Merge branch 'main' of https://github.com/MicrosoftDocs/azure-docs-pr into fixes4

Author: billmath

articles/azure-monitor/agents/data-collection-text-log.md

@@ -122,12 +122,12 @@ To create the data collection rule in the Azure portal:
 
 1. Specify the following information:
 
-    - **File Pattern** - Identifies where the log files are located on the local disk. You can enter multiple file patterns separated by commas if your AMA is using Fluent Bit v1.5.1 or more.  
+    - **File Pattern** - Identifies where the log files are located on the local disk. You can enter multiple file patterns separated by commas (on Linux, AMA version 1.26 or higher is required to collect from a comma-separated list of file patterns).
 
         Examples of valid inputs: 
         - 20220122-MyLog.txt 
         - ProcessA_MyLog.txt  
-        - ErrorsOnly_MyLog.txt, WarningOnly_MyLog.txt 
+        - ErrorsOnly_MyLog.txt, WarningOnly_MyLog.txt
 
         > [!NOTE]
         > Multiple log files of the same type commonly exist in the same directory. For example, a machine might create a new file every day to prevent the log file from growing too large. To collect log data in this scenario, you can use a file wildcard. Use the format `C:\directoryA\directoryB\*MyLog.txt` for Windows and `/var/*.log` for Linux. There is no support for directory wildcards. 

articles/azure-video-indexer/release-notes.md

@@ -20,6 +20,15 @@ To stay up-to-date with the most recent Azure Video Indexer developments, this a
 
 ## May 2023
 
+### API breaking change
+
+We're introducing a change in behavior that may break your existing query logic. The change is in the **List** and **Search** APIs, find a detailed change between the current and the new behavior in a table that follows. You may need to update your code to utilize the [new APIs](https://api-portal.videoindexer.ai/).
+ 
+|API	|Current|New|The breaking change|
+|---|---|---|---|
+|List Videos|•	List all videos/projects according to 'IsBase' boolean parameter. If 'IsBase' is not defined, list both.<br/>•	Returns videos in all states (In progress/Proccessed/Failed).	|•	List Videos API will Return only videos (with paging) in all states.<br/>•	List Projects API will return only projects (with paging).|• List videos API was divided into two new API’s **List Videos** and **List Projects**<br/>•	The 'IsBase' parameter no longer has a meaning. |
+|Search Videos|•	Search all videos/projects according to 'IsBase' boolean parameter. If 'IsBase' is not defined, search both. <br/>•	Search videos in all states (In progress/Proccessed/Failed). |Search only processed videos.|•	Search Videos API will only search videos and not projects.<br/>•	The 'IsBase' parameter no longer has a meaning.<br/>•	Search Videos API will only search Processed videos (and not Failed/InProgress ones.)|
+
 ### Support for HTTP/2
 
 Added support for HTTP/2 for our [Data Plane API](https://api-portal.videoindexer.ai/). [HTTP/2](https://en.wikipedia.org/wiki/HTTP/2) offers several benefits over HTTP/1.1, which continues to be supported for backwards compatibility. One of the main benefits of HTTP/2 is increased performance, better reliability and reduced system resource requirements over HTTP/1.1. With this change we now support HTTP/2 for both the Video Indexer [Portal](https://videoindexer.ai/) and our Data Plane API. We advise to update your code to take advantage of this change.

articles/energy-data-services/how-to-use-managed-identity.md

@@ -98,7 +98,7 @@ To add the application ID:
    * [Access token](how-to-manage-users.md#prerequisites)
    * Application ID of the managed identity
 
-2. Use the [Add Member API](https://microsoft.github.io/meds-samples/rest-apis/index.html?page=/meds-samples/rest-apis/entitlements_openapi.yaml#/add-member-api/addMemberUsingPOST) to add the application ID of the user-assigned managed identity to the appropriate entitlement groups. 
+2. Use the [Add Member API](https://microsoft.github.io/adme-samples/rest-apis/index.html?page=/adme-samples/rest-apis/M12/entitlements_openapi.yaml#/add-member-api) to add the application ID of the user-assigned managed identity to the appropriate entitlement groups. 
 
    > [!NOTE]
    > In the following commands, be sure to use the application ID of the managed identity and not the object ID. 

articles/machine-learning/.openpublishing.redirection.machine-learning.json

@@ -5,6 +5,11 @@
         "redirect_url": "/azure/machine-learning/how-to-network-security-overview",
         "redirect_document_id": false
     },
+    {
+        "source_path_from_root": "/articles/machine-learning/how-to-manage-imported-data-assets.md",
+        "redirect_url": "/azure/machine-learning/",
+        "redirect_document_id": false
+    },
     {
         "source_path_from_root": "/articles/machine-learning/v1/how-to-workspace-diagnostic-api.md",
         "redirect_url": "/azure/machine-learning/how-to-workspace-diagnostic-api",

articles/machine-learning/how-to-image-processing-batch.md

@@ -66,7 +66,7 @@ __endpoint.yml__
 
 Run the following code to create the endpoint.
 
-:::code language="azurecli" source="~/azureml-examples-main/cli/endpoints/batch/deploy-models/imagenet-classifier/deploy-and-run.sh" ID="create_batch_endpoint" :::
+:::code language="azurecli" source="~/azureml-examples-main/cli/endpoints/batch/deploy-models/imagenet-classifier/deploy-and-run.sh" ID="create_endpoint" :::
 
 # [Python](#tab/python)
 
@@ -193,7 +193,7 @@ One the scoring script is created, it's time to create a batch deployment for it
 
    Then, create the deployment with the following command:
 
-   :::code language="azurecli" source="~/azureml-examples-main/cli/endpoints/batch/deploy-models/imagenet-classifier/deploy-and-run.sh" ID="create_batch_deployment_set_default" :::
+   :::code language="azurecli" source="~/azureml-examples-main/cli/endpoints/batch/deploy-models/imagenet-classifier/deploy-and-run.sh" ID="create_deployment" :::
 
    # [Python](#tab/python)
 
@@ -342,7 +342,7 @@ For testing our endpoint, we are going to use a sample of 1000 images from the o
 
    To download the predictions, use the following command:
 
-   :::code language="azurecli" source="~/azureml-examples-main/cli/endpoints/batch/deploy-models/imagenet-classifier/deploy-and-run.sh" ID="download_scores" :::
+   :::code language="azurecli" source="~/azureml-examples-main/cli/endpoints/batch/deploy-models/imagenet-classifier/deploy-and-run.sh" ID="download_outputs" :::
 
    # [Python](#tab/python)
 
@@ -398,7 +398,7 @@ On those cases, we may want to perform inference on the entire batch of data. Th
 
    Then, create the deployment with the following command:
 
-   :::code language="azurecli" source="~/azureml-examples-main/cli/endpoints/batch/deploy-models/imagenet-classifier/deploy-and-run.sh" ID="create_batch_deployment_ht" :::
+   :::code language="azurecli" source="~/azureml-examples-main/cli/endpoints/batch/deploy-models/imagenet-classifier/deploy-and-run.sh" ID="create_deployment_ht" :::
 
    # [Python](#tab/python)
 

articles/machine-learning/how-to-nlp-processing-batch.md

@@ -125,7 +125,7 @@ We are going to create a batch endpoint named `text-summarization-batch` where t
 
    # [Azure CLI](#tab/cli)
 
-   :::code language="azurecli" source="~/azureml-examples-main/cli/endpoints/batch/deploy-models/huggingface-text-summarization/deploy-and-run.sh" ID="create_batch_endpoint" :::
+   :::code language="azurecli" source="~/azureml-examples-main/cli/endpoints/batch/deploy-models/huggingface-text-summarization/deploy-and-run.sh" ID="create_endpoint" :::
 
    # [Python](#tab/python)
 
@@ -222,7 +222,7 @@ Let's create the deployment that will host the model:
 
    Then, create the deployment with the following command:
 
-   :::code language="azurecli" source="~/azureml-examples-main/cli/endpoints/batch/deploy-models/huggingface-text-summarization/deploy-and-run.sh" ID="create_batch_deployment_set_default" :::
+   :::code language="azurecli" source="~/azureml-examples-main/cli/endpoints/batch/deploy-models/huggingface-text-summarization/deploy-and-run.sh" ID="create_deployment" :::
 
    # [Python](#tab/python)
 

articles/machine-learning/how-to-use-batch-endpoints.md

@@ -97,7 +97,7 @@ A batch endpoint is an HTTPS endpoint that clients can call to trigger a batch i
     
     Run the following code to create a batch deployment under the batch endpoint and set it as the default deployment.
 
-    :::code language="azurecli" source="~/azureml-examples-main/cli/endpoints/batch/deploy-models/mnist-classifier/deploy-and-run.sh" ID="create_batch_endpoint" :::
+    :::code language="azurecli" source="~/azureml-examples-main/cli/endpoints/batch/deploy-models/mnist-classifier/deploy-and-run.sh" ID="create_endpoint" :::
 
     # [Python](#tab/python)
     
@@ -176,7 +176,7 @@ For instance, the following example downloads the output __score__ from the job.
 
 # [Azure CLI](#tab/cli)
 
-:::code language="azurecli" source="~/azureml-examples-main/cli/endpoints/batch/deploy-models/mnist-classifier/deploy-and-run.sh" ID="download_scores" :::
+:::code language="azurecli" source="~/azureml-examples-main/cli/endpoints/batch/deploy-models/mnist-classifier/deploy-and-run.sh" ID="download_outputs" :::
 
 # [Python](#tab/python)
 
@@ -212,7 +212,7 @@ To add a new deployment to an existing endpoint, use the  code:
 
 # [Azure CLI](#tab/cli)
 
-:::code language="azurecli" source="~/azureml-examples-main/cli/endpoints/batch/deploy-models/mnist-classifier/deploy-and-run.sh" ID="create_new_deployment_not_default" :::
+:::code language="azurecli" source="~/azureml-examples-main/cli/endpoints/batch/deploy-models/mnist-classifier/deploy-and-run.sh" ID="create_deployment_non_default" :::
 
 # [Python](#tab/python)
 

articles/virtual-machines/image-builder-api-update-release-notes.md

@@ -5,7 +5,7 @@ author: kof-f
 ms.service: virtual-machines
 ms.topic: conceptual
 ms.workload: infrastructure
-ms.date: 04/04/2022
+ms.date: 05/08/2023
 ms.reviewer: erd
 ms.subservice: image-builder
 ms.custom: references_regions
@@ -17,11 +17,30 @@ ms.custom: references_regions
 
 **Applies to:** :heavy_check_mark: Linux VMs :heavy_check_mark: Windows VMs :heavy_check_mark: Flexible scale sets :heavy_check_mark: Uniform scale sets
 
-This article contains all major API changes and feature updates for the Azure VM Image Builder service.
+This article contains all major API changes and feature updates for the Azure VM Image Builder (AIB) service.
 
 ## API releases
 
 
+### Version 2022-07-01
+
+**Improvements**
+- Added support to use the latest image version stored in Azure Compute Gallery as the source for the image template
+- Added `versioning` to support generating version numbers for image distributions. For more information, see [properties: versioning](../virtual-machines/linux/image-builder-json.md#versioning)
+- Added support for per region configuration when distributing to Azure Compute Gallery. For more information, see [Distribute:targetRegions](../virtual-machines/linux/image-builder-json.md#distribute-targetregions)
+- Added new 'File' validation type. For more information, see [validate properties](../virtual-machines/linux/image-builder-json.md#properties-validate)
+- VHDs can now be distributed to a custom blob or container in a custom storage account. For more information, see [Distribute: VHD](../virtual-machines/linux/image-builder-json.md#distribute-vhd)
+- Added support for using a [Direct Shared Gallery](/azure/virtual-machines/shared-image-galleries?tabs=azure-cli#sharing) image as the source for the image template
+
+
+**Changes**
+- `replicationRegions` is now deprecated for gallery distributions. For more information, use [gallery-replicated-regions](/cli/azure/image/builder/output?view=azure-cli-latest#az-image-builder-output-add-examples&preserve-view=true)
+- VHDs can now be distributed to a custom blob or container in a custom storage account
+- `targetRegions` array added and applied only to "SharedImage" type distribute. For more information on `targetRegions`, see [Azure Compute Gallery](../../articles/virtual-machines/azure-compute-gallery.md)
+- Added support for using a [Direct Shared Gallery](/azure/virtual-machines/shared-image-galleries?tabs=azure-cli#sharing) image as the source for the image template. Direct Shared Gallery is currently in preview.
+
+
+
 ### Version 2022-02-14
 
 **Improvements**