Merge pull request #222629 from MicrosoftDocs/main

12/29 AM Publish

Author: huypub

articles/active-directory/cloud-infrastructure-entitlement-management/TOC.yml

@@ -89,6 +89,8 @@
     - name: Manage users, roles, and their access levels
       expanded: false
       items:
+      - name: Add or remove a user in Permissions Management
+        href: how-to-add-remove-user-to-group.md
       - name: Manage users and groups
         href: ui-user-management.md
       # - name: Define and manage users, roles, and access levels

articles/active-directory/cloud-infrastructure-entitlement-management/how-to-add-remove-user-to-group.md

@@ -0,0 +1,56 @@
+---
+title: Add or remove a user in Permissions Management through the Microsoft Entra admin center
+description: How to add or remove a user in Permissions Management through Azure Active Directory (AD).
+services: active-directory
+author: jenniferf-skc
+manager: amycolannino
+ms.service: active-directory 
+ms.subservice: ciem
+ms.workload: identity
+ms.topic: how-to
+ms.date: 12/28/2022
+ms.author: jfields
+---
+
+# Add or remove a user in Permissions Management
+
+This article describes how you can add or remove a new user for a group in Permissions Management. 
+
+> [!NOTE] 
+> Permissions Management entitlements work through group-based access. To add a new user, you must add a user to a group through Azure Active Directory (AD).
+
+## Add a user
+
+1. Navigate to the [Microsoft Entra admin center](https://entr.microsoft.com/#home). 
+1. From the Azure Active Directory tile, select **Go to Azure Active Directory**. 
+1. From the navigation pane, select the **Groups** drop-down menu, then **All groups**.
+1. Select the group name for the group you want to add the user to.
+1. From the group's **Manage** menu, click **Members**.
+1. Click **+ Add members**, then search for the user you want to add from the list.
+    > [!NOTE]
+    > In order to add a user to a group, you must be the group owner. If you're not the owner of the           
+      selected group, please reach out to the group owner. If you don't know who the owner of the group is, 
+      select **Owners** under the group's **Manage** menu.
+7. Click **Select**. Your user has been added. 
+8. Click the **Refresh** button to refresh your screen and view the user you've added.
+
+
+## Remove a user
+
+1. Navigate to the Microsoft [Entra admin center](https://entr.microsoft.com/#home). 
+1. From the Azure Active Directory tile, select **Go to Azure Active Directory**. 
+1. From the navigation pane, select the **Groups** drop-down menu, then **All groups**.
+1. Select the group name for the group you want to remove the user from.
+1. From the groups **Manage** menu, click **Members**.
+1. Search for the user you want to remove from the list, then check the box next to their name.
+    > [!NOTE]
+    > In order to remove a user from a group, you must be the group owner. If you're not the owner of the 
+    selected group, please reach out to the group owner. If you don't know who the owner of the group is, 
+    select **Owners** under the group's **Manage** menu.
+7. Click **X Remove**, then click **Yes**. The user is removed from the group.
+
+
+## Next steps
+
+- For more information on managing users and groups, see [Manage users and groups with the User management dashboard](ui-user-management.md).
+- For more information on setting group permissions, see [Select group-based permissions settings](how-to-create-group-based-permissions.md).

articles/aks/node-access.md

@@ -39,13 +39,7 @@ aks-nodepool1-12345678-vmss000001   Ready    agent   13m     v1.19.9   10.240.0.
 aksnpwin000000                      Ready    agent   87s     v1.19.9   10.240.0.67   <none>        Windows Server 2019 Datacenter   10.0.17763.1935    docker://19.3.1
 ```
 
-Us the `kubectl debug` command to run a container image on the node to connect to it.
-
-```bash
-kubectl debug node/aks-nodepool1-12345678-vmss000000 -it --image=mcr.microsoft.com/dotnet/runtime-deps:6.0
-```
-
-The following command starts a privileged container on your node and connects to it.
+Use the `kubectl debug` command to run a container image on the node to connect to it. The following command starts a privileged container on your node and connects to it.
 
 ```bash
 kubectl debug node/aks-nodepool1-12345678-vmss000000 -it --image=mcr.microsoft.com/dotnet/runtime-deps:6.0

articles/application-gateway/application-gateway-autoscaling-zone-redundant.md

@@ -14,7 +14,7 @@ ms.custom: fasttrack-edit, references_regions
 
 Application Gateway and WAF can be configured to scale in two modes:
 
-- **Autoscaling** - With autoscaling enabled, the Application Gateway and WAF v2 SKUs scale out or in based on application traffic requirements. This mode offers better elasticity to your application and eliminates the need to guess the application gateway size or instance count. This mode also allows you to save cost by not requiring the gateway to run at peak-provisioned capacity for expected maximum traffic load. You must specify a minimum and optionally maximum instance count. Minimum capacity ensures that Application Gateway and WAF v2 don't fall below the minimum instance count specified, even without traffic. Each instance is roughly equivalent to 10 more reserved Capacity Units. Zero signifies no reserved capacity and is purely autoscaling in nature. You can also optionally specify a maximum instance count, which ensures that the Application Gateway doesn't scale beyond the specified number of instances. You'll only be billed for the amount of traffic served by the Gateway. The instance counts can range from 0 to 125. The default value for maximum instance count is 20 if not specified.
+- **Autoscaling** - With autoscaling enabled, the Application Gateway and WAF v2 SKUs scale out or in based on application traffic requirements. This mode offers better elasticity to your application and eliminates the need to guess the application gateway size or instance count. This mode also allows you to save cost by not requiring the gateway to run at peak-provisioned capacity for expected maximum traffic load. You must specify a minimum and optionally maximum instance count. Minimum capacity ensures that Application Gateway and WAF v2 don't fall below the minimum instance count specified, even without traffic. Each instance is roughly equivalent to 10 more reserved Capacity Units. Zero signifies no reserved capacity and is purely autoscaling in nature. You can also optionally specify a maximum instance count, which ensures that the Application Gateway doesn't scale beyond the specified number of instances. You'll only be billed for the amount of traffic served by the Gateway. The instance counts can range from 0 to 125. The default value for maximum instance count is 10 if not specified.
 - **Manual** - You can also choose Manual mode where the gateway won't autoscale. In this mode, if there's more traffic than what Application Gateway or WAF can handle, it could result in traffic loss. With manual mode, specifying instance count is mandatory. Instance count can vary from 1 to 125 instances.
 
 ## Autoscaling and High Availability

articles/applied-ai-services/form-recognizer/containers/form-recognizer-container-install-run.md

@@ -32,7 +32,7 @@ You'll also need the following to use Form Recognizer containers:
 | **Familiarity with Docker** | You should have a basic understanding of Docker concepts, like registries, repositories, containers, and container images, as well as knowledge of basic `docker`  [terminology and commands](/dotnet/architecture/microservices/container-docker-introduction/docker-terminology). |
 | **Docker Engine installed** | <ul><li>You need the Docker Engine installed on a [host computer](#host-computer-requirements). Docker provides packages that configure the Docker environment on [macOS](https://docs.docker.com/docker-for-mac/), [Windows](https://docs.docker.com/docker-for-windows/), and [Linux](https://docs.docker.com/engine/installation/#supported-platforms). For a primer on Docker and container basics, see the [Docker overview](https://docs.docker.com/engine/docker-overview/).</li><li> Docker must be configured to allow the containers to connect with and send billing data to Azure. </li><li> On **Windows**, Docker must also be configured to support **Linux** containers.</li></ul>  |
 |**Form Recognizer resource** | A [**single-service Azure Form Recognizer**](https://portal.azure.com/#create/Microsoft.CognitiveServicesFormRecognizer) or [**multi-service Cognitive Services**](https://portal.azure.com/#create/Microsoft.CognitiveServicesAllInOne) resource in the Azure portal. To use the containers, you must have the associated key and endpoint URI. Both values are available on the Azure portal Form Recognizer **Keys and Endpoint** page: <ul><li>**{FORM_RECOGNIZER_KEY}**: one of the two available resource keys.<li>**{FORM_RECOGNIZER_ENDPOINT_URI}**: the endpoint for the resource used to track billing information.</li></li></ul>|
-| **Computer Vision API resource** | **To process business cards, ID documents, or Receipts, you'll need a Computer Vision resource.** <ul><li>You can access the Recognize Text feature as either an Azure resource (the REST API or SDK) or a **cognitive-services-recognize-text** [container](../../../cognitive-services/Computer-vision/computer-vision-how-to-install-containers.md#get-the-container-image-with-docker-pull). The usual [billing](#billing) fees apply.</li> <li>If you use the **cognitive-services-recognize-text** container, make sure that your Computer Vision key for the Form Recognizer container is the key specified in the Computer Vision `docker run`  or `docker compose` command for the **cognitive-services-recognize-text** container and  your billing endpoint is the container's endpoint (for example, `http://localhost:5000`). If you use both the Computer Vision container and Form Recognizer container together on the same host, they can't both be started with the default port of *5000*. </li></ul></br>Pass in both the key and endpoints for your Computer Vision Azure cloud or Cognitive Services container:<ul><li>**{COMPUTER_VISION_KEY}**: one of the two available resource keys.</li><li> **{COMPUTER_VISION_ENDPOINT_URI}**: the endpoint for the resource used to track billing information.</li></ul> |
+| **Computer Vision API resource** | **To process business cards, ID documents, or Receipts, you'll need a Computer Vision resource.** <ul><li>You can access the Recognize Text feature as either an Azure resource (the REST API or SDK) or a **cognitive-services-recognize-text** [container](../../../cognitive-services/Computer-vision/computer-vision-how-to-install-containers.md#get-the-container-image). The usual [billing](#billing) fees apply.</li> <li>If you use the **cognitive-services-recognize-text** container, make sure that your Computer Vision key for the Form Recognizer container is the key specified in the Computer Vision `docker run`  or `docker compose` command for the **cognitive-services-recognize-text** container and  your billing endpoint is the container's endpoint (for example, `http://localhost:5000`). If you use both the Computer Vision container and Form Recognizer container together on the same host, they can't both be started with the default port of *5000*. </li></ul></br>Pass in both the key and endpoints for your Computer Vision Azure cloud or Cognitive Services container:<ul><li>**{COMPUTER_VISION_KEY}**: one of the two available resource keys.</li><li> **{COMPUTER_VISION_ENDPOINT_URI}**: the endpoint for the resource used to track billing information.</li></ul> |
 
 |Optional|Purpose|
 |---------|----------|

articles/automation/how-to/region-mappings.md

@@ -1,10 +1,10 @@
 ---
 title: Supported regions for linked Log Analytics workspace
 description: This article describes the supported region mappings between an Automation account and a Log Analytics workspace as it relates to certain features of Azure Automation.
-ms.date: 11/29/2022
+ms.date: 12/29/2022
 services: automation
 ms.topic: conceptual
-ms.custom: references_regions, engagement-fy23
+ms.custom: references_regions
 ---
 
 # Supported regions for linked Log Analytics workspace
@@ -75,6 +75,7 @@ The following table shows the supported mappings:
 |SouthCentralUS|SouthCentralUS|
 |WestUS|WestUS|
 |WestUS2|WestUS2|
+|WestUS3|WestUS3|
 |WestCentralUS|WestCentralUS|
 
 <sup>1</sup> EastUS mapping for Log Analytics workspaces to Automation accounts isn't an exact region-to-region mapping, but is the correct mapping.

articles/azure-monitor/alerts/alerts-dynamic-thresholds.md

@@ -105,12 +105,11 @@ If the behavior of a metric changed recently, the changes won't necessarily be r
 
 To identify weekly seasonality, the Dynamic Thresholds model requires at least three weeks of historical data. When enough historical data is available, any weekly seasonality that exists in the metric data is identified and the model is adjusted accordingly.
 
-## Dynamic Thresholds shows a negative lower bound for a metric even though the metric always has positive values
+## Dynamic Thresholds is showing values that are not within the range of expected values
 
-When a metric exhibits large fluctuation, Dynamic Thresholds builds a wider model around the metric values. This action can result in the lower border being below zero. Specifically, this scenario can happen when:
+When a metric exhibits large fluctuation, Dynamic Thresholds builds a wider model around the metric values. This model can result in a lower border below zero when the metric only has positive values, or in an upper border above 100% when the metric can't exceed 100%. This scenario can happen when:
 
 - The sensitivity is set to low.
-- The median values are close to zero.
 - The metric exhibits an irregular behavior with high variance, which appears as spikes or dips in the data.
 
 When the lower bound has a negative value, it's plausible for the metric to reach a zero value given the metric's irregular behavior. Consider choosing a higher sensitivity or a larger **Aggregation granularity (Period)** to make the model less sensitive. Or, use the **Ignore data before** option to exclude a recent irregularity from the historical data used to build the model.
@@ -306,4 +305,4 @@ Use the following information to interpret the chart:
 - **Red dot with a black circle**: Shows the first metric value out of the allowed range. This value fires a metric alert and puts it in an active state.
 - **Red dots**: Indicate other measured values outside of the allowed range. They won't fire more metric alerts, but the alert stays in the active state.
 - **Red area**: Shows the time when the metric value was outside of the allowed range. The alert remains in the active state as long as subsequent measured values are out of the allowed range, but no new alerts are fired.
-- **End of red area**: When the blue line is back inside the allowed values, the red area stops and the measured value line turns blue. The status of the metric alert fired at the time of the red dot with black outline is set to resolved.
+- **End of red area**: When the blue line is back inside the allowed values, the red area stops and the measured value line turns blue. The status of the metric alert fired at the time of the red dot with black outline is set to resolved.

articles/backup/backup-azure-troubleshoot-slow-backup-performance-issue.md

@@ -2,7 +2,11 @@
 title: Troubleshoot slow backup of files and folders
 description: Provides troubleshooting guidance to help you diagnose the cause of Azure Backup performance issues
 ms.topic: troubleshooting
-ms.date: 07/05/2019
+ms.date: 12/28/2022
+author: v-amallick
+ms.service: backup
+ms.author: v-amallick
+ms.custom: engagement-fy23
 ---
 # Troubleshoot slow backup of files and folders in Azure Backup
 
@@ -26,7 +30,7 @@ We also strongly recommend that you review the [Azure Backup service FAQ](backup
 * Unoptimized mode is slow because the agent has to scan each and every file on the volume and compare against the metadata to determine the changed files.
 * To verify this, open **Job Details** from the MARS agent console  and check the status to see if it says **Transferring data (unoptimized, may take more time)** as shown below:
 
-    ![Running in unoptimized mode](./media/backup-azure-troubleshoot-slow-backup-performance-issue/unoptimized-mode.png)
+    ![Screenshot shows backup jobs running in unoptimized mode.](./media/backup-azure-troubleshoot-slow-backup-performance-issue/unoptimized-mode.png)
 
 * The following conditions can cause the backup job to run in unoptimized mode:
   * First backup (also known as Initial Replication) will always run in unoptimized mode