Enterprises face major challenges with cloud costs and more

A new study reveals that 93 percent of enterprise platform teams face persistent challenges with cloud costs, Kubernetes complexity and developer productivity.

The research from Rafay Systems shows that despite the widespread adoption of platform teams within IT organizations, survey respondents across the board confirm that these teams often are stretched to their limits managing complex multi-cluster Kubernetes and cloud environments.

Top challenges include managing cost visibility and controlling Kubernetes and cloud infrastructure costs (45 percent), the complexity of keeping up with Kubernetes cluster lifecycle management with multiple, disparate tools (38 percent), and the establishment and upkeep of enterprise-wide standardization (38 percent).

Nearly a third (31 percent) say that the total cost of ownership (including software/support licenses, salaries of resources) is higher than budgeted for or anticipated. Looking ahead, 60 percent report that reducing and optimizing costs associated with Kubernetes infrastructure remains a top management initiative in the next year.

There are challenges around adopting AII and GenAI too, the majority of respondents recognize the critical importance of efficient development and deployment methods, with 96 percent emphasizing this need for AI applications and 94 percent for GenAI applications.

Organizations are prioritizing key capabilities for their AI initiatives to overcome these obstacles. The top five features include pre-configured environments for developing and testing generative AI applications; automatic allocation of AI workloads to appropriate GPU resources; pre-built MLOps pipelines; GPU virtualization and sharing; and dynamic GPU matchmaking. These capabilities aim to streamline development, optimize resource utilization and manage costs effectively.

Enterprises are also prioritizing the developer experience with a growing emphasis on automation and self-service, spanning both AI initiatives and Kubernetes deployments. Priorities include automating cluster provisioning (47 percent), standardizing and automating infrastructure (44 percent), and providing self-service experiences for developers (44 percent).

"The survey's findings confirm the platform engineering trend Team Rafay has highlighted previously: platform teams are now decidedly in the driver’s seat when it comes to major tooling and architectural decisions for compute consumption," says Haseeb Budhani, CEO and founder of Rafay Systems. "It's also clear from the survey that these teams are grappling with ever-increasing costs and complexity. Success for these teams will hinge on them being empowered with the right tools and strategies to optimize resources, standardize processes and drive innovation. Organizations that actively support their platform teams in addressing these challenges are best positioned to thrive in an increasingly competitive and technology-driven business landscape."

You can find the full report on the Rafay site.

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