Configure your release pipeline to trigger automatically as soon as there are any changes made to your 'dev' factory.Better CI/CD: If you are deploying to multiple environments with a continuous delivery process, git integration makes certain actions easier.Some team members may only be allowed to make changes via Git and only certain people in the team are allowed to publish the changes to the factory. You can also set up your factory such that not every contributor has equal permissions.
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Collaboration and control: If you have multiple team members contributing to the same factory, you may want to let your teammates collaborate with each other via a code review process.Configuring a git repository allows you to save changes, letting you only publish when you have tested your changes to your satisfaction. Whether your pipelines are not finished or you simply don't want to lose changes if your computer crashes, git integration allows for incremental changes of data factory resources regardless of what state they are in. Partial saves: When authoring against the data factory service, you can't save changes as a draft and all publishes must pass data factory validation.Ability to revert changes that introduced bugs.Source control: As your data factory workloads become crucial, you would want to integrate your factory with Git to leverage several source control benefits like the following:.
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This article will outline how to configure and work in a git repository along with highlighting best practices and a troubleshooting guide.īelow is a list of some of the advantages git integration provides to the authoring experience: Git is a version control system that allows for easier change tracking and collaboration. To provide a better authoring experience, Azure Data Factory allows you to configure a Git repository with either Azure Repos or GitHub.
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