DEVOPSdigest

The smart business will use the best tools available for its jobs and will expand its capability strategically. Often this expansion takes the form of bringing in not just new technology tools but acquiring businesses — which might have their own tools. This is one way technical diversity grows in a business, and we are seeing it dramatically in the way companies use database products. Simply put: We're using more databases. And that comes at a cost.

More Databases

According to data from Redgate's 2024 The State of the Database Landscape report, 79% of businesses are running a multiplatform database environment, up from 62% in 2020. And it's not just that new, niche products are entering the market; the overall popularity of traditional juggernauts, such as SQL Server and MySQL, is wavering.

Reasons for the increasing diversity include newer and more diverse use cases but also a desire for more flexibility and, of course, cost savings.

And if that's not enough, companies are seeing that there's no one universal hosting architecture, with 70% of survey respondents using a hybrid (cloud plus on-prem) architecture for database hosting. Flexibility and scalability are the key drivers for that, as well as the capability to create high-available systems as needed. (And, yes, cost considerations too.)

Operationally, technological diversity is a challenge, especially in a continuous release or DevOps work cycle. Diversity means complexity, and it also impacts the skills that an organization needs to support. And yet, even as you add complexity and capability to your organization, you still see the need for unified monitoring and management. Without monitoring, things can run out of control — costs especially.

AI: Underused

But just as technology is diversifying, the platform story is getting more complex, and the need to optimize for cost (which translates to efficiency and performance) is growing, a new technology comes along that shows incredible promise to help the database professional: Artificial intelligence.

We're going to need all the help we can get as more companies adopt Database DevOps so they can deliver value to the business more quickly and continuously.

Today, less than a quarter of the people we surveyed work in companies that are using AI for database management, but 40% are considering it for the future.

The AI use we do see falls into a few areas, including testing and development, generating code and sample data, and simulating test scenarios.

AI use for testing shows great promise and could give companies a large security benefit, as our data shows that 60% of companies are still using production data in testing scenarios. That, we believe, is a large security risk. Companies in this situation should be looking at all methods to mitigate it.

The Skills Gap

The largest impediment to this new approach is not technical, it's human: Teams are not skilled for this new environment.

There are solutions to this challenge, but they are structural. Companies need to re-think how they hire developers, focusing more on hiring for a learning mindset vs. particular skills. Then, once these developers are onboard, they need to be supported with training programs, workshops, and a management mindset that supports peer training and knowledge sharing. These additions require that time and resources be budgeted to them.

Just as we are expanding the scope of the technologies we use to address database needs, we need to think expansively about how we hire, manage, and retain our personnel.