Involvement across the enterprise is critical. “Building a community around DevOps and databases has been a huge help in advancing the DevOps culture in our organization,” said Jones. “The developers and DBAs are able to share their experiences. We’re seeing that the more experienced teams are excited to share what they’ve learned. Again, I believe DevOps is a culture, not just a group of concepts. In a large enterprise, it cannot be accomplished by just one development team. It requires changes from all levels of the information technology organization."
PREPARING FOR THE AGILE FUTURE
The transformation to agile infrastructure and organizations doesn’t happen overnight—it requires not only technology but also training and development. Agile processes and methodology training are essential to managers and professionals, said Furt. “The adjustment to agile processes is a paradigm shift for most, and training is just the first step on that journey of change,” she said. To adopt the new technology optimally, people need to fundamentally change how they think about data, architectures, and the organization of teams.
Brey compares such preparation and training to “team building skills, but on a whole different level because agility will require cross-team collaboration and even a certain amount of blurring the lines of traditional organizational structures.” To create differentiated value, organizations will need to focus on the cultural aspects of training, he noted.
In addition, developers and DBAs will need to learn more of each other’s roles. “Developers will need to see data management as something they can directly own and embed into their applications,” said Carr. “The training isn’t just the nuts and bolts of APIs—it’s also facilitating a cultural shift as the developer becomes decoupled from substantial data management and a transition is made to a mindset that the developer is their own data manager, data architect, and DBA.”
The challenge of applying DevOps, containerization, and microservices to databases “is that data is much more fluid than code,” said Fried. “However, data managers can put themselves ahead by applying these agility practices to both their software applications and then ultimately their data. For instance, containerization enables organizations to package an application in a portable container to speed up and simplify the deployment and configuration process. Code and data are stored separately, allowing customers to package their code cleanly in the container. When making application updates, new code can be up and running in the cloud very quickly, and data is then naturally used with the new version.”
It’s important “to be aware that you are applying a new mindset and simply have patience,” Fried continued. “DevOps practices are based on automation, meaning that you design processes to be replicable. It takes more time and resources to build the system initially, and it can be very frustrating as you need to go into the user interface and specify all the code up front. Once established, the ability to react quickly to incoming data, and the resulting insights pulled from it, increases exponentially. It’s also important to cut through misconceptions and hype by being persistent and asking a lot of questions.”