Kubernetes remains king of the Cloud Native Computing Foundation (CNCF) hierarchy, a position the open source-focused cloud native group expects will only accelerate with growing AI opportunities.

Results from CNCF’s latest Annual Cloud Native Survey showed that 82% of container users were running Kubernetes in production last year. That was touted as showing the open-source orchestration platform was “the default choice for building scalable, observable systems.”

That adoption was a nice boost over the 66% who reported similar usage in 2023, though a noted dip from the 85% who claimed Kubernetes usage in production in 2024.

That discrepancy aside, the CNCF survey showed 66% of respondents reported their organization was using Kubernetes to host generative AI workloads. This was deemed as illustrating “how Kubernetes has become the common denominator for cloud native scale, stability, and innovation, especially as organizations bring AI workloads into production environments.”

“Over the past decade, Kubernetes has become the foundation of modern infrastructure," CNCF executive director Jonathan Bryce noted in a statement. “Now, as AI and cloud native converge, we're entering a new chapter. Kubernetes isn't just scaling applications; it's becoming the platform for intelligent systems. This community has the expertise to shape how AI runs at scale, and we have a massive opportunity to build something open, powerful, and impactful for the next 10 years.”

However, the survey also clarified that only 7% of organizations were deploying AI models “daily” and 47% deploying “occasionally,” with 44% of respondents stating they did not yet run AI or machine learning workloads on Kubernetes, “underscoring the early stage of AI production maturity.”

That early stage opportunity was also highlighted by a recent Spectro Cloud survey that found enterprises using Kubernetes are twice as likely to scale so-called “edge AI” applications and 20% more confident presenting return-on-investment plans to company leadership.

Vendors are also taking notice.

Cast AI recently launched its Omni Compute unified control plane for Kubernetes designed to automatically find and connect external cloud resources – including GPUs – to existing clusters, allowing workloads to run on the best resources locally or across clouds without changes.

The Miami-based startup is positioning its Omni Compute offering as a way for firms to run workloads – including AI inference – without cloud lock-in, while ensuring compliance control is met. Teams can use the service to scale without pinning workloads to a single region or provider, while keeping infrastructure behavior automated and predictable.

“Enterprises don’t just need cheaper infrastructure, they need infrastructure that adapts automatically as workloads and constraints change,” Cast CEO Yuri Frayman explained. “That is what our automation agents were built to do, and this investment helps us scale that globally.”

Oracle is among the cloud providers making GPU capacity available to Cast customers through the Omni Compute, providing access to Oracle Cloud Infrastructure (OCI) AI infrastructure to firms running on any hyperscaler.

What’s next?

Analysts have also linked this Kubernetes-orchestrated AI opportunity to broader use cases.

ABI Research Senior Research Director Dimitris Mavrakis recently noted that operators need platforms that “combine Kubernetes automation with telco-grade security, observability, and lifecycle management.”

The analyst firm linked this shift to operators preparing their networks to better support what it termed the “next phase of the AI supercycle,” which it claims will be the distribution of AI inferencing across the network.

Looking ahead, CNCF said the next wave of Kubernetes-linked AI innovation “will hinge on resolving cultural adoption barriers, investing in platform engineering, and evolving security and observability standards.”

"Enterprises are aligning around Kubernetes because it has proven to be the most effective and reliable platform for deploying modern, production-grade systems at scale—including AI—and because of the ecosystem and community that support it," Hilary Carter, SVP of research at Linux Foundation Research, explained. "This year's data shows that the next phase of cloud native evolution will be as much about people and platforms as it is about the tech itself. Organizations that invest in both will have a clear advantage."