Azure Data Factory CI/CD tools

Introduction

This extension is developed to help you in your everyday work with Data Factory. It includes 2 pipeline tasks, which will be detailed below.

It can be used both in classic and YAML pipelines, although the examples will exclusively use YAML.

Task for validating pull requests

This task is not yet released, it will be added soon (before end of year)

With this task, you can run a series of tests against any change before accepting a pull requests. Most tests can be turned off, or configured to issue a warning or an error, while some tests will always be on and will always issue an error (hard limits enforced by the service as documented here).
Documentation for this task is available here.

Task for deploying changes to an environmant

This task will allow you to deploy to a Data Factory instance directly from the json files saved in your repo. It will compare the contents of your repo with already deployed content and only deploy new, updated or deleted elements. It also supports more advanced scenarious like manipulating linked services, triggers, references to Key Vault and/or Integration Runtimes per environment. Please see the documentation for the more advanced scenarious.
This task will deploy:

• Linked Services
• Datasets
• DataFlows
• Pipelines
• Triggers

Link to documentation

The use of the extension should to a certain degree be self-explanatory, but if you would like to dig deeper into some or the more advanced use cases, you'll find the documentation here

Link to issue tracker

If you encounter issues, please first look at the troubleshooting page. If you still can't solve your issue, please create an issue on my GitHub page

Also, if you have feature requests you should open an issue here.

Release Notes: