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用于 Azure 流分析的持续集成和部署 (CI/CD) Continuous integration and deployment (CI/CD) for Azure Stream Analytics

你可以使用源代码管理集成来持续部署 Azure 流分析作业。You can deploy your Azure Stream Analytics job continuously by using source control integration. 源代码管理集成启用了一个工作流,其中的代码更新将触发到 Azure 的资源部署。Source control integration enables a workflow in which a code update triggers a resource deployment to Azure. 本文概述了 (CI/CD) 管道创建持续集成和部署的基本步骤。This article outlines the basic steps for creating a continuous integration and deployment (CI/CD) pipeline.

如果你不熟悉 Azure 流分析,请开始了解 Azure 流分析快速入门If you're new to Azure Stream Analytics, get started with the Azure Stream Analytics quickstart.

创建 CI/CD 管道Create a CI/CD pipeline

遵循本指南中的步骤,为流分析创建 CI/CD 管道。Follow the steps in this guide to create a CI/CD pipeline for Stream Analytics.

  1. 开发 Azure 流分析查询。Develop an Azure Stream Analytics query.

    使用用于 Visual Studio CodeVisual Studio 的 Azure 流分析工具在 本地开发和测试查询Use Azure Stream Analytics tools for Visual Studio Code or Visual Studio to develop and test queries locally. 你还可以将 现有作业导出 到本地项目中。You can also export an existing job to a local project.

  2. 将 Azure 流分析项目提交到源代码管理系统,如 Git 存储库。Commit your Azure Stream Analytics projects to your source control system, like a Git repository.

  3. 使用 Azure 流分析 CI/CD 工具 生成项目并生成用于部署的 Azure 资源管理模板。Use Azure Stream Analytics CI/CD tools to build the projects and generate Azure Resource Management Templates for the deployment.

  4. 为质量回归运行 自动脚本测试Run automated script tests for quality regression.

  5. 作业自动部署到 Azure。Deploy the job to Azure automatically.

自动生成、测试和部署Auto build, test, and deploy

你可以使用命令行和 Azure 流分析 CI/CD 工具 自动生成、测试和部署。You can use the command line and Azure Stream Analytics CI/CD tools to auto build, test, and deploy. 你还可以在 Azure Pipelines中设置 CI/CD 管道。You can also set up a CI/CD pipeline in Azure Pipelines. Azure Pipelines 以实现更高级的功能,如管道管理、可视化和触发器。Azure Pipelines to enable more advanced capabilities, such as pipeline management, visualization, and triggers.

后续步骤Next steps