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In this post in our Databricks mini-series, I’d like to talk about integrating Azure DevOps within Azure Databricks. Databricks connects easily with DevOps and requires two primary things. First is a Git, which is how we store our notebooks so we can look back and see how things have changed. The next important feature is the DevOps pipeline. The pipeline allows you to deploy notebooks to different environments.
In my video included in this post, I’ll show you how to save Databricks notebooks using Azure DevOps Git and how to deploy your notebooks using a DevOps pipeline. Be sure to check it out. Here’s a breakdown:
I find that the DevOps pipeline, as well as the release pipeline, is the best thing to come around in a long time. It’s a tremendous asset to have in your arsenal. We use it a lot, not just for Databricks, but for Data Factory, Key Vault Storage Account as well as other things.
Again, take a look at my demo for a detailed walkthrough of Databricks integration to Git and the DevOps pipeline. If you want to discuss more about Azure Databricks or have questions about Azure or the Power Platform, we’d love to help. Our expert team has all the knowledge and experience to show you how to integrate any Azure product or service in your organization.
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