Version Control SQL Databases & DevOps Strategy - Series

Introduction 

Version Control systems (VCS) are essential tools that track changes in code and configuration over time. As developers or DevOps engineers make updates to code or configuration files, the VCS captures snapshots of these changes. The snapshots are stored permanently, allowing any version to be retrieved later if necessary. Without a VCS, it is common for developers and DevOps teams to create multiple copies of code and configuration locally, which can lead to confusion and potential data loss if changes are made to wrong copy. By managing and consolidating all versions, a version control system ensures that teams work with a single, consistent version at any given time, while retaining the ability to access and revert to previous versions if needed. 

Why Version Control? 

As a developer, there are numerous tasks that can consume your time, such as reproducing bugs, learning new tools, and adding new features or content. As users demands increase, version control becomes crucial for helping teams collaborate efficiently and meet deadlines. 

Benefits of Version Control 

• Create workflows: Version control workflows prevent chaos by standardizing development process and tools. They enforce consistent practices and manage permissions, keeping the team aligned. 
  

• Work with versions: Each version includes a description of changes, like bug fixes or new features, helping the team track updates by version rather than individual file changes. Versions can be viewed and restored anytime, making it easy to base new work on any previous version. 
  

• Code together: Version control synchronizes changes and prevents conflicts, helping the team manage simultaneous updates and resolve issues. 
  

• Keep a history: Version control tracks all code changes, allowing team members to see who made updates, why and when. This history supports experimentation and easy roll back to previous versions, enabling work from any past code version, like fixing bugs in earlier releases. 
  

• Automate tasks: Version control automation saves time and ensures consistency by automating tasks like testing, code analysis, and deployment with each new version. 
  

In this post, we will delve into the DevOps strategy specifically tailored for databases. We’ll examine how integrating DevOps principles with database management can enhance development and operational efficiency. This includes exploring methods for automating database deployments, managing database versions, and ensuring continuous integration and delivery. We’ll also discuss best practices for maintaining data consistency, handling schema changes, and improving collaboration between development and operations teams. By the end, you’ll have a comprehensive understanding of how to apply DevOps strategies to databases for optimized performance and streamlined processes. 

Prerequisites 

• SQL Server with source and target database instance.  

• Visual Code for SQL Server Database Objects. 

• Azure DevOps Account.  

Checklist to Cover 

1. Create an SSDT project. 

2. Link SSDT to Azure Repo with a Local Repo. 

3. Create a folder for DACPAC in Local Repo. 

4. Add settings in Visual Studio Code to point DACPAC creation to this folder. 

5. Build the solution. 

6. DACPAC should be created in the new folder. 

7. Push the code and sync it to Azure Repo. 

8. Verify the new folder is available in Azure Repo. 

9. Create a DevOps pipeline with DACPAC option. 

10. Configure and link it to Azure Repo. 

11. Test and run the pipeline on target database. 

12. SQL Objects should be deployed and should be available on target Database. 

I hope that you enjoyed this and please be on a lookout for the next part of this series.

Thank you