Posted by
Rayis Imayev
on
(2020-Jan-28) This blog post is a followup to my previous post about DevOps (CI/CD) for Azure Data Factory - Continuous integration and delivery (CI/CD) in Azure Data Factory using DevOps and GitHub - Part 1 where I described a method to design a Data Factory code release & deployment to other environments.
Part 1:
Simple approach for Azure Data Factory code deployment by connecting code git repository to Azure DevOps Release pipelines to promote code to other environments.
Part 2:This time I would like to shed more light on how to utilize both Build and Release pipelines in Azure DevOps for Data Factory code deployment along with other supplementary artifacts. Other code artifacts could be PowerShell scripts, Database projects, Databricks notebooks, Logic Apps, etc.
To illustrate the 2nd approach using both Build and Release Azure DevOps pipelines I will be using PowerShell script from the official Microsoft documentation resource for Data Factory CI/CD - https://docs.microsoft.com/e…
Part 1:
Simple approach for Azure Data Factory code deployment by connecting code git repository to Azure DevOps Release pipelines to promote code to other environments.
Part 2:This time I would like to shed more light on how to utilize both Build and Release pipelines in Azure DevOps for Data Factory code deployment along with other supplementary artifacts. Other code artifacts could be PowerShell scripts, Database projects, Databricks notebooks, Logic Apps, etc.
To illustrate the 2nd approach using both Build and Release Azure DevOps pipelines I will be using PowerShell script from the official Microsoft documentation resource for Data Factory CI/CD - https://docs.microsoft.com/e…
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