DevOps for Databases in Azure

Learn how to deploy database changes and updates using DevOps patterns and practices with MySQL, Terraform, and Azure in this hands-on project focused course:

DevOps for Databases

To kick off the DevOps for Databases project-focused course, we're going to talk about why practicing DevOps for databases is very-much the same as practicing DevOps with developer or infrastructure code.

• Source control with MySQL queries

• CI/CD and MySQL queries

• DevOps workflow

  
  

Creating a MySQL Database in Azure with Terraform

When you're creating a database, the best way to do it is with code. That way, you aren't manually clicking through a UI. The best place to start is with Terraform, an infrastructure-as-code language. You use Hashicorp Configuration Language (HCL) to write the code to create a MySQL database in Azure and a firewall rule.

• Resources to use in Terraform for Azure

• Create a MySQL database

• Create a firewall rule for the MySQL database

• Clean up your environment

  
  

Running the Terraform Creation in Azure DevOps

Taking the code that you wrote in video 2, you'll follow the same practices, but with a twist using CI/CD in Azure DevOps. The Terraform config files will be deployed via Azure DevOps to create a fully-functional pipeline that creates a database.

• Set up a YAML pipeline

• Use specific Terraform tasks

• Create variables and secrets

• Run the pipeline

  
  

Storing SQL Code in GitHub

No code is ready to be used until you store it in source control. Once code is stored in source control, others can collaborate on it and see it so they understand what's happening in the environment. This same workflow is no different with SQL code.

• Write a SQL query to create a database, table, and users

• Store the code in GitHub

  
  

Running a SQL Query in Azure DevOps

Once code is committed to source control, which you learned about in video 4, you can take the same approach as developers take to run their code in a CI/CD pipeline. Using Azure DevOps, you will create a pipeline that will be used to deploy a MySQL query.

• Set up a YAML pipeline to run MySQL code

• Use specific MySQL tasks

• Create variables and secrets

• Run the MySQL query via a CI/CD pipeline

  
  

Testing the SQL Query in Azure DevOps

Code should always be tested, regardless of if it's application code, automation code, or even SQL code. The last video in this project-focused course shows you how to create a test using Python. Once the test is created, you use an Azure DevOps pipeline to run the test.

• Create a MySQL test using Python

• Create a pipeline for the test

• Run the test in CI/CD