Merge pull request #2742 from MicrosoftDocs/repo_sync_working_branch

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

Author: Taojunshen

articles/machine-learning/how-to-access-azureml-behind-firewall.md

@@ -395,7 +395,7 @@ __Azure Machine Learning compute instance and compute cluster hosts__
 > * Ports 8787 and 18881 for __compute instance__ are only needed when your Azure Machine workspace has a private endpoint.
 > * In the following table, replace `<storage>` with the name of the default storage account for your Azure Machine Learning workspace.
 > * In the following table, replace `<region>` with the Azure region that contains your Azure Machine Learning workspace.
-> * Websocket communication must be allowed to the compute instance. If you block websocket traffic, Jupyter notebooks won't work correctly.
+> * WebSocket communication must be allowed to the compute instance. If you block websocket traffic, Jupyter notebooks won't work correctly.
 
 # [Azure public](#tab/public)
 

articles/machine-learning/how-to-managed-network.md

@@ -1178,7 +1178,8 @@ The Azure Machine Learning managed virtual network feature is free. However, you
 
 * Once you enable managed virtual network isolation of your workspace (either allow internet outbound or allow only approved outbound), you can't disable it.
 * Managed virtual network uses private endpoint connection to access your private resources. You can't have a private endpoint and a service endpoint at the same time for your Azure resources, such as a storage account. We recommend using private endpoints in all scenarios.
-* The managed virtual network is deleted when the workspace is deleted. When deleting Azure Machine Learning resources in your Azure subscription, disable any resource locks or locks which prevent deletion of resources you created, or were created by Microsoft for the managed virtual network.
+* The managed virtual network is deleted when the workspace is deleted.
+* Make sure there are no __scope locks__ on the Azure Machine Learning resources and resource group. Internal operations related to managed virtual network might be blocked.
 * Data exfiltration protection is automatically enabled for the only approved outbound mode. If you add other outbound rules, such as to FQDNs, Microsoft can't guarantee that you're protected from data exfiltration to those outbound destinations.
 * Creating a compute cluster in a different region than the workspace isn't supported when using a managed virtual network.
 * Kubernetes and attached VMs aren't supported in an Azure Machine Learning managed virtual network.

articles/search/search-region-support.md

@@ -60,7 +60,7 @@ AI service integration refers to internal connections to an Azure AI multi-servi
 |--|--|--|--|--|
 | North Europe​​ | ✅ | ✅ | ✅ | All tiers|
 | West Europe​​ <sup>1</sup>| ✅ | ✅ | ✅ | All Tiers |
-| France Central​​ | ✅ | ✅ | ✅ | Basic, S1|
+| France Central​​ | ✅ | ✅ | ✅ | All Tiers|
 | Germany West Central​ <sup>1</sup>​| ✅ |  | ✅ | |
 | Italy North​​ |  |  | ✅ | |
 | Norway East​​ | ✅ |  | ✅ |  |

articles/search/search-sku-tier.md

@@ -59,7 +59,7 @@ Currently, several regions are capacity-constrained for specific tiers and can't
 
 | Region | Disabled tier (SKU) due to over-capacity | Suggested alternative |
 |--------|------------------------------------------|-----------------------|
-| France Central | Basic, S1| Sweden Central, Switzerland North|
+| France Central | All tiers| Sweden Central, Switzerland North|
 | North Europe | All tiers | Sweden Central, Switzerland North|
 | West Europe | All tiers | Sweden Central, Switzerland North|