Merge pull request #57759 from MicrosoftDocs/repo_sync_working_branch

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

Author: huypub

articles/active-directory-b2c/saml-technical-profile.md

@@ -17,7 +17,7 @@ ms.component: B2C
 
 [!INCLUDE [active-directory-b2c-advanced-audience-warning](../../includes/active-directory-b2c-advanced-audience-warning.md)]
 
-Azure Active Directory (Azure AD) B2C provides support for the SAML 2.0 identity provider. This article describes the specifics of a technical profile for interacting with a claims provider that supports this standardized protocol. With SAML technical profile you can federate with a SAML based identity provider, such as AD-FS and Salesforce, allowing you users to sign-in with their existing social or enterprise identities.
+Azure Active Directory (Azure AD) B2C provides support for the SAML 2.0 identity provider. This article describes the specifics of a technical profile for interacting with a claims provider that supports this standardized protocol. With SAML technical profile you can federate with a SAML based identity provider, such as AD-FS and Salesforce, allowing your users to sign-in with their existing social or enterprise identities.
 
 ## Metadata exchange
 

articles/application-insights/app-insights-ip-addresses.md

@@ -34,7 +34,7 @@ You need to open some outgoing ports in your server's firewall to allow the Appl
 
 | Purpose | URL | IP | Ports |
 | --- | --- | --- | --- |
-| Telemetry |dc.services.visualstudio.com<br/>dc.applicationinsights.microsoft.com |40.114.241.141<br/>104.45.136.42<br/>40.84.189.107<br/>168.63.242.221<br/>52.167.221.184<br/>52.169.64.244<br/>40.85.218.175<br/>104.211.92.54<br/>52.175.198.74<br/>51.140.6.23 | 443 |
+| Telemetry |dc.services.visualstudio.com<br/>dc.applicationinsights.microsoft.com |40.114.241.141<br/>104.45.136.42<br/>40.84.189.107<br/>168.63.242.221<br/>52.167.221.184<br/>52.169.64.244<br/>40.85.218.175<br/>104.211.92.54<br/>52.175.198.74<br/>51.140.6.23<br/>40.71.12.231 | 443 |
 | Live Metrics Stream |rt.services.visualstudio.com<br/>rt.applicationinsights.microsoft.com |23.96.28.38<br/>13.92.40.198 |443 |
 
 ## Status Monitor

articles/azure-databricks/databricks-extract-load-sql-data-warehouse.md

@@ -13,15 +13,15 @@ ms.date: 07/26/2018
 ---
 # Tutorial: Extract, transform, and load data using Azure Databricks
 
-In this tutorial, you perform an ETL (extract, transform, and load data) operation using Azure Databricks. You extract data from Azure Data Lake Store into Azure Databricks, run transformations on the data in Azure Databricks, and then load the transformed data into Azure SQL Data Warehouse. 
+In this tutorial, you perform an ETL (extract, transform, and load data) operation using Azure Databricks. You extract data from Azure Data Lake Store into Azure Databricks, run transformations on the data in Azure Databricks, and then load the transformed data into Azure SQL Data Warehouse.
 
 The steps in this tutorial use the SQL Data Warehouse connector for Azure Databricks to transfer data to Azure Databricks. This connector, in turn, uses Azure Blob Storage as temporary storage for the data being transferred between an Azure Databricks cluster and Azure SQL Data Warehouse.
 
 The following illustration shows the application flow:
 
 ![Azure Databricks with Data Lake Store and SQL Data Warehouse](./media/databricks-extract-load-sql-data-warehouse/databricks-extract-transform-load-sql-datawarehouse.png "Azure Databricks with Data Lake Store and SQL Data Warehouse")
 
-This tutorial covers the following tasks: 
+This tutorial covers the following tasks:
 
 > [!div class="checklist"]
 > * Create an Azure Databricks workspace
@@ -58,7 +58,7 @@ In this section, you create an Azure Databricks workspace using the Azure portal
 
     ![Create an Azure Databricks workspace](./media/databricks-extract-load-sql-data-warehouse/create-databricks-workspace.png "Create an Azure Databricks workspace")
 
-    Provide the following values: 
+    Provide the following values:
 
     |Property  |Description  |
     |---------|---------|
@@ -89,14 +89,14 @@ In this section, you create an Azure Databricks workspace using the Azure portal
     Accept all other defaults other than the following values:
 
     * Enter a name for the cluster.
-    * For this article, create a cluster with **4.0** runtime. 
+    * For this article, create a cluster with **4.0** runtime.
     * Make sure you select the **Terminate after \_\_ minutes of inactivity** checkbox. Provide a duration (in minutes) to terminate the cluster, if the cluster is not being used.
 
     Select **Create cluster**. Once the cluster is running, you can attach notebooks to the cluster and run Spark jobs.
 
 ## Create an Azure Data Lake Store account
 
-In this section, you create an Azure Data Lake Store account and associate an Azure Active Directory service principal with it. Later in this tutorial, you use this service principal in Azure Databricks to access Azure Data Lake Store. 
+In this section, you create an Azure Data Lake Store account and associate an Azure Active Directory service principal with it. Later in this tutorial, you use this service principal in Azure Databricks to access Azure Data Lake Store.
 
 1. From the [Azure portal](https://portal.azure.com), select **Create a resource** > **Storage** > **Data Lake Store**.
 3. In the **New Data Lake Store** blade, provide the values as shown in the following screenshot:
@@ -183,7 +183,7 @@ When programmatically logging in, you need to pass the tenant ID with your authe
 
 1. Copy the **Directory ID**. This value is your tenant ID.
 
-   ![tenant ID](./media/databricks-extract-load-sql-data-warehouse/copy-directory-id.png) 
+   ![tenant ID](./media/databricks-extract-load-sql-data-warehouse/copy-directory-id.png)
 
 ## Upload data to Data Lake Store
 
@@ -300,7 +300,7 @@ You have now extracted the data from Azure Data Lake Store into Azure Databricks
 
 ## Transform data in Azure Databricks
 
-The raw sample data **small_radio_json.json** captures the audience for a radio station and has a variety of columns. In this section, you transform the data to only retrieve specific columns in from the dataset. 
+The raw sample data **small_radio_json.json** captures the audience for a radio station and has a variety of columns. In this section, you transform the data to only retrieve specific columns in from the dataset.
 
 1. Start by retrieving only the columns *firstName*, *lastName*, *gender*, *location*, and *level* from the dataframe you already created.
 
@@ -334,7 +334,7 @@ The raw sample data **small_radio_json.json** captures the audience for a radio
         |  Margaux|     Smith|     F|Atlanta-Sandy Spr...| free|
         +---------+----------+------+--------------------+-----+
 
-2.  You can further transform this data to rename the column **level** to **subscription_type**.
+2. You can further transform this data to rename the column **level** to **subscription_type**.
 
         val renamedColumnsDf = specificColumnsDf.withColumnRenamed("level", "subscription_type")
         renamedColumnsDf.show()
@@ -376,7 +376,7 @@ As mentioned earlier, the SQL date warehouse connector uses Azure Blob Storage a
 
         val blobStorage = "<STORAGE ACCOUNT NAME>.blob.core.windows.net"
         val blobContainer = "<CONTAINER NAME>"
-        val blobAccessKey =  "<ACCESS KEY>"
+        val blobAccessKey = "<ACCESS KEY>"
 
 2. Specify a temporary folder that will be used while moving data between Azure Databricks and Azure SQL Data Warehouse.
 
@@ -391,23 +391,23 @@ As mentioned earlier, the SQL date warehouse connector uses Azure Blob Storage a
 
         //SQL Data Warehouse related settings
         val dwDatabase = "<DATABASE NAME>"
-        val dwServer = "<DATABASE SERVER NAME>" 
+        val dwServer = "<DATABASE SERVER NAME>"
         val dwUser = "<USER NAME>"
         val dwPass = "<PASSWORD>"
-        val dwJdbcPort =  "1433"
+        val dwJdbcPort = "1433"
         val dwJdbcExtraOptions = "encrypt=true;trustServerCertificate=true;hostNameInCertificate=*.database.windows.net;loginTimeout=30;"
         val sqlDwUrl = "jdbc:sqlserver://" + dwServer + ".database.windows.net:" + dwJdbcPort + ";database=" + dwDatabase + ";user=" + dwUser+";password=" + dwPass + ";$dwJdbcExtraOptions"
         val sqlDwUrlSmall = "jdbc:sqlserver://" + dwServer + ".database.windows.net:" + dwJdbcPort + ";database=" + dwDatabase + ";user=" + dwUser+";password=" + dwPass
 
-5. Run the following snippet to load the transformed dataframe, **renamedColumnsDf**, as a table in SQL data warehouse. This snippet creates a table called **SampleTable** in the SQL database. Please note that Azure SQL DW requires a master key.  You can create a master key by executing "CREATE MASTER KEY;" command in SQL Server Management Studio.
+5. Run the following snippet to load the transformed dataframe, **renamedColumnsDf**, as a table in SQL data warehouse. This snippet creates a table called **SampleTable** in the SQL database. Please note that Azure SQL DW requires a master key. You can create a master key by executing "CREATE MASTER KEY;" command in SQL Server Management Studio.
 
         spark.conf.set(
           "spark.sql.parquet.writeLegacyFormat",
           "true")
         
         renamedColumnsDf.write
             .format("com.databricks.spark.sqldw")
-            .option("url", sqlDwUrlSmall) 
+            .option("url", sqlDwUrlSmall)
             .option("dbtable", "SampleTable")
             .option( "forward_spark_azure_storage_credentials","True")
             .option("tempdir", tempDir)
@@ -428,9 +428,9 @@ After you have finished running the tutorial, you can terminate the cluster. To
 
 ![Stop a Databricks cluster](./media/databricks-extract-load-sql-data-warehouse/terminate-databricks-cluster.png "Stop a Databricks cluster")
 
-If you do not manually terminate the cluster it will automatically stop, provided you selected the **Terminate after __ minutes of inactivity** checkbox while creating the cluster. In such a case, the cluster automatically stops if it has been inactive for the specified time.
+If you do not manually terminate the cluster it will automatically stop, provided you selected the **Terminate after \_\_ minutes of inactivity** checkbox while creating the cluster. In such a case, the cluster automatically stops if it has been inactive for the specified time.
 
-## Next steps 
+## Next steps
 In this tutorial, you learned how to:
 
 > [!div class="checklist"]

articles/azure-stack/asdk/asdk-prepare-host.md

@@ -49,7 +49,7 @@ Before you can install the ASDK on the host computer, the ASDK host computer env
 
 6. On the **Optional settings** page, provide the local administrator account information for the development kit host computer and then click **Next**. You can also provide values for the following optional settings:
   - **Computername**: This option sets the name for the development kit host. The name must comply with FQDN requirements and must be 15 characters or less in length. The default is a random computer name generated by Windows.
-  - **Static IP configuration**: Sets your deployment to use a static IP address. Otherwise, when the installer reboots into the cloudbuilder.vhx, the network interfaces are configured with DHCP.
+  - **Static IP configuration**: Sets your deployment to use a static IP address. Otherwise, when the installer reboots into the cloudbuilder.vhdx, the network interfaces are configured with DHCP.
 
     ![](media/asdk-prepare-host/3.PNG)
 

articles/azure-stack/user/azure-stack-solution-machine-learning.md

@@ -988,7 +988,7 @@ The Docker engine must be running locally to complete the following steps to ope
 1.  Make sure the Azure resource provider **Microsoft.ContainerRegistry** is registered in the subscription. Register this resource provider before creating an environment in step 3. Check to see if it's already registered by using the following command:
 
     ```CLI
-        az provider list --query "\[\].{Provider:namespace, Status:registrationState}" --out table
+        az provider list --query "[].{Provider:namespace, Status:registrationState}" --out table
     ```
 
     View this output:
@@ -1267,10 +1267,8 @@ From within the WSL Environment, run the following commands to install kubectl i
 
 ```Bash  
     apt-get update && apt-get install -y apt-transport-https
-    curl -s https://packages.cloud.google.com/apt/doc/apt-key.gpg | apt-key add -
-    cat <<EOF >/etc/apt/sources.list.d/kubernetes.list
-    deb http://apt.kubernetes.io/ kubernetes-xenial main
-    EOF
+    curl -s https://packages.cloud.google.com/apt/doc/apt-key.gpg | apt-key add
+    sudo apt-add-repository "deb http://apt.kubernetes.io/ kubernetes-xenial main"
     apt-get update
     apt-get install -y kubectl
 ```

articles/batch-ai/use-azure-storage.md

@@ -94,7 +94,7 @@ If your training script requires knowledge of a path, you should pass it as a co
 
 ### Abbreviate input paths
 
-To abbreviate input paths as an environment variable, use the `inputDirectories` property of your `job.json` file (or `models.JobCreateParamters.input_directories` if using the Batch AI SDK). The schema of `inputDirectories` is:
+To abbreviate input paths as an environment variable, use the `inputDirectories` property of your `job.json` file (or `models.JobCreateParameters.input_directories` if using the Batch AI SDK). The schema of `inputDirectories` is:
 
 ```json
 {
@@ -111,7 +111,7 @@ For more information, see [here](https://github.com/Azure/BatchAI/blob/master/do
 
 ### Abbreviate output paths
 
-To abbreviate output paths as an environment variable, use the `outputDirectories` property of your `job.json` file (or `models.JobCreateParamters.output_directories` if using the Batch AI SDK). Using this method can simplify the paths for output files. The schema of `outputDirectories` is:
+To abbreviate output paths as an environment variable, use the `outputDirectories` property of your `job.json` file (or `models.JobCreateParameters.output_directories` if using the Batch AI SDK). Using this method can simplify the paths for output files. The schema of `outputDirectories` is:
 
 ```json
 {

articles/cognitive-services/QnAMaker/Quickstarts/update-kb-java.md

@@ -272,7 +272,7 @@ public class UpdateKB {
      * Sends the request to update the knowledge base.
      * @param kb The ID for the existing knowledge base
      * @param req The data source for the updated knowledge base
-     * @return Reponse Returns the response from a PATCH request
+     * @return Response Returns the response from a PATCH request
      */
     public static Response UpdateKB (String kb, Request req) throws Exception {
         URL url = new URL(host + service + method + kb);

articles/cosmos-db/change-feed.md

@@ -378,7 +378,7 @@ That’s it. After these few steps documents will start showing up into the **Do
 Above code is for illustration purpose to show different kind of objects and their interaction. You have to define proper variables and initiate them with correct values. You can get the complete code used in this article from the [GitHub repo](https://github.com/Azure/azure-documentdb-dotnet/tree/master/samples/code-samples/ChangeFeedProcessorV2).
 
 > [!NOTE]
-> You should never have a master key in your code or in config file as shown in above code. Please see [how to use Key-Vault to retrive the keys](https://sarosh.wordpress.com/2017/11/23/cosmos-db-and-key-vault/).
+> You should never have a master key in your code or in config file as shown in above code. Please see [how to use Key-Vault to retrieve the keys](https://sarosh.wordpress.com/2017/11/23/cosmos-db-and-key-vault/).
 
 
 ## FAQ

articles/load-balancer/quickstart-create-basic-load-balancer-portal.md

@@ -154,6 +154,7 @@ To allow the Basic load balancer to monitor the status of your app, you use a he
    - **myHealthProbe** for the name of the health probe
    - **HTTP** for the protocol type
    - **80** for the port number
+   - **Healthprobe.aspx** for the URI path. You can either replace this value with any other URI or keep the default path value of **"\\"** to get the default URI.
    - **15** for **Interval**, the number of seconds between probe attempts
    - **2** for **Unhealthy threshold**, the number of consecutive probe failures that must occur before a VM is considered unhealthy
 

articles/load-balancer/quickstart-load-balancer-standard-public-portal.md

@@ -141,6 +141,7 @@ To allow the load balancer to monitor the status of your app, you use a health p
     - *myHealthProbe* - for the name of the health probe.
     - **HTTP** - for the protocol type.
     - *80* - for the port number.
+    - *Healthprobe.aspx* - for the URI path. You can either replace this value with any other URI or keep the default path value of **"\\"** to get the default URI.
     - *15* - for number of **Interval** in seconds between probe attempts.
     - *2* - for number of **Unhealthy threshold** or consecutive probe failures that must occur before a VM is considered unhealthy.
 4. Click **OK**.