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You can build, test, and deploy your Azure Stream Analytics (ASA) job 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.
Follow the steps to create a CI/CD pipeline for your Stream Analytics project:
Create a Stream Analytics project using VS Code. You can either create a new project or export an existing job to your local machine using the ASA Tools extension for Visual Studio Code.
Commit your Stream Analytics project to your source control system, like a Git repository.
Use Azure Stream Analytics CI/CD tools to build the projects and generate Azure Resource Manager templates for the deployment.
Run automated script tests for quality regression.
Deploy the job to Azure automatically.
You can use the command line and Azure Stream Analytics CI/CD tools to auto build, test, and deploy. You can also set up a CI/CD pipeline in Azure Pipelines. Azure Pipelines to enable more advanced capabilities, such as pipeline management, visualization, and triggers.
Събитие
31.03, 23 ч. - 2.04, 23 ч.
Най-голямото събитие за обучение на Fabric, Power BI и SQL. 31 март – 2 април. Използвайте код FABINSIDER, за да спестите $400.
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Пътека за обучение
Define and implement continuous integration - Training
Create automated pipelines that continuously build, test, and deploy your applications and prepare for Exam AZ-400: Designing and Implementing Microsoft DevOps Solutions.
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Microsoft Certified: DevOps Engineer Expert - Certifications
This certification measures your ability to accomplish the following technical tasks: Design and implement processes and communications, design and implement a source control strategy, design and implement build and release pipelines, develop a security and compliance plan, and implement an instrumentation strategy.