Hybrid multicloud computing company Nutanix said on Aug. 27 it has officially launched Nutanix Enterprise AI (NAI) 2.8 and plans to officially release Nutanix Kubernetes Platform (NKP) 2.19.

NAI and NKP expand the capabilities of Nutanix Cloud Platform (NCP). They support secure operation and management of AI, containerised applications and virtualised workloads under a consistent control plane and allow governance to be applied.

The company said many firms face difficulties in adopting AI. AI is accelerating the shift to containers, but core applications and data remain distributed across virtualised and containerised environments. Because of this dual structure, companies face the burden of adding separate infrastructure silos, moving data or redesigning existing workloads to run AI alongside existing applications and data. Nutanix stressed that, taking this into account, it provides a governance-based dual-native architecture that can run existing applications and modern AI at the same time.

Nutanix said this allows companies to secure a more flexible alternative by moving away from existing infrastructure stacks that constrain architectural choices, raise costs or require large-scale platform changes.

Nutanix also unveiled new incentives, programs and resources to help partners accelerate growth by leveraging opportunities in the rapidly expanding AI market. A new program for partners, Powered by Nutanix: Verified Services, supports partners in leveraging major industry changes and opportunities to adopt next-generation AI.

Thomas Cornely (토마스 코넬리), senior vice president and head of product management at Nutanix, said companies do not need to rebuild from scratch the systems that run their existing business to adopt enterprise AI. He said Nutanix's dual-native architecture allows companies to apply AI in environments with existing applications and data while using the infrastructure best suited to each workload. He said it can also deliver consistent operations and governance across VMs, containers and AI. That provides companies with a practical way to introduce AI into real operating environments without creating new silos or limiting future choices, he said.