Merge pull request #210298 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/app-service/configure-connect-to-azure-storage.md

@@ -106,7 +106,6 @@ The following features are supported for Linux containers:
 - Mapping `/mounts`, `mounts/foo/bar`, `/`, and `/mounts/foo.bar/` to custom-mounted storage is not supported (you can only use /mounts/pathname for mounting custom storage to your web app.)
 - Storage mounts cannot be used together with clone settings option during [deployment slot](deploy-staging-slots.md) creation.
 - Storage mounts are not backed up when you [back up your app](manage-backup.md). Be sure to follow best practices to back up the Azure Storage accounts. 
-- Only Azure Files [SMB](../storage/files/files-smb-protocol.md) are supported.  Azure Files [NFS](../storage/files/files-nfs-protocol.md) is not currently supported for Linux App Services.
 
 ::: zone-end
 
@@ -118,7 +117,7 @@ The following features are supported for Linux containers:
 - FTP/FTPS access to mounted storage not supported (use [Azure Storage Explorer](https://azure.microsoft.com/features/storage-explorer/)).
 - Mapping `[C-Z]:\`, `[C-Z]:\home`, `/`, and `/home` to custom-mounted storage is not supported.
 - Storage mounts cannot be used together with clone settings option during [deployment slot](deploy-staging-slots.md) creation.
-- Storage mounts are not backed up when you [back up your app](manage-backup.md). Be sure to follow best practices to back up the Azure Storage accounts. 
+- Storage mounts are not backed up when you [back up your app](manage-backup.md). Be sure to follow best practices to back up the Azure Storage accounts.
 
 > [!NOTE]
 > Ensure ports 80 and 445 are open when using Azure Files with VNET integration.
@@ -134,6 +133,7 @@ The following features are supported for Linux containers:
 - Don't map the custom storage mount to `/tmp` or its subdirectories as this may cause timeout during app startup.
 - Storage mounts cannot be used together with clone settings option during [deployment slot](deploy-staging-slots.md) creation.
 - Storage mounts are not backed up when you [back up your app](manage-backup.md). Be sure to follow best practices to back up the Azure Storage accounts. 
+- Only Azure Files [SMB](../storage/files/files-smb-protocol.md) are supported.  Azure Files [NFS](../storage/files/files-nfs-protocol.md) is not currently supported for Linux App Services.
 
 > [!NOTE]
 > When VNET integration is used, ensure the following ports are open:
@@ -343,4 +343,4 @@ To validate that the Azure Storage is mounted successfully for the app:
 - [Configure a custom container](configure-custom-container.md?pivots=platform-linux).
 - [Video: How to mount Azure Storage as a local share](https://www.youtube.com/watch?v=OJkvpWYr57Y).
 
-::: zone-end
+::: zone-end

articles/event-grid/event-filtering.md

@@ -353,7 +353,7 @@ FOR_EACH filter IN (a, b, c)
 See [Limitations](#limitations) section for current limitation of this operator.
 
 ## StringBeginsWith
-The **StringBeginsWith** operator evaluates to true if the **key** value **begins with** any of the specified **filter** values. In the following example, it checks whether the value of the `key1` attribute in the `data` section begins with `event` or `grid`. For example, `event hubs` begins with `event`.  
+The **StringBeginsWith** operator evaluates to true if the **key** value **begins with** any of the specified **filter** values. In the following example, it checks whether the value of the `key1` attribute in the `data` section begins with `event` or `message`. For example, `event hubs` begins with `event`.  
 
 ```json
 "advancedFilters": [{

articles/event-grid/system-topics.md

@@ -26,7 +26,9 @@ In the past, a system topic was implicit and wasn't exposed for simplicity. Syst
 - Set up alerts on publish and delivery failures 
 
 > [!NOTE]
-> Azure Event Grid creates a system topic resource in the same Azure subscription that has the event source. For example, if you create a system topic for a storage account *ContosoStorage* in an Azure subscription *ContosoSubscription*, Event Grid creates the system topic in the *ContosoSubscription*. It's not possible to create a system topic in an Azure subscription that's different from the event source's Azure subscription.
+> - Only one Azure Event Grid system topic is allowed per source (like Subscription, Resource Group, etc.).
+> - Resource Group is required for Subscription level Event Grid system topic and cannot be changed until deleted/moved to another subscription.  
+> - Azure Event Grid creates a system topic resource in the same Azure subscription that has the event source. For example, if you create a system topic for a storage account *ContosoStorage* in an Azure subscription *ContosoSubscription*, Event Grid creates the system topic in the *ContosoSubscription*. It's not possible to create a system topic in an Azure subscription that's different from the event source's Azure subscription.
 
 ## Lifecycle of system topics
 You can create a system topic in two ways: 

articles/iot-hub/iot-hub-tls-support.md

@@ -104,7 +104,7 @@ For IoT Hubs not configured for TLS 1.2 enforcement, TLS 1.2 still works with th
 * `TLS_ECDHE_RSA_WITH_AES_128_CBC_SHA`
 * `TLS_RSA_WITH_AES_256_CBC_SHA`
 * `TLS_RSA_WITH_AES_128_CBC_SHA`
-* `TLS_RSA_WITH_3DES_EDE_CBC_SHA`
+* `TLS_RSA_WITH_3DES_EDE_CBC_SHA` **(This cipher will be deprecated on 10/01/2022 and will no longer be used for TLS handshakes)**
 
 A client can suggest a list of higher cipher suites to use during `ClientHello`. However, some of them might not be supported by IoT Hub (for example, `ECDHE-ECDSA-AES256-GCM-SHA384`). In this case, IoT Hub will try to follow the preference of the client, but eventually negotiate down the cipher suite with `ServerHello`.
 

articles/machine-learning/v1/how-to-cicd-data-ingestion.md

@@ -106,7 +106,7 @@ steps:
     artifact: di-notebooks
 ```
 
-The pipeline uses [flake8](https://pypi.org/project/flake8/) to do the Python code linting. It runs the unit tests defined in the source code and publishes the linting and test results so they're available in the Azure Pipeline execution screen.
+The pipeline uses [flake8](https://pypi.org/project/flake8/) to do the Python code linting. It runs the unit tests defined in the source code and publishes the linting and test results so they're available in the Azure Pipelines execution screen.
 
 If the linting and unit testing is successful, the pipeline will copy the source code to the artifact repository to be used by the subsequent deployment steps.
 
@@ -209,7 +209,7 @@ The values in the JSON file are default values configured in the pipeline defini
 
 The Continuous Delivery process takes the artifacts and deploys them to the first target environment. It makes sure that the solution works by running tests. If successful, it continues to the next environment. 
 
-The CD Azure Pipeline consists of multiple stages representing the environments. Each stage contains [deployments](/azure/devops/pipelines/process/deployment-jobs) and [jobs](/azure/devops/pipelines/process/phases?tabs=yaml) that perform the following steps:
+The CD Azure Pipelines consists of multiple stages representing the environments. Each stage contains [deployments](/azure/devops/pipelines/process/deployment-jobs) and [jobs](/azure/devops/pipelines/process/phases?tabs=yaml) that perform the following steps:
 
 * Deploy a Python Notebook to Azure Databricks workspace
 * Deploy an Azure Data Factory pipeline 
@@ -479,4 +479,4 @@ stages:
 
 * [Source Control in Azure Data Factory](/azure/data-factory/source-control)
 * [Continuous integration and delivery in Azure Data Factory](/azure/data-factory/continuous-integration-delivery)
-* [DevOps for Azure Databricks](https://marketplace.visualstudio.com/items?itemName=riserrad.azdo-databricks)
+* [DevOps for Azure Databricks](https://marketplace.visualstudio.com/items?itemName=riserrad.azdo-databricks)

articles/storage/common/storage-use-azurite.md

@@ -13,7 +13,7 @@ ms.custom: devx-track-csharp
 
 # Use the Azurite emulator for local Azure Storage development
 
-The Azurite open-source emulator provides a free local environment for testing your Azure blob, queue storage, and table storage applications. When you're satisfied with how your application is working locally, switch to using an Azure Storage account in the cloud. The emulator provides cross-platform support on Windows, Linux, and macOS.
+The Azurite open-source emulator provides a free local environment for testing your Azure Blob, Queue Storage, and Table Storage applications. When you're satisfied with how your application is working locally, switch to using an Azure Storage account in the cloud. The emulator provides cross-platform support on Windows, Linux, and macOS.
 
 Azurite is the future storage emulator platform. Azurite supersedes the [Azure Storage Emulator](storage-use-emulator.md). Azurite will continue to be updated to support the latest versions of Azure Storage APIs.
 

articles/stream-analytics/stream-analytics-stream-analytics-query-patterns.md

@@ -109,7 +109,7 @@ For more information, see [**WITH** clause](/stream-analytics-query/with-azure-s
 
 ## Simple pass-through query
 
-A simple pass-through query can be used to copy the input stream data into the output. For example, if a stream of data containing real-time vehicle information needs to be saved in a SQL database for letter analysis, a simple pass-through query will do the job.
+A simple pass-through query can be used to copy the input stream data into the output. For example, if a stream of data containing real-time vehicle information needs to be saved in a SQL database for later analysis, a simple pass-through query will do the job.
 
 **Input**:
 

articles/synapse-analytics/spark/apache-spark-what-is-delta-lake.md

@@ -13,9 +13,9 @@ ms.reviewer: euang
 
 # What is Delta Lake
 
-Azure Synapse Analytics is compatible with Linux Foundation Delta Lake. Delta Lake is an open-source storage layer that brings ACID (atomicity, consistency, isolation, and durability) transactions to Apache Spark and big data workloads.
+Delta Lake is an open-source storage layer that brings ACID (atomicity, consistency, isolation, and durability) transactions to Apache Spark and big data workloads.
 
-The current version of Delta Lake included with Azure Synapse has language support for Scala, PySpark, and .NET. There are links at the bottom of the page to more detailed examples and documentation.
+The current version of Delta Lake included with Azure Synapse has language support for Scala, PySpark, and .NET and is compatible with Linux Foundation Delta Lake. There are links at the bottom of the page to more detailed examples and documentation.
 
 ## Key features
 

articles/synapse-analytics/sql-data-warehouse/sql-data-warehouse-source-control-integration.md

@@ -22,7 +22,7 @@ This tutorial outlines how to integrate your SQL Server Data Tools (SSDT) databa
 
 ## Set up and connect to Azure DevOps
 
-1. In your Azure DevOps Organization, create a project that will host your SSDT database project via an Azure Repo repository.
+1. In your Azure DevOps Organization, create a project that will host your SSDT database project via an Azure Repos repository.
 
    ![Create Project](./media/sql-data-warehouse-source-control-integration/1-create-project-azure-devops.png "Create Project")
 
@@ -60,28 +60,28 @@ For more information about connecting projects using Visual Studio, see the [Con
 
    ![Commit](./media/sql-data-warehouse-source-control-integration/6.5-commit-push-changes.png "Commit")  
 
-4. Now that you have the changes committed locally in the cloned repository, sync and push your changes to your Azure Repo repository in your Azure DevOps project.
+4. Now that you have the changes committed locally in the cloned repository, sync and push your changes to your Azure Repos repository in your Azure DevOps project.
 
    ![Sync and Push - staging](./media/sql-data-warehouse-source-control-integration/7-commit-push-changes.png "Sync and push - staging")
 
    ![Sync and Push](./media/sql-data-warehouse-source-control-integration/7.5-commit-push-changes.png "Sync and push")  
 
 ## Validation
 
-1. Verify changes have been pushed to your Azure Repo by updating a  table column in your database project from Visual Studio SQL Server Data Tools (SSDT).
+1. Verify changes have been pushed to your Azure Repos by updating a  table column in your database project from Visual Studio SQL Server Data Tools (SSDT).
 
    ![Validate update column](./media/sql-data-warehouse-source-control-integration/8-validation-update-column.png "Validate update column")
 
 2. Commit and push the change from your local repository to your Azure Repo.
 
    ![Push changes](./media/sql-data-warehouse-source-control-integration/9-push-column-change.png "Push changes")
 
-3. Verify the change has been pushed in your Azure Repo repository.
+3. Verify the change has been pushed in your Azure Repos repository.
 
    ![Verify](./media/sql-data-warehouse-source-control-integration/10-verify-column-change-pushed.png "Verify changes")
 
-4. (**Optional**) Use Schema Compare and update the changes to your target dedicated SQL pool using SSDT to ensure the object definitions in your Azure Repo repository and local repository reflect your dedicated SQL pool.
+4. (**Optional**) Use Schema Compare and update the changes to your target dedicated SQL pool using SSDT to ensure the object definitions in your Azure Repos repository and local repository reflect your dedicated SQL pool.
 
 ## Next steps
 
-- [Developing for dedicated SQL pool](sql-data-warehouse-overview-develop.md)
+- [Developing for dedicated SQL pool](sql-data-warehouse-overview-develop.md)

articles/synapse-analytics/sql/query-delta-lake-format.md

@@ -1,6 +1,6 @@
 ---
 title: Query Delta Lake format using serverless SQL pool
-description: In this article, you'll learn how to query files stored in Apache Delta Lake format using serverless SQL pool.
+description: In this article, you'll learn how to query files stored in Delta Lake format using serverless SQL pool.
 services: synapse analytics
 ms.service: synapse-analytics
 ms.topic: how-to
@@ -14,7 +14,7 @@ ms.custom: ignite-fall-2021
 
 # Query Delta Lake files using serverless SQL pool in Azure Synapse Analytics
 
-In this article, you'll learn how to write a query using serverless Synapse SQL pool to read Apache Delta Lake files.
+In this article, you'll learn how to write a query using serverless Synapse SQL pool to read Delta Lake files.
 Delta Lake is an open-source storage layer that brings ACID (atomicity, consistency, isolation, and durability) transactions to Apache Spark and big data workloads.
 
 The serverless SQL pool in Synapse workspace enables you to read the data stored in Delta Lake format, and serve it to reporting tools.