Merge pull request #218333 from MicrosoftDocs/repo_sync_working_branch

Confirm merge from repo_sync_working_branch to main to sync with https://github.com/MicrosoftDocs/azure-docs (branch main)

Author: huypub

articles/active-directory/devices/howto-vm-sign-in-azure-ad-windows.md

@@ -297,7 +297,7 @@ The AADLoginForWindows extension must be installed successfully for the VM to co
 1. View the device state by running `dsregcmd /status`. The goal is for the device state to show as `AzureAdJoined : YES`.
 
    > [!NOTE]
-   > Azure AD join activity is captured in Event Viewer under the *User Device Registration\Admin* log at *Event Viewer (local)\Applications* and *Services Logs\Windows\Microsoft\User Device Registration\Admin*.
+   > Azure AD join activity is captured in Event Viewer under the *User Device Registration\Admin* log at *Event Viewer (local)\Applications* and *Services Logs\Microsoft\Windows\User Device Registration\Admin*.
 
 If the AADLoginForWindows extension fails with an error code, you can perform the following steps.
 

articles/active-directory/enterprise-users/licensing-service-plan-reference.md

@@ -288,7 +288,7 @@ When managing licenses in [the Azure portal](https://portal.azure.com/#blade/Mic
 | Power BI Pro | POWER_BI_PRO | f8a1db68-be16-40ed-86d5-cb42ce701560 | EXCHANGE_S_FOUNDATION (113feb6c-3fe4-4440-bddc-54d774bf0318)<br/>BI_AZURE_P2 (70d33638-9c74-4d01-bfd3-562de28bd4ba) | Exchange Foundation (113feb6c-3fe4-4440-bddc-54d774bf0318)<br/>Power BI Pro (70d33638-9c74-4d01-bfd3-562de28bd4ba) |
 | Power BI Pro CE | POWER_BI_PRO_CE | 420af87e-8177-4146-a780-3786adaffbca | EXCHANGE_S_FOUNDATION (113feb6c-3fe4-4440-bddc-54d774bf0318)<br/>BI_AZURE_P2 (70d33638-9c74-4d01-bfd3-562de28bd4ba) | Exchange Foundation (113feb6c-3fe4-4440-bddc-54d774bf0318)<br/>Power BI Pro (70d33638-9c74-4d01-bfd3-562de28bd4ba) |
 | Power BI Pro Dept | POWER_BI_PRO_DEPT | 3a6a908c-09c5-406a-8170-8ebb63c42882 | EXCHANGE_S_FOUNDATION (113feb6c-3fe4-4440-bddc-54d774bf0318)<br/>BI_AZURE_P2 (70d33638-9c74-4d01-bfd3-562de28bd4ba) | Exchange Foundation (113feb6c-3fe4-4440-bddc-54d774bf0318)<br/>Power BI Pro (70d33638-9c74-4d01-bfd3-562de28bd4ba) |
-| Power BI Pro for GCC | POWERBI_PRO_GOV |	f0612879-44ea-47fb-baf0-3d76d9235576 | EXCHANGE_S_FOUNDATION_GOV (922ba911-5694-4e99-a794-73aed9bfeec8)<br/>BI_AZURE_P_2_GOV (944e9726-f011-4353-b654-5f7d2663db76) | Exchange Foundation for Government (922ba911-5694-4e99-a794-73aed9bfeec8)</br>Power BI Pro for Government (944e9726-f011-4353-b654-5f7d2663db76) |
+| Power BI Pro for GCC | POWERBI_PRO_GOV |	f0612879-44ea-47fb-baf0-3d76d9235576 | EXCHANGE_S_FOUNDATION_GOV (922ba911-5694-4e99-a794-73aed9bfeec8)<br/>BI_AZURE_P_2_GOV (944e9726-f011-4353-b654-5f7d2663db76) | Exchange Foundation for Government (922ba911-5694-4e99-a794-73aed9bfeec8)<br/>Power BI Pro for Government (944e9726-f011-4353-b654-5f7d2663db76) |
 | Power Virtual Agent |	VIRTUAL_AGENT_BASE | e4e55366-9635-46f4-a907-fc8c3b5ec81f | CDS_VIRTUAL_AGENT_BASE (0a0a23fa-fea1-4195-bb89-b4789cb12f7f)<br/>FLOW_VIRTUAL_AGENT_BASE (4b81a949-69a1-4409-ad34-9791a6ec88aa)<br/>VIRTUAL_AGENT_BASE (f6934f16-83d3-4f3b-ad27-c6e9c187b260) | Common Data Service for Virtual Agent Base (0a0a23fa-fea1-4195-bb89-b4789cb12f7f)<br/>Power Automate for Virtual Agent (4b81a949-69a1-4409-ad34-9791a6ec88aa)<br/>Virtual Agent Base (f6934f16-83d3-4f3b-ad27-c6e9c187b260) |
 | Power Virtual Agents Viral Trial | CCIBOTS_PRIVPREV_VIRAL |	606b54a9-78d8-4298-ad8b-df6ef4481c80 | DYN365_CDS_CCI_BOTS (cf7034ed-348f-42eb-8bbd-dddeea43ee81)<br/>CCIBOTS_PRIVPREV_VIRAL (ce312d15-8fdf-44c0-9974-a25a177125ee)<br/>FLOW_CCI_BOTS (5d798708-6473-48ad-9776-3acc301c40af) | Common Data Service for CCI Bots (cf7034ed-348f-42eb-8bbd-dddeea43ee81)<br/>Dynamics 365 AI for Customer Service Virtual Agents Viral (ce312d15-8fdf-44c0-9974-a25a177125ee)<br/>Flow for CCI Bots (5d798708-6473-48ad-9776-3acc301c40af) |
 | Project for Office 365	| PROJECTCLIENT	| a10d5e58-74da-4312-95c8-76be4e5b75a0	| PROJECT_CLIENT_SUBSCRIPTION (fafd7243-e5c1-4a3a-9e40-495efcb1d3c3) | PROJECT ONLINE DESKTOP CLIENT (fafd7243-e5c1-4a3a-9e40-495efcb1d3c3) |

articles/azure-monitor/app/java-jmx-metrics-configuration.md

@@ -1,6 +1,6 @@
 ---
 title: How to configure JMX metrics - Azure Monitor application insights for Java
-description: Configure additional JMX metrics collection for Azure Monitor application insights Java agent
+description: Configure additional JMX metrics collection for Azure Monitor Application Insights Java agent
 ms.topic: conceptual
 ms.date: 03/16/2021
 ms.devlang: java

articles/azure-monitor/change/change-analysis.md

@@ -126,6 +126,8 @@ Currently the following dependencies are supported in **Web App Diagnose and sol
 - **App Services file changes**: File changes take up to 30 minutes to display.
 - **App Services configuration changes**: Due to the snapshot approach to configuration changes, timestamps of configuration changes could take up to 6 hours to display from when the change actually happened.
 - **Web app deployment and configuration changes**: Since these changes are collected by a site extension and stored on disk space owned by your application, data collection and storage is subject to your application's behavior. Check to see if a misbehaving application is affecting the results.
+- **Snapshot retention for all changes**: The Change Analysis data for resources is tracked by Azure Resource Graphs (ARG). ARG keeps snapshot history of tracked resources only for 14 days.
+
 
 ## Next steps
 

articles/azure-resource-manager/templates/quickstart-create-templates-use-the-portal.md

@@ -13,7 +13,7 @@ ms.custom: contperf-fy21q3, mode-ui
 
 In this quickstart, you learn how to create an Azure Resource Manager template (ARM template) in the Azure portal. You edit and deploy the template from the portal.
 
-ARM templates are JSON files that define the resources you need to deploy for your solution. To understand the concepts associated with deploying and managing your Azure solutions, see [template deployment overview](overview.md).
+ARM templates are JSON or Bicep files that define the resources you need to deploy for your solution. To understand the concepts associated with deploying and managing your Azure solutions, see [template deployment overview](overview.md).
 
 After completing the tutorial, you deploy an Azure Storage account. The same process can be used to deploy other Azure resources.
 
@@ -54,7 +54,7 @@ Rather than manually building an entire ARM template, let's start by retrieving
 
 You can use the portal for quickly developing and deploying ARM templates. In general, we recommend using Visual Studio Code for developing your ARM templates, and Azure CLI or Azure PowerShell for deploying the template, but you can use the portal for quick deployments without installing those tools.
 
-In this section, let's suppose you have an ARM template that you want to deploy one time with setting up the other tools.
+In this section, let's suppose you have an ARM template that you want to deploy one time without setting up the other tools.
 
 1. Again, select **Deploy a custom template** in the portal.
 

articles/confidential-ledger/quickstart-python.md

@@ -194,14 +194,15 @@ entry = ledger_client.get_ledger_entry(transaction_id=append_result['transaction
 print(f"Entry (transaction id = {entry['transactionId']}) in collection {entry['collectionId']}: {entry['contents']}")
 ```
 
-If you would simply like the latest transaction that was committed to the ledger, you can use the `get_current_ledger_entry` function.
+If you just want the latest transaction that was committed to the ledger, you can use the `get_current_ledger_entry` function.
+
 
 ```python
 latest_entry = ledger_client.get_current_ledger_entry()
 print(f"Current entry (transaction id = {latest_entry['transactionId']}) in collection {latest_entry['collectionId']}: {latest_entry['contents']}")
 ```
 
-The print function will return "Hello world!", as that is the message in the ledger that that corresponds to the transaction ID and is the latest transaction.
+The print function will return "Hello world!", as that's the message in the ledger that corresponds to the transaction ID and is the latest transaction.
 
 ## Full sample code
 
@@ -301,7 +302,7 @@ print(f"Current entry (transaction id = {latest_entry['transactionId']}) in coll
 
 ## Pollers
 
-If you would like to wait for your write transaction to be committed to your ledger you can use the `begin_create_ledger_entry` function. This will return a poller to wait until the entry is durably committed.
+If you'd like to wait for your write transaction to be committed to your ledger, you can use the `begin_create_ledger_entry` function. This will return a poller to wait until the entry is durably committed.
 
 ```python
 sample_entry = {"contents": "Hello world!"}

articles/container-registry/container-registry-firewall-access-rules.md

@@ -19,6 +19,8 @@ To pull or push images or other artifacts to an Azure container registry, a clie
 
 * **Registry REST API endpoint** - Authentication and registry management operations are handled through the registry's public REST API endpoint. This endpoint is the login server name of the registry. Example: `myregistry.azurecr.io`
 
+* **Registry REST API endpoint for certificates** - Azure container registry uses a wildcard SSL certificate for all subdomains. When connecting to the Azure container registry using SSL, the client must be able to download the certificate for the TLS handshake. In such cases, `azurecr.io` must also be accessible.
+
 * **Storage (data) endpoint** - Azure [allocates blob storage](container-registry-storage.md) in Azure Storage accounts on behalf of each registry to manage the data for container images and other artifacts. When a client accesses image layers in an Azure container registry, it makes requests using a storage account endpoint provided by the registry.
 
 If your registry is [geo-replicated](container-registry-geo-replication.md), a client might need to interact with the data endpoint in a specific region or in multiple replicated regions.
@@ -204,4 +206,4 @@ If you need to access Microsoft Container Registry (MCR) from behind a firewall,
 <!-- LINKS - Internal -->
 
 [az-acr-update]: /cli/azure/acr#az_acr_update
-[az-acr-show-endpoints]: /cli/azure/acr#az_acr_show_endpoints
+[az-acr-show-endpoints]: /cli/azure/acr#az_acr_show_endpoints

articles/hdinsight/hdinsight-hadoop-oms-log-analytics-tutorial.md

@@ -232,7 +232,7 @@ $LAW = "<your-Log-Analytics-workspace>"
 # obtain workspace id for defined Log Analytics workspace
 $WorkspaceId = (Get-AzOperationalInsightsWorkspace `
                     -ResourceGroupName $resourceGroup `
-                    -Name $LAW).CustomerId
+                    -Name $LAW).ResourceId
 
 # obtain primary key for defined Log Analytics workspace
 $PrimaryKey = (Get-AzOperationalInsightsWorkspace `

articles/machine-learning/concept-data.md

@@ -23,7 +23,7 @@ ms.custom: devx-track-python, data4ml, event-tier1-build-2022
 Azure Machine Learning lets you bring data from a local machine or an existing cloud-based storage. In this article you will learn the main data concepts in Azure Machine Learning, including:
 
 > [!div class="checklist"]
-> - [**URIs**](#uris) - A **U**niform **R**esource **I**dentifier that is a reference to a storage location on your local computer or in the cloud that makes it very easy to access data in your jobs. Azure Machine Learning distinguishes two types of URIs:`uri_file` and `uri_folder`. If you want to consume a file as an input of a job, You can define this job input by providing `type` as `uri_file`, `path` as where the file is.
+> - [**URIs**](#uris) - A **U**niform **R**esource **I**dentifier that is a reference to a storage location on your local computer or in the cloud that makes it very easy to access data in your jobs. Azure Machine Learning distinguishes two types of URIs:`uri_file` and `uri_folder`. If you want to consume a file as an input of a job, you can define this job input by providing `type` as `uri_file`, `path` as where the file is.
 > - [**MLTable**](#mltable) - `MLTable` helps you to abstract the schema definition for tabular data so it is more suitable for complex/changing schema or to be leveraged in automl. If you just want to create an data asset for a job or you want to write your own parsing logic in python you could use `uri_file`, `uri_folder`.
 > - [**Data asset**](#data-asset) - If you plan to share your data (URIs or MLTables) in your workspace to team members, or you want to track data versions, or track lineage, you can create data assets from URIs or MLTables you have. But if you didn't create data asset, you can still consume the data in jobs without lineange tracking, version management, etc.
 > - [**Datastore**](#datastore) - Azure Machine Learning Datastores securely keep the connection information(storage container name, credentials) to your data storage on Azure, so you don't have to code it in your scripts. You can use AzureML datastore uri and relative path to your data to point to your data. You can also register files/folders in your AzureML datastore into data assets.

articles/service-fabric/service-fabric-get-started.md

@@ -32,7 +32,7 @@ For latest Runtime and SDK you can download from below:
 
 | Package |Version|
 | --- | --- |
-|[Install Service fabric runtime for Windows](https://download.microsoft.com/download/b/8/a/b8a2fb98-0ec1-41e5-be98-9d8b5abf7856/MicrosoftServiceFabric.9.1.1390.9590.exe) | 9.1.1390 |
+|[Install Service Fabric Runtime for Windows](https://download.microsoft.com/download/b/8/a/b8a2fb98-0ec1-41e5-be98-9d8b5abf7856/MicrosoftServiceFabric.9.1.1390.9590.exe) | 9.1.1390 |
 |[Install Service Fabric SDK](https://download.microsoft.com/download/b/8/a/b8a2fb98-0ec1-41e5-be98-9d8b5abf7856/MicrosoftServiceFabricSDK.6.1.1390.msi) | 6.1.1390 |
 
 You can find direct links to the installers for previous releases on [Service Fabric Releases](https://github.com/microsoft/service-fabric/tree/master/release_notes)