We often need a permanent data store across Azure DevOps pipelines, for scenarios such as: Passing variables from one stage to the next in a multi-stage release pipeline. Any variables defined in a task are only propagated to tasks in the same stage. Storing state between pipeline runs, for example a blue/green deployment release pipeline […]
Tag: devops
Data Lineage in Azure Databricks with Spline
The Spline open-source project can be used to automatically capture data lineage information from Spark jobs, and provide an interactive GUI to search and visualize data lineage information. We provide an Azure DevOps template project that automates the deployment of an end-to-end demo project in your environment, using Azure Databricks, Cosmos DB and Azure App […]
PaaS integration testing with Azure DevOps
Using Azure DevOps pipelines, we can easily spin test environments to run various sorts of integration tests on PaaS resources. Azure DevOps allows powerful scripting and orchestration using familiar CLI commands, and is very useful to automatically spin entire environments using Infrastructure as Code without manual intervention. Sample project In this example, we looked at […]
Tutorial: Monitoring Azure Databricks with Azure Log Analytics and Grafana
This is the second post in our series on Monitoring Azure Databricks. See Monitoring and Logging in Azure Databricks with Azure Log Analytics and Grafana for an introduction. Here is a walkthrough that deploys a sample end-to-end project using Automation that you use to quickly get overview of the logging and monitoring functionality. The provided […]
Tutorial: DevOps in Azure with Databricks and Data Factory
This is Part 2 of our series on Azure DevOps with Databricks. Read Part 1 first for an introduction and walkthrough of DevOps in Azure with Databricks and Data Factory. Setting up the environment To get started, you will need a Pay-as-you-Go or Enterprise Azure subscription. A free trial subscription will not allow you to […]
DevOps in Azure with Databricks and Data Factory
Building simple deployment pipelines to synchronize Databricks notebooks across environments is easy, and such a pipeline could fit the needs of small teams working on simple projects. Yet, a more sophisticated application includes other types of resources that need to be provisioned in concert and securely connected, such as Data Factory pipeline, storage accounts and […]