DevOps for Applications in Azure Databricks  Creating Continuous Integration Pipelines on Azure Usin

Working with our customers, developers and partners around the world, it’s clear DevOps has become increasingly critical to a team’s success. Continuous integration (CI) and continuous delivery (CD) which is part of DevOps, embody a culture, set of operating principles, and collection of practices that enable application development teams to deliver code changes more frequently and reliably. In this session, we will cover how you can automate your entire process from code commit to production using CI/CD pipelines in Azure DevOps for Azure Databricks applications. Using CI/CD practices, you can simplify, speed and improve your cloud development to deliver features to your customers as soon as they’re ready.

About: Databricks provides a unified data analytics platform, powered by Apache Spark™, that accelerates innovation by unifying data science, engineering and business.
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12 thoughts on “DevOps for Applications in Azure Databricks Creating Continuous Integration Pipelines on Azure Usin”
  1. In the Release pipeline of this presentation, demo is given by installing third party extension "Databricks Script Deployment Task by Data Thirst". But to Install, Azure DevOps Project Administrator permission is needed. It got rejected for me because this third party extension could be deprecated. Query: Is there an alternative to this extension?

  2. Is there a demo/video of building the build pipeline and release pipeline that are used in this demo? How did you use workspace API?

  3. Does the Databricks Notebooks Deployment extension not exist anymore? It's not available in any of my Azure subscriptions.

  4. How can we programmatically attach clusters to notebooks once the notebooks are deployed on the workspace?

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