory if you want to do image segmentation.
 
@@ -161,12 +166,12 @@ Set the query string *mode** to one of these two values. This query string is ma
 
 A populated URL for backgroundRemoval would look like this: `https://<endpoint>/computervision/imageanalysis:segment?api-version=2023-02-01-preview&mode=backgroundRemoval`
 
----
 
 ## Get results from the service
 
 This section shows you how to make the API call and parse the results.
 
+<!--
 #### [C#](#tab/csharp)
 
 The following code calls the Image Analysis API and saves the resulting segmented image to a file named **output.png**. It also displays some metadata about the segmented image.
@@ -196,10 +201,10 @@ The following code calls the Image Analysis API and saves the resulting segmente
 [!code-cpp[](~/azure-ai-vision-sdk/docs/learn.microsoft.com/cpp/image-analysis/segmentation/segmentation.cpp?name=segment)]
 
 #### [REST](#tab/rest)
+-->
 
 The service returns a `200` HTTP response on success with `Content-Type: image/png`, and the body contains the returned PNG image in the form of a binary stream.
 
----
 
 As an example, assume background removal is run on the following image:
 

articles/ai-services/computer-vision/how-to/model-customization.md

@@ -473,4 +473,4 @@ The API call returns an **ImageAnalysisResult** JSON object, which contains all
 In this guide, you created and trained a custom image classification model using Image Analysis. Next, learn more about the Analyze Image 4.0 API, so you can call your custom model from an application using REST or library SDKs.
 
 * See the [Model customization concepts](../concept-model-customization.md) guide for a broad overview of this feature and a list of frequently asked questions.
-* [Call the Analyze Image API](./call-analyze-image-40.md). Note the sections [Set model name when using a custom model](./call-analyze-image-40.md#set-model-name-when-using-a-custom-model) and [Get results using custom model](./call-analyze-image-40.md#get-results-using-custom-model).
+* [Call the Analyze Image API](./call-analyze-image-40.md). <!--Note the sections [Set model name when using a custom model](./call-analyze-image-40.md#set-model-name-when-using-a-custom-model) and [Get results using custom model](./call-analyze-image-40.md#get-results-using-custom-model).-->

articles/ai-services/computer-vision/how-to/shelf-model-customization.md

@@ -46,15 +46,14 @@ When your custom model is trained and ready (you've completed the steps in the [
 The API call will look like this:
 
 ```bash
-curl.exe -H "Ocp-Apim-Subscription-Key: <subscriptionKey>" -H "Content-Type: application/json" "https://<endpoint>/computervision/productrecognition/ms-pretrained-product-detection/models/<your_model_name>/runs/<your_run_name>?api-version=2023-04-01-preview" -d "{
+curl.exe -H "Ocp-Apim-Subscription-Key: <subscriptionKey>" -H "Content-Type: application/json" "https://<endpoint>/computervision/productrecognition/ms-pretrained-product-detection/runs/<your_run_name>?api-version=2023-04-01-preview" -d "{
     'url':'<your_url_string>'
 }"
 ```
 
 1. Make the following changes in the command where needed:
     1. Replace the `<subscriptionKey>` with your Vision resource key.
     1. Replace the `<endpoint>` with your Vision resource endpoint. For example: `https://YourResourceName.cognitiveservices.azure.com`.
-    1. Replace the `<your_model_name>` with your unique custom model name. This will be the name of the customized model you have trained with your own data. For example, `.../models/mymodel1/runs/...`
     2. Replace the `<your_run_name>` with your unique test run name for the task queue. It is an async API task queue name for you to be able retrieve the API response later. For example, `.../runs/test1?api-version...`
     1. Replace the `<your_url_string>` contents with the blob URL of the image
 1. Open a command prompt window.

articles/ai-services/computer-vision/includes/custom-vision-ia-compare.md

@@ -19,6 +19,7 @@ ms.author: pafarley
 |Web Portal |[Customvision.ai](https://www.customvision.ai/) |[Vision Studio](https://portal.vision.cognitive.azure.com/gallery/featured) |
 |Libraries |REST, SDK |REST, Python Sample |
 |Minimum training data needed |15 images per category |2-5 images per category |
-|Training data storage |Uploaded to service |In customer’s blob storage account |
-|Model hosting |Cloud and Edge |Cloud hosting only, Edge container hosting to come |
-|AI quotient (AIQ) | <table ><col ><col ></colgroup><thead><tr><th>context</th><th>IC</br>(top-1 accuracy, 22 datasets)</th><th>OD</br>(mAP@50, 59 datasets)</th></tr></thead><tbody><tr><td>0 shot</td><td>N/A</td><td>N/A</td></tr><tr><td>2 shot</td><td>51.47</td><td>33.3</td></tr><tr><td>3 shot</td><td>56.73</td><td>37.0</td></tr><tr><td>5 shot</td><td>63.01</td><td>43.4</td></tr><tr><td>10 shot</td><td>68.95</td><td>54.0</td></tr><tr><td>full</td><td>85.25</td><td>76.6</td></tr></tbody></table> | <table ><col ><col ></colgroup><thead><tr><th>context</th><th>IC</br>(top-1 accuracy, 22 datasets)</th><th>OD</br>(mAP@50, 59 datasets)</th></tr></thead><tbody><tr><td>0 shot</td><td>57.8</td><td>27.1</td></tr><tr><td>2 shot</td><td>73.02</td><td>49.2</td></tr><tr><td>3 shot</td><td>75.51</td><td>61.1</td></tr><tr><td>5 shot</td><td>79.14</td><td>68.2</td></tr><tr><td>10 shot</td><td>81.31</td><td>75.0</td></tr><tr><td>full</td><td>90.98</td><td>85.4</td></tr></tbody></table> |
+|Training data storage |Uploaded to service |Customer’s blob storage account |
+|Model hosting |Cloud and edge |Cloud hosting only, edge container hosting to come |
+|AI quality | <table ><col ><col ></colgroup><thead><tr><th>context</th><th>IC</br>(top-1 accuracy, 22 datasets)</th><th>OD</br>(mAP@50, 59 datasets)</th></tr></thead><tbody><tr><td>0 shot</td><td>N/A</td><td>N/A</td></tr><tr><td>2 shot</td><td>51.47</td><td>33.3</td></tr><tr><td>3 shot</td><td>56.73</td><td>37.0</td></tr><tr><td>5 shot</td><td>63.01</td><td>43.4</td></tr><tr><td>10 shot</td><td>68.95</td><td>54.0</td></tr><tr><td>full</td><td>85.25</td><td>76.6</td></tr></tbody></table> | <table ><col ><col ></colgroup><thead><tr><th>context</th><th>IC</br>(top-1 accuracy, 22 datasets)</th><th>OD</br>(mAP@50, 59 datasets)</th></tr></thead><tbody><tr><td>0 shot</td><td>57.8</td><td>27.1</td></tr><tr><td>2 shot</td><td>73.02</td><td>49.2</td></tr><tr><td>3 shot</td><td>75.51</td><td>61.1</td></tr><tr><td>5 shot</td><td>79.14</td><td>68.2</td></tr><tr><td>10 shot</td><td>81.31</td><td>75.0</td></tr><tr><td>full</td><td>90.98</td><td>85.4</td></tr></tbody></table> |
+| Pricing | [Custom Vision pricing](/pricing/details/cognitive-services/custom-vision-service/) | [Image Analysis pricing](/pricing/details/cognitive-services/computer-vision/) |