Merge pull request #236789 from MicrosoftDocs/repo_sync_working_branch

huypub · web-flow · commit 746499fea1ca · 2023-05-03T14:53:04.000-07:00
Confirm merge from repo_sync_working_branch to main to sync with https://github.com/MicrosoftDocs/azure-docs (branch main)
diff --git a/articles/active-directory/authentication/concept-authentication-strengths.md b/articles/active-directory/authentication/concept-authentication-strengths.md
@@ -203,8 +203,6 @@ An authentication strength Conditional Access policy works together with [MFA tr
 
 - **Using 'Require one of the selected controls' with 'require authentication strength' control** - After you select authentication strengths grant control and additional controls, all the selected controls must be satisfied in order to gain access to the resource. Using **Require one of the selected controls** isn't applicable, and will default to requiring all the controls in the policy.
 
-- **Authentication loop** -  When the user is required to use Microsoft Authenticator (Phone Sign-in) but the user is not registered for this method, they will be given instructions on how to set up the Microsoft Authenticator, that does not include how to enable Passwordless sign-in. As a result, the user can get into an authentication loop. To avoid this issue, make sure the user is registered for the method before the Conditional Access policy is enforced. Phone Sign-in can be registered using the steps outlined here: [Add your work or school account to the Microsoft Authenticator app ("Sign in with your credentials")](https://support.microsoft.com/en-us/account-billing/add-your-work-or-school-account-to-the-microsoft-authenticator-app-43a73ab5-b4e8-446d-9e54-2a4cb8e4e93c)
-
 
 ## Limitations
 
diff --git a/articles/active-directory/authentication/howto-authentication-use-email-signin.md b/articles/active-directory/authentication/howto-authentication-use-email-signin.md
@@ -125,6 +125,9 @@ One of the user attributes that's automatically synchronized by Azure AD Connect
 
 Email as an alternate login ID applies to [Azure AD B2B collaboration](../external-identities/what-is-b2b.md) under a "bring your own sign-in identifiers" model. When email as an alternate login ID is enabled in the home tenant, Azure AD users can perform guest sign in with non-UPN email on the resource tenant endpoint. No action is required from the resource tenant to enable this functionality.
 
+> [!NOTE]
+> When an alternate login ID is used on a resource tenant endpoint that does not have the functionality enabled, the sign-in process will work seamlessly, but SSO will be interrupted.  
+
 ## Enable user sign-in with an email address
 
 > [!NOTE]
diff --git a/articles/active-directory/authentication/howto-password-ban-bad-on-premises-deploy.md b/articles/active-directory/authentication/howto-password-ban-bad-on-premises-deploy.md
@@ -249,7 +249,7 @@ To install the Azure AD Password Protection proxy service, complete the followin
 
     Registration of the Azure AD Password Protection proxy service is necessary only once in the lifetime of the service. After that, the Azure AD Password Protection proxy service will automatically perform any other necessary maintenance.
 
-1. To make sure that the changes have taken effect, run `Test-AzureADPasswordProtectionDCAgentHealth -TestAll`. For help resolving errors, see [Troubleshoot: On-premises Azure AD Password Protection](howto-password-ban-bad-on-premises-troubleshoot.md).
+1. To make sure that the changes have taken effect, run `Test-AzureADPasswordProtectionProxyHealth -TestAll`. For help resolving errors, see [Troubleshoot: On-premises Azure AD Password Protection](howto-password-ban-bad-on-premises-troubleshoot.md).
 
 1. Now register the on-premises Active Directory forest with the necessary credentials to communicate with Azure by using the `Register-AzureADPasswordProtectionForest` PowerShell cmdlet.
 
@@ -304,7 +304,7 @@ To install the Azure AD Password Protection proxy service, complete the followin
     
     For `Register-AzureADPasswordProtectionForest` to succeed, at least one DC running Windows Server 2012 or later must be available in the Azure AD Password Protection proxy server's domain. The Azure AD Password Protection DC agent software doesn't have to be installed on any domain controllers prior to this step.
 
-1. To make sure that the changes have taken effect, run `Test-AzureADPasswordProtectionDCAgentHealth -TestAll`. For help resolving errors, see [Troubleshoot: On-premises Azure AD Password Protection](howto-password-ban-bad-on-premises-troubleshoot.md).
+1. To make sure that the changes have taken effect, run `Test-AzureADPasswordProtectionProxyHealth -TestAll`. For help resolving errors, see [Troubleshoot: On-premises Azure AD Password Protection](howto-password-ban-bad-on-premises-troubleshoot.md).
 
 ### Configure the proxy service to communicate through an HTTP proxy
 
diff --git a/articles/aks/configure-kube-proxy.md b/articles/aks/configure-kube-proxy.md
@@ -69,14 +69,14 @@ The full `kube-proxy` configuration structure can be found in the [AKS Cluster S
 - `mode` - can be set to `IPTABLES` or `IPVS`. Defaults to `IPTABLES`.
 - `ipvsConfig` - if `mode` is `IPVS`, this object contains IPVS-specific configuration properties.
   - `scheduler` - which connection scheduler to utilize. Supported values:
-    - `LeastConnections` - sends connections to the backend pod with the fewest connections
+    - `LeastConnection` - sends connections to the backend pod with the fewest connections
     - `RoundRobin` - distributes connections evenly between backend pods
   - `tcpFinTimeoutSeconds` - the value used for timeout after a FIN has been received in a TCP session
   - `tcpTimeoutSeconds` - the value used for timeout length for idle TCP sessions
   - `udpTimeoutSeconds` - the value used for timeout length for idle UDP sessions
 
 > [!NOTE]
-> IPVS load balancing operates in each node independently and is still only aware of connections flowing through the local node. This means that while `LeastConnections` results in more even load under higher number of connections, when low numbers of connections (# connects < 2 * node count) occur traffic may still be relatively unbalanced.
+> IPVS load balancing operates in each node independently and is still only aware of connections flowing through the local node. This means that while `LeastConnection` results in more even load under higher number of connections, when low numbers of connections (# connects < 2 * node count) occur traffic may still be relatively unbalanced.
 
 ## Utilize `kube-proxy` configuration in a new or existing AKS cluster using Azure CLI
 
diff --git a/articles/azure-functions/durable/durable-functions-overview.md b/articles/azure-functions/durable/durable-functions-overview.md
@@ -518,7 +518,7 @@ public static async Task Run(
         if (jobStatus == "Completed")
         {
             // Perform an action when a condition is met.
-            await context.CallActivityAsync("SendAlert", machineId);
+            await context.CallActivityAsync("SendAlert", jobId);
             break;
         }
 
@@ -547,7 +547,7 @@ public static async Task Run(
         if (jobStatus == "Completed")
         {
             // Perform an action when a condition is met.
-            await context.CallActivityAsync("SendAlert", machineId);
+            await context.CallActivityAsync("SendAlert", jobId);
             break;
         }
 
@@ -575,7 +575,7 @@ module.exports = df.orchestrator(function*(context) {
         const jobStatus = yield context.df.callActivity("GetJobStatus", jobId);
         if (jobStatus === "Completed") {
             // Perform an action when a condition is met.
-            yield context.df.callActivity("SendAlert", machineId);
+            yield context.df.callActivity("SendAlert", jobId);
             break;
         }
 
diff --git a/articles/azure-functions/functions-machine-learning-tensorflow.md b/articles/azure-functions/functions-machine-learning-tensorflow.md
@@ -59,13 +59,7 @@ Navigate to the *start* folder and run the following commands to create and acti
 
 ```bash
 cd start
-```
-
-```bash
 python -m venv .venv
-```
-
-```bash
 source .venv/bin/activate
 ```
 
@@ -79,27 +73,15 @@ sudo apt-get install python3-venv
 
 ```powershell
 cd start
-```
-
-```powershell
 py -3.7 -m venv .venv
-```
-
-```powershell
 .venv\scripts\activate
 ```
 
 # [Cmd](#tab/cmd)
 
 ```cmd
 cd start
-```
-
-```cmd
 py -3.7 -m venv .venv
-```
-
-```cmd
 .venv\scripts\activate
 ```
 
diff --git a/articles/azure-functions/ip-addresses.md b/articles/azure-functions/ip-addresses.md
@@ -49,6 +49,9 @@ nslookup <APP_NAME>.azurewebsites.net
 
 Each function app has a set of available outbound IP addresses. Any outbound connection from a function, such as to a back-end database, uses one of the available outbound IP addresses as the origin IP address. You can't know beforehand which IP address a given connection will use. For this reason, your back-end service must open its firewall to all of the function app's outbound IP addresses.
 
+> [!TIP]
+> For some platform-level features such as [Key Vault references](../app-service/app-service-key-vault-references.md), the origin IP might not be one of the outbound IPs, and you should not configure the target resource to rely on these specific addresses. It is recommended that the app instead use a virtual network integration, as the platform will route traffic to the target resource through that network.
+
 To find the outbound IP addresses available to a function app:
 
 # [Azure portal](#tab/portal)
diff --git a/articles/storage/common/storage-solution-large-dataset-low-network.md b/articles/storage/common/storage-solution-large-dataset-low-network.md
@@ -44,7 +44,7 @@ The following table summarizes the differences in key capabilities.
 |                                     |    Data Box Disk      |    Data Box                                      |    Data Box Heavy              |    Import/Export                       |
 |-------------------------------------|---------------------------------|--------------------------------------------------|------------------------------------------|----------------------------------------|
 |    **Data size**                    |    Up to 35 TBs                 |    Up to 80 TBs per device                       |    Up to 800 TB per device               |    Variable                            |
-|    **Data type**                    |    Azure Blobs                  |    Azure Blobs<br>Azure Files                    |    Azure Blobs<br>Azure Files            |    Azure Blobs<br>Azure Files          |
+|    **Data type**                    |    Azure Blobs<br>Azure Files*  |    Azure Blobs<br>Azure Files                    |    Azure Blobs<br>Azure Files            |    Azure Blobs<br>Azure Files          |
 |    **Form factor**                  |    5 SSDs per order             |    1 X 50-lbs. desktop-sized device per order    |    1 X ~500-lbs. large device per order    |    Up to 10 HDDs/SSDs per order        |
 |    **Initial setup time**           |    Low <br>(15 mins)            |    Low to moderate <br> (<30 mins)               |    Moderate<br>(1-2 hours)               |    Moderate to difficult<br>(variable) |
 |    **Send data to Azure**           |    Yes                          |    Yes                                           |    Yes                                   |    Yes                                 |
@@ -57,6 +57,8 @@ The following table summarizes the differences in key capabilities.
 | **Use when data moves**     |Within a commerce boundary|Within a commerce boundary|Within a commerce boundary|Across geographic boundaries, e.g. US to EU|
 |    **Pricing**                      |    [Pricing](https://azure.microsoft.com/pricing/details/databox/disk/)                    |   [Pricing](https://azure.microsoft.com/pricing/details/storage/databox/)                                      |  [Pricing](https://azure.microsoft.com/pricing/details/storage/databox/heavy/)                               |   [Pricing](https://azure.microsoft.com/pricing/details/storage-import-export/)                            |
 
+*\* Data Box Disk does not support Large File Shares and does not preserve file metadata.*
+
 ## Next steps
 
 - Understand how to
diff --git a/articles/storage/common/storage-solution-large-dataset-moderate-high-network.md b/articles/storage/common/storage-solution-large-dataset-moderate-high-network.md
@@ -60,7 +60,7 @@ If using offline data transfer, use the following table to understand the differ
 |                                     |    Data Box Disk      |    Data Box                                      |    Data Box Heavy            |    Import/Export                       |
 |-------------------------------------|---------------------------------|--------------------------------------------------|------------------------------------------|----------------------------------------|
 |    **Data size**                    |    Up to 35 TBs                 |    Up to 80 TBs per device                       |    Up to 800 TB per device               |    Variable                            |
-|    **Data type**                    |    Azure Blobs                  |    Azure Blobs<br>Azure Files                    |    Azure Blobs<br>Azure Files            |    Azure Blobs<br>Azure Files          |
+|    **Data type**                    |    Azure Blobs<br>Azure Files*   |    Azure Blobs<br>Azure Files                    |    Azure Blobs<br>Azure Files            |    Azure Blobs<br>Azure Files          |
 |    **Form factor**                  |    5 SSDs per order             |    1 X 50-lbs. desktop-sized device per order    |    1 X ~500-lbs. large device per order    |    Up to 10 HDDs/SSDs per order        |
 |    **Initial setup time**               |    Low <br>(15 mins)            |    Low to moderate <br> (<30 mins)               |    Moderate<br>(1-2 hours)               |    Moderate to difficult<br>(variable) |
 |    **Send data to Azure**           |    Yes                          |    Yes                                           |    Yes                                   |    Yes                                 |
@@ -73,6 +73,8 @@ If using offline data transfer, use the following table to understand the differ
 | **Use when data moves**     |Within a commerce boundary|Within a commerce boundary|Within a commerce boundary|Across geographic boundaries, e.g. US to EU|
 |    **Pricing**                          |    [Pricing](https://azure.microsoft.com/pricing/details/databox/disk/)                    |   [Pricing](https://azure.microsoft.com/pricing/details/storage/databox/)                                      |  [Pricing](https://azure.microsoft.com/pricing/details/storage/databox/heavy/)                               |   [Pricing](https://azure.microsoft.com/pricing/details/storage-import-export/)                            |
 
+*\* Data Box Disk does not support Large File Shares and does not preserve file metadata*
+
 If using online data transfer, use the table in the following section for high network bandwidth.
 
 ### High network bandwidth

Original file line number	Diff line number	Diff line change
`@@ -518,7 +518,7 @@ public static async Task Run(`
`518`	`518`	`if (jobStatus == "Completed")`
`519`	`519`	`{`
`520`	`520`	`// Perform an action when a condition is met.`
`521`		`- await context.CallActivityAsync("SendAlert", machineId);`
	`521`	`+ await context.CallActivityAsync("SendAlert", jobId);`
`522`	`522`	`break;`
`523`	`523`	`}`
`524`	`524`
`@@ -547,7 +547,7 @@ public static async Task Run(`
`547`	`547`	`if (jobStatus == "Completed")`
`548`	`548`	`{`
`549`	`549`	`// Perform an action when a condition is met.`
`550`		`- await context.CallActivityAsync("SendAlert", machineId);`
	`550`	`+ await context.CallActivityAsync("SendAlert", jobId);`
`551`	`551`	`break;`
`552`	`552`	`}`
`553`	`553`
`@@ -575,7 +575,7 @@ module.exports = df.orchestrator(function*(context) {`
`575`	`575`	`const jobStatus = yield context.df.callActivity("GetJobStatus", jobId);`
`576`	`576`	`if (jobStatus === "Completed") {`
`577`	`577`	`// Perform an action when a condition is met.`
`578`		`- yield context.df.callActivity("SendAlert", machineId);`
	`578`	`+ yield context.df.callActivity("SendAlert", jobId);`
`579`	`579`	`break;`
`580`	`580`	`}`
`581`	`581`