Implement CI/CD in Azure Data Factory using Azure Devops

In this project, we are going to see how to implement CI/CD in Azure Data Factory using Azure Devops


In real world scenarios, usually you would have a DEV environment and QA environment and PROD environment while implementing data engineering solutions using Azure Data Factory.
Also, there would be three different Azure Data Factory services created, one for each environment (DEV,QA,PROD).

So for faster and automated deployments of your data factory pipelines from one environment to another (DEV to QA, DEV to PROD) we can use Azure Devops CI/CD functionality to achieve this.

Hence , in this project we are going to see with an example how to deploy Azure Data Factory metadata(pipelines/linked services/datasets etc) from DEV to QA using Azure Devops CI / CD pipelines.




Pre requisites:
1. Azure subscription account(its preferred to have owner level access on the subscription account)
2. Basic understanding of Azure Data Factory
3. Azure Devops account

Here is a brief description of the tasks we are going to perform in this project:

Task1: Setup a DEV and QA environments
In this task we are going to create a ADF account for DEV environment and a ADF account for QA environment. Also, we would be creating Azure Data Lake Storage Account for DEV and QA.

Task2: Configure Azure Devops account
In this task, we are going to configure the Azure Devops account by creating an organization and a project. Also, we would be creating a sample pipeline in ADF Dev environment and setup code repository in ADF Dev environment.

Task3: Create Azure Devops pipeline for CI/CD
In this task, we are going to create pipeline in Azure Devops which will contain the actual logic to perform CI/CD of Azure Data Factory pipelines

Task4: Demo of Azure Devops CI/CD pipeline
In this task, we are going to see Devops CI/CD in action. So, we would be making some changed in Dev ADF pipeline and publish it to see if those changes were automatically migrated to QA ADF service.

Task5: Deploy to multiple environments
In this task, we are going to see how to deploy the data factory metadata to multiple environments (DEV,PROD,UAT etc) using the Azure Devops CI/CD pipeline