Utilize DevOps to Quickly Modify Database Structure

Database changes are tedious, time-consuming challenges that introduce a great deal of risk into any organization. Deploying database schema changes is a highly demanding technical task, and it takes critical development hours away from other strategic objectives.

At the same time, lagging database response can obstruct even the best-planned application deliveries and slow down an entire organization. Application developers are under constant pressure to release applications quickly – yet without the appropriate level of database support, they increasingly find themselves stuck against an increasingly intractable obstacle.

Eight out of every ten managers report that deploying database changes takes longer than application changes. However, managers who empower their DevOps team to take charge of database modification by using automation can reduce errors, improve performance, and guarantee compliance in the process.


Automating Database Schema Changes with DevOps

Many application stakeholders face serious production issues due to errors in database changes, which can take hours for the highest performing organizations to resolve. In lower-performance organizations, these production issues can last months.

Automation is the most effective way to address the obstacles that database schema changes generate. The key to evolving from a low-performance organization to a high-performance one is through integrating database architecture into DevOps.

According to the 2018 State of Database DevOps survey, the highest-performing organizations are able to leverage the power of automation to hugely improve key performance metrics:

  • DevOps database teams implement database schema changes 46 times more frequently than traditional database teams.
  • DevOps teams enjoy a change failure rate that is seven times lower than traditional database teams.
  • Organizations with integrated DevOps database teams are able to recover from database incidents 2,600 times faster than their peers.

Automation through DevOps empowers organizations to experiment with new strategies and improve customer adoption, retention, and satisfaction. At the same time, it provides a solid foundation for regulatory compliance.


How to Implement Automated Processes for Database Changes

Database change automation is a task that typically involves a great deal of manual code review, iterative changes, and verification. Automation allows developers to streamline the most difficult and time-consuming of these processes.

In a typical automated deployment pipeline, developers link deployments to source-controlled versions of application code. This way, development changes can be associated with the most recent deployment without having to manually search for, link, and verify the code itself.

Relatively few developers know this kind of functionality can also be extended to database changes. Doing so requires making some key workflow and pipeline adjustments that allow database schema and related information to operate like application data.

Developers can put the database into the source control directory and treat database changes in a similar way to application changes. Doing so requires meeting the following challenges:

  • Ensuring Data Persistence. Developers can’t simply drop and replace an entire database – the data must persist and remain available. This can be achieved with migration scripts, which must also be in the source control.
  • Loading Static and Test Data. Customer and transaction databases won’t function unless they are stocked with the immutable data that database-dependent applications require – lookup data and lists, for instance. These must also be located in the source control.
  • Including Instance and Server-Level Objects. A functional database system is more than the sum of its schema and static data. Instance and server-level objects, including roles and permissions vital to database security, must also be included in the source control to ensure database performance.
  • Preventing Database Drift. If it takes more than a day to make, test, and implement a one-line database change, database drift will eventually generate inconsistencies that cause deployment failures. This is especially true if database administrators regularly perform hotfixes without modifying the source control.

There are tools that can provide this level of functionality to SQL database administrators and DevOps teams. SQL Change Automation is an example of an SCA Visual Studio plugin that helps developers build, verify, and deploy SQL databases from source control while automating the most difficult and time-consuming steps of the process.

SQL Change Automation and other similar tools can auto-generate migration scripts for source-controlled databases while validating projects and incremental scripts and testing the resulting build. These tools also include release components that automate the deployment of the build package itself. This can transform a project timeline measured in weeks to one measured in mere hours.