Merge pull request #222518 from alexlzx/branch1227

update CICD and VSCode related docs

Author: Stacyrch140

articles/stream-analytics/cicd-overview.md

@@ -2,31 +2,30 @@
 title: Continuous integration and deployment for Azure Stream Analytics 
 description: This article gives an overview of a continuous integration and deployment (CI/CD) pipeline for Azure Stream Analytics.
 services: stream-analytics
-author: su-jie
-ms.author: sujie
+author: alexlzx
+ms.author: zhenxilin
 ms.service: stream-analytics
 ms.topic: how-to
-ms.date: 9/22/2020
+ms.date: 12/27/2022
 ---
 
 # Continuous integration and deployment (CI/CD) for Azure Stream Analytics
 
-You can deploy your Azure Stream Analytics job continuously by using source control integration. Source control integration enables a workflow in which a code update triggers a resource deployment to Azure. This article outlines the basic steps for creating a continuous integration and deployment (CI/CD) pipeline.
+You can build and deploy your Azure Stream Analytics (ASA) job continuously using a source control integration. Source control integration creates a workflow in which updating code would trigger a resource deployment to Azure. This article outlines the basic steps for creating a continuous integration and continuous delivery (CI/CD) pipeline.
 
 If you're new to Azure Stream Analytics, get started with the [Azure Stream Analytics quickstart](stream-analytics-quick-create-portal.md).
 
 ## Create a CI/CD pipeline
 
-Follow the steps in this guide to create a CI/CD pipeline for Stream Analytics.
+Follow the steps to create a CI/CD pipeline for your Stream Analytics project: 
 
-1. Develop an Azure Stream Analytics query.
+1. Create a Stream Analytics project using VSCode.
+   
+    You can either create a new project or export an existing job to your computer using the ASA Tools extension for Visual Studio Code. Check out these two docs for more information:
+    * [Quickstart: Create a Stream Analytics job using VSCode](./quick-create-visual-studio-code.md) 
+    * [Export an existing job](visual-studio-code-explore-jobs.md#export-a-job-to-a-local-project)
 
-   Use Azure Stream Analytics tools for [Visual Studio Code](./quick-create-visual-studio-code.md) or [Visual Studio](stream-analytics-quick-create-vs.md) to [develop and test queries locally](develop-locally.md). You can also [export an existing job](visual-studio-code-explore-jobs.md#export-a-job-to-a-local-project) to a local project.
-
-   > [!NOTE] 
-   > We strongly recommend using [**Stream Analytics tools for Visual Studio Code**](./quick-create-visual-studio-code.md) for best local development experience. There are known feature gaps in Stream Analytics tools for Visual Studio 2019 (version 2.6.3000.0) and it won't be improved going forward.
-
-2. Commit your Azure Stream Analytics projects to your source control system, like a Git repository.
+2. Commit your Stream Analytics project to your source control system, like a Git repository.
 
 3. Use [Azure Stream Analytics CI/CD tools](cicd-tools.md) to build the projects and generate Azure Resource Manager templates for the deployment.
 

articles/stream-analytics/cicd-tools.md

@@ -2,16 +2,16 @@
 title: Automate builds, tests, and deployments of an Azure Stream Analytics job using CI/CD tools
 description: This article describes how to use Azure Stream Analytics CI/CD tools to auto build, test, and deploy an Azure Stream Analytics project.
 services: stream-analytics
-author: su-jie
-ms.author: sujie
+author: alexlzx
+ms.author: zhenxilin
 ms.service: stream-analytics
 ms.topic: how-to
-ms.date: 06/29/2021
+ms.date: 12/27/2022
 ---
 
 # Automate builds, tests, and deployments of an Azure Stream Analytics job using CI/CD tools
 
-You can use the Azure Stream Analytics CI/CD npm package to automatically build, test, and deploy your Azure Stream Analytics Visual Studio Code or Visual Studio projects. The projects can be created using development tools or they can be exported from existing Stream Analytics jobs. This article describes how to use the npm package with any CI/CD system. For deployment with Azure Pipelines, see [Use Azure DevOps to create a CI/CD pipeline for a Stream Analytics job](set-up-cicd-pipeline.md).
+After developing your Stream Analytics project in Visual Studio Code, you can use the Azure Stream Analytics (ASA) CI/CD npm package to automatically build, test, and deploy your Stream Analytics projects. This article shows how to use the npm package with any CI/CD system. For deployment with Azure Pipelines, see [Use Azure DevOps to create a CI/CD pipeline for a Stream Analytics job](set-up-cicd-pipeline.md).
 
 ## Installation
 
@@ -21,7 +21,7 @@ You can [download the package](https://www.npmjs.com/package/azure-streamanalyti
 
 The **asa-streamanalytics-cicd** npm package provides the tools to generate Azure Resource Manager templates of Stream Analytics [Visual Studio Code projects](./quick-create-visual-studio-code.md) or [Visual Studio projects](stream-analytics-quick-create-vs.md). You can also use the npm package on Windows, macOS, and Linux without installing Visual Studio Code or Visual Studio.
 
-Once you have installed the package, use the following command to build your Stream Analytics projects.
+Once you've installed the package, use the following command to build your Stream Analytics projects.
 
 ```powershell
 azure-streamanalytics-cicd build -project <projectFullPath> [-outputPath <outputPath>]
@@ -32,7 +32,7 @@ The *build* command does a keyword syntax check and outputs the Azure Resource M
 | Parameter | Description |
 |---|---|
 | `-project` | The absolute path of the **asaproj.json** file for your Visual Studio Code project or **[Your project name].asaproj** for Visual Studio project. |
-| `-outputPath` | The path of the output folder for Azure Resource Manager Templates. If it is not specified, the templates will be placed in the current directory. |
+| `-outputPath` | The path of the output folder for Azure Resource Manager Templates. If it isn't specified, the templates will be placed in the current directory. |
 
 #### [Visual Studio Code](#tab/visual-studio-code)
 
@@ -60,7 +60,7 @@ When a Stream Analytics project builds successfully, it generates the following
 
 The default parameters in the parameters.json file are from the settings in your Visual Studio Code or Visual Studio project. If you want to deploy to another environment, replace the parameters accordingly.
 
-The default values for all credentials are **null**. You are required to set the values before you deploy to Azure.
+The default values for all credentials are **null**. You're required to set the values before you deploy to Azure.
 
 ```json
 "Input_EntryStream_sharedAccessPolicyKey": {
@@ -81,8 +81,8 @@ azure-streamanalytics-cicd localrun -project <projectFullPath> [-outputPath <out
 | Parameter | Description |
 |---|---|
 | `-project` | The path of the **asaproj.json** file for your Visual Studio Code project or **[Your project name].asaproj** for Visual Studio project. |
-| `-outputPath` | The path of the output folder. If it is not specified, the output result files will be placed in the current directory. |
-| `-customCodeZipFilePath` | The path of the zip file for C# custom code, such as a UDF or deserializer, if they are used. Package the DLLs into a zip file and specify this path. |
+| `-outputPath` | The path of the output folder. If it isn't specified, the output result files will be placed in the current directory. |
+| `-customCodeZipFilePath` | The path of the zip file for C# custom code, such as a UDF or deserializer, if they're used. Package the DLLs into a zip file and specify this path. |
 
 #### [Visual Studio Code](#tab/visual-studio-code)
 
@@ -116,7 +116,7 @@ azure-streamanalytics-cicd addtestcase -project <projectFullPath> [-testConfigPa
 | Parameter | Description |
 |---|---|
 | `-project` | The path of the **asaproj.json** file for your Visual Studio Code project or **[Your project name].asaproj** for Visual Studio project. |
-| `-testConfigPath` | The path of the test configuration file. If it is not specified, the file will be searched in **\test** under the current directory of the **asaproj.json** file, with default file name **testConfig.json**. A new file will be created if not existed. |
+| `-testConfigPath` | The path of the test configuration file. If it isn't specified, the file will be searched in **\test** under the current directory of the **asaproj.json** file, with default file name **testConfig.json**. A new file will be created if not existed. |
 
 > [!NOTE]
 > The `Script` value in the generated **testConfig.json** file is only for providing the context; It's not used in the testing logic. 
@@ -249,9 +249,9 @@ azure-streamanalytics-cicd test -project <projectFullPath> [-testConfigPath <tes
 | Parameter | Description |
 |---|---|
 | `-project` | The path of the **asaproj.json** file for your Visual Studio Code project or **[Your project name].asaproj** for Visual Studio project. |
-| `-testConfigPath` | The path to the test configuration file. If it is not specified, the file will be searched in **\test** under the current directory of the **asaproj.json** file, with default file name **testConfig.json**.
-| `-outputPath` | The path of the test result output folder. If it is not specified, the output result files will be placed in the current directory. |
-| `-customCodeZipFilePath` | The path of the zip file for custom code such as a UDF or deserializer, if they are used. |
+| `-testConfigPath` | The path to the test configuration file. If it isn't specified, the file will be searched in **\test** under the current directory of the **asaproj.json** file, with default file name **testConfig.json**.
+| `-outputPath` | The path of the test result output folder. If it isn't specified, the output result files will be placed in the current directory. |
+| `-customCodeZipFilePath` | The path of the zip file for custom code such as a UDF or deserializer, if they're used. |
 
 As an example, in a PowerShell enabled terminal, if all test assets are located in a `test` subfolder of the project folder. With each test run output stored in a new timestamped subfolder of a `testResults` subfolder:
 

articles/stream-analytics/copy-job.md

@@ -1,34 +1,32 @@
 ---
 title: Copy, back up and move your Azure Stream Analytics jobs between regions
 description: This article describes how to move, copy, and back up an Azure Stream Analytics job.
-author: su-jie
-ms.author: sujie
-
+author: alexlzx
+ms.author: zhenxilin
 ms.service: stream-analytics
 ms.topic: how-to
 ms.custom: subject-moving-resources
-ms.date: 09/11/2019
+ms.date: 12/27/2012
 #Customer intent: As an Azure Stream Analytics job developer or admin, I want export my job so that I can reuse, move between Azure regions, or back up.
 ---
 
 # Copy, back up and move your Azure Stream Analytics jobs between regions
 
-When you want to move, copy or back up your deployed Azure Stream Analytics jobs, you can use the job exporting function in Stream Analytics extension for Visual Studio Code or Visual Studio to achieve. It will help you to export your job's definition to local, then you can backup it there or resubmit it to another region.
+If you want to move, copy or back up your Azure Stream Analytics jobs in Azure, the Azure Stream Analytics extension for Visual Studio Code allows you to export an existing job in Azure cloud to your local computer. All the configurations of your Stream Analytics job will be saved locally and you can resubmit it to another cloud region.
 
 > [!NOTE] 
-> * We strongly recommend using [**Stream Analytics tools for Visual Studio Code**](./quick-create-visual-studio-code.md) for best local development experience. There are known feature gaps in Stream Analytics tools for Visual Studio 2019 (version 2.6.3000.0) and it won't be improved going forward. 
 > * Copying a job to another region does not copy the last output time. Therefore, you cannot use [**When last stopped**](./start-job.md#start-options) option when starting the copied job.
 
 ## Before you begin
 * If you don't have an Azure subscription, create a [free account](https://azure.microsoft.com/free/).
 
 * Sign in to the [Azure portal](https://portal.azure.com/).
 
-* Install [Azure Stream Analytics extension for Visual Studio Code](quick-create-visual-studio-code.md#install-the-azure-stream-analytics-tools-extension) or [Azure Stream Analytics tools for Visual Studio](quick-create-visual-studio-code.md#install-the-azure-stream-analytics-tools-extension).  
+* Install [Azure Stream Analytics extension for Visual Studio Code](quick-create-visual-studio-code.md#install-the-azure-stream-analytics-tools-extension).
 
 ## Visual Studio Code
 
-1. Click the **Azure** icon on the Visual Studio Code Activity Bar and then expand **Stream Analytics** node. Your jobs should appear under your subscriptions.
+1. Select the **Azure** icon on the Visual Studio Code Activity Bar and then expand **Stream Analytics** node. Your jobs should appear under your subscriptions.
 
    ![Open Stream Analytics Explorer](./media/vscode-explore-jobs/open-explorer.png)
 
@@ -42,13 +40,6 @@ When you want to move, copy or back up your deployed Azure Stream Analytics jobs
 
     ![Publish to Azure in Visual Studio Code](./media/quick-create-visual-studio-code/submit-job.png)
 
-## Visual Studio
-
-1. Follow the [export a deployed Azure Stream Analytics job to a project instructions](./stream-analytics-vs-tools.md#export-jobs-to-a-project).
-
-2. Open the \*.asaql file in the Query Editor, select **Submit To Azure** in the script editor and follow the instructions to publish the job to another region or backup using a new name.
-
 ## Next steps
 
-* [Quickstart: Create a Stream Analytics job by using Visual Studio Code](quick-create-visual-studio-code.md)
-* [Quickstart: Create a Stream Analytics job by using Visual Studio](stream-analytics-quick-create-vs.md)
+* [Quickstart: Create a Stream Analytics job by using Visual Studio Code](quick-create-visual-studio-code.md)

articles/stream-analytics/develop-locally.md

@@ -1,16 +1,16 @@
 ---
 title: Develop and debug Azure Stream Analytics jobs locally 
 description: Learn how to develop and test Azure Stream Analytics jobs on your local computer before you run them in Azure portal.
-ms.author: sujie
-author: su-jie
+ms.author: zhenxilin
+author: alexlzx
 ms.topic: conceptual
-ms.date: 03/31/2020
+ms.date: 12/27/2022
 ms.service: stream-analytics
 ---
 
 # Develop and debug Azure Stream Analytics jobs locally
 
-While you're able to create and test Azure Stream Analytics jobs in the Azure portal, many developers prefer a local development experience. Stream Analytics makes it easy to use your favorite code editor and development tools to create and test jobs with live event streams from Azure Event Hub, IoT Hub, and Blob Storage using a fully functioned single node local runtime. You can also submit jobs to Azure directly from your local development environment.
+Apart from creating and developing an Azure Stream Analytics job in the Azure portal, you can set up a Stream Analytics job using a developer tool on your computer. Azure Stream Analytics (ASA) allows you to use your favorite code editor, e.g.,  Visual Studio Code to build and test query locally with live data streams from Azure Event Hubs, IoT Hub, Blob Storage and other Azure resources. The ASA developer tool creates a fully functional node in local runtime to run your Stream Analytics job. You can also submit your local Stream Analytics jobs to Azure cloud and change the job running status. Using the ASA developer tool is a convenient way to build, test and manage your Stream Analytics jobs.
 
 ## Local development environments
 
@@ -20,16 +20,10 @@ The environments in the following table support local development:
 
 |Environment                              |Description    |
 |-----------------------------------------|------------|
-|[Visual Studio Code](visual-studio-code-explore-jobs.md)| The [Azure Stream Analytics Tools extension](https://marketplace.visualstudio.com/items?itemName=ms-bigdatatools.vscode-asa) for Visual Studio Code allows you to author, manage, test your Stream analytics job both locally and in the cloud with rich IntelliSense and native source control. Supports development on Linux, MacOS and Windows. To learn more, see [Create an Azure Stream Analytics job in Visual Studio Code](quick-create-visual-studio-code.md). The extension also supports [Visual Studio Codespaces](https://visualstudio.microsoft.com/services/visual-studio-codespaces/) which is a cloud-hosted dev environment.|
-|[Visual Studio 2019](stream-analytics-tools-for-visual-studio-install.md) |Stream Analytics Tools is part of the Azure development and Data storage and processing workloads in Visual Studio. You can use Visual Studio to write custom C# user-defined functions and deserializers. To learn more, see [Create an Azure Stream Analytics job by using Visual Studio](stream-analytics-quick-create-vs.md).|
+|[Visual Studio Code](visual-studio-code-explore-jobs.md)| The [Azure Stream Analytics tools extension](https://marketplace.visualstudio.com/items?itemName=ms-bigdatatools.vscode-asa) for Visual Studio Code allows you to author, manage, test your Stream Analytics job both locally and in the cloud with rich IntelliSense and native source control. It supports development on Linux, macOS and Windows. To learn more, see [Create an Azure Stream Analytics job in Visual Studio Code](quick-create-visual-studio-code.md). The extension also supports [Visual Studio Codespaces](https://visualstudio.microsoft.com/services/visual-studio-codespaces/), which is a cloud-hosted dev environment.|
 |[Command prompt or terminal](stream-analytics-tools-for-visual-studio-cicd.md)|The Azure Stream Analytics CI/CD NuGet package provides tools for Visual studio project build, local testing on an arbitrary machine. The Azure Stream Analytics CI/CD npm package provides tools for Visual Studio Code project builds (which generates an Azure Resource Manager template) on an arbitrary machine.|
 
-> [!NOTE] 
-> We strongly recommend using [**Stream Analytics tools for Visual Studio Code**](./quick-create-visual-studio-code.md) for best local development experience. There are known feature gaps in Stream Analytics tools for Visual Studio 2019 (version 2.6.3000.0) and it won't be improved going forward.
-
 ## Next steps
 
 * [Test Stream Analytics queries locally with sample data using Visual Studio Code](visual-studio-code-local-run.md)
-* [Test Stream Analytics queries locally against live stream input by using Visual Studio Code](visual-studio-code-local-run-live-input.md)
-* [Test Stream Analytics queries locally with Visual Studio](stream-analytics-vs-tools-local-run.md)
-* [Test live data locally using Azure Stream Analytics tools for Visual Studio](stream-analytics-live-data-local-testing.md)
+* [Test Stream Analytics queries locally against live stream input by using Visual Studio Code](visual-studio-code-local-run-live-input.md)