Data is a modern company’s greatest asset, if used effectively. After all, in our always-connected economy, the most valuable business applications are data-driven. Customers expect real-time interactions powered by millions of end-points and massive amounts of data. To remain competitive in the market, organizations are adopting fast data applications to create new business models and transform industries, and Kubernetes is increasing the velocity with which they can be deployed.
To better understand the types and volumes of data workloads deployed in Kubernetes, the Data on Kubernetes Community surveyed more than 500 international executives and technology leaders whose organizations are currently running data on Kubernetes (DoK). In addition, the Community leveraged Clearpath’s data-driven enterprise (DDE) scale to measure the technical maturity of organizations based on their use of data and their ability to operationalize and derive value from data. Based on the DDE scale, organizations were categorized as “Leading,” “Advancing,” “Aspiring,” or “Lagging.” The findings are reflected in the Data on Kubernetes 2022 Report.
DoK Has a Transformative Effect
Although the early adoption of Kubernetes was designed for stateless services rather than fast data applications, findings from last year’s DoK report found that 90% of respondents believed Kubernetes was ready for stateful workloads, and 70% were running them in production.
Today, running stateful workloads on Kubernetes isn’t only for early adopters. As Kelsey Hightower notes, “We’ve officially crossed the chasm.” Hightower’s statement corresponds with the growth trajectory of DoK workloads. More than one-half of respondents said they had 50% or more of their data workloads running on Kubernetes, with even more expecting to increase that by 30% in the next 12 months. In addition, almost one-half (40%) of Leading organizations plan to increase their DoK footprint by 50% or more in the next 12 months.
Organizations were found to be running a wide range of data workloads on Kubernetes, including databases (76%), analytics (67%), and AI/ML (50%). The rising adoption rate is attributed to the need to streamline their IT operations by ensuring consistency (43%) and simplifying management (41%).
DoK Benefits All Organizations, Regardless of Tech Maturity
The transformational impact of DoK isn’t limited to engineering–35% of respondents said they run DoK to increase their revenue growth and have seen positive gains. A major finding is that the majority of respondents (83%) attribute more than 10% of their revenue to running data on Kubernetes. Although Leading (63%) and Advancing (55%) organizations benefit the most, revenue gains are felt by Aspiring (34%) and Lagging (34%) as well.
Similar to last year’s report, productivity gains remain a key benefit of DoK. Leading (30%) and Advancing (39%) organizations saw their productivity increase by 2x or more. Productivity gains weren’t limited by tech maturity. Aspiring (39%) and Lagging (35%) organizations experienced 50% or more productivity gains.
However, the benefits of running data workloads on Kubernetes do not come without challenges.
Day-2 Operations Remain a Significant Challenge
Figure 5 For many organizations, the journey to Day-2 success with Kubernetes is not an easy one. Almost all the surveyed organizations that run data workloads on Kubernetes have run into challenges, most commonly during the development phase. For the second year in a row, organizations (35%) cite a lack of integration with their existing tools as the number-one challenge of running data workloads on Kubernetes. Successful production deployments at scale require a deep understanding of how Kubernetes integrates with existing IT infrastructure.
To bridge the Day-2 operations gap, 81% organizations are currently using (66%) or evaluating (15%) Kubernetes operators to automate stateful applications on Kubernetes. And because data is a modern company’s greatest asset, organizations want to ensure their operators are secure and easy to use.
Although technical challenges remain, most organizations don’t have the necessary skills and resources to run data workloads in production. Respondents cite a lack of qualified talent (34%) as the second biggest challenge–up from fourth last year. As workloads move closer to production, 42% of respondents find that it requires too much time and effort to manage them throughout their lifetime, especially as they look to automate provisioning and configuration management.
As the report notes, a lack of qualified talent will become a bottleneck unless organizations can upskill and train their existing teams to run complex workloads on Kubernetes. However, the future of DoK is bright, especially for Leading organizations (54%) who plan to re-skill and hire people in the next 0-3 months.
