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是否可以在 Azure 数据工厂的 Azure DevOps 中创建构建管道

[英]Is it possible to create build pipeline in Azure DevOps for Azure Data factory

I need to automate Azure Data Factory deployment via Azure DevOps.我需要通过 Azure DevOps 自动化 Azure 数据工厂部署。 As part of that, I have created a build pipeline but for enabling continuous trigger, which branch should I select?作为其中的一部分,我创建了一个构建管道,但为了启用连续触发,我应该使用哪个分支 select? Is it the adf_publish branch?它是 adf_publish 分支吗? If this is the branch, then I believe a new build should be published manually in the Dev environment to trigger a change in the adf_publish branch, which is a manual process.如果这是分支,那么我认为应该在 Dev 环境中手动发布一个新构建,以触发 adf_publish 分支的更改,这是一个手动过程。 Thanks in advance!!提前致谢!!

You should choose adf_publish branch when enabling continuous trigger.启用连续触发时应选择adf_publish分支。 So that whenever changes are published to adf_publish branch, your pipeline will be triggered.因此,每当更改发布到 adf_publish 分支时,都会触发您的管道。

By default, data factory generates the Resource Manager templates of the published factory and saves them into a branch called adf_publish.默认情况下,数据工厂会生成已发布工厂的资源管理器模板,并将它们保存到名为 adf_publish 的分支中。

To trigger a change in the adf_publish branch, you need to click Publish to manually publish your code changes in the collaboration branch to the Data Factory service, after you have merged changes to the collaboration branch (master is the default).要触发 adf_publish 分支中的更改,您需要在将更改合并到协作分支(默认为 master)后,单击发布以手动将协作分支中的代码更改发布到数据工厂服务。 So the the changes will be updated to adf_publish branch.因此更改将更新到 adf_publish 分支。

You can refer to the examples in below blogs:您可以参考以下博客中的示例:

Continuous integration and delivery in Azure Data Factory Azure 数据工厂中的持续集成和交付

Continuous integration and delivery (CI/CD) in Azure Data Factory using DevOps and GitHub 使用 DevOps 和 GitHub 的 Azure 数据工厂中的持续集成和交付 (CI/CD)

Azure DevOps Pipeline Setup for Azure Data Factory (v2) Azure 用于 Azure 数据工厂 (v2) 的 DevOps 管道设置

The above mentioned issue where dev values are hardcoded can be changed by adding parametrization template in the Azure DataFactory.可以通过在 Azure DataFactory 中添加参数化模板来更改上述对 dev 值进行硬编码的问题。 Using the below link from Microsoft custom parameters can be added.可以使用 Microsoft 自定义参数中的以下链接添加。 https://docs.microsoft.com/en-us/azure/data-factory/continuous-integration-deployment#use-custom-parameters-with-the-resource-manager-template https://docs.microsoft.com/en-us/azure/data-factory/continuous-integration-deployment#use-custom-parameters-with-the-resource-manager-template

Yes, you can.是的你可以。 I am working on a three part series on setting up Azure DevOps for your Data Factory.我正在编写一个由三部分组成的系列,为您的数据工厂设置 Azure DevOps。 Check out part 1 which I just published.查看我刚刚发布的第 1 部分。 https://doylestowncoder.com/2021/11/29/building-ci-cd-pipelines-with-azure-data-factory-part-1/ https://doylestowncoder.com/2021/11/29/building-ci-cd-pipelines-with-azure-data-factory-part-1/

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