Nutanix Expands Cloud Platform with Governance Controls for Production Agentic AI

Nutanix expands cloud platform with controls for agentic AI

Nutanix expands cloud platform with controls for agentic AI Nutanix Inc. today introduced new capabilities intended to help enterprises run agentic artificial intelligence applications alongside existing virtual machines and containerized workloads without splitting their infrastructure into separate management silos. The updates include the general availability of Nutanix Enterprise AI 2.8 and a forthcoming release of Nutanix Kubernetes Platform 2.19. Nutanix also made its Service Provider Central program for cloud partners generally available and detailed a partner program for building cloud, Kubernetes, AI and virtual machine migration services. The company calls its approach "dual-native" because its platform treats VMs and containers as first-class infrastructure. That means customers can run Kubernetes on Nutanix's Acropolis Hypervisor virtualization platform when isolation and operational consistency are priorities or deploy Kubernetes directly on bare-metal systems for workloads that require different performance or resource profiles. The distinction is not simply the ability to support both architectures, said Thomas Cornely, executive vice president of product management at Nutanix.. "It's not about getting containers working; it's about how you operate and manage those containers," he said. The customer selects the environment for each workload, and Nutanix optimizes deployment based on that decision. "They decide," Cornely said. "What we can do is provide optimizations of how the workload is actually getting deployed once you choose the location and the substrate. But the choice is theirs." NAI 2.8 adds a generally available Model Context Protocol gateway to Nutanix Agent Gateway. It provides a central point for governing the tools and data that AI agents can access through MCP. A separate MCP Server for Nutanix Cloud Platform gives agents controlled access to infrastructure managed by the company's software. The gateway also tracks token use and allows organizations to impose quotas at the team, user or agent level. That addresses a growing customer concern as autonomous agents make repeated model calls that users may not see or anticipate. "The first things that customers ask for are visibility, control and governance," Cornely said. "They don't control the cost per token." He said this can leave customers with bills they can't control or predict. Cornely said Nutanix has encountered customers whose monthly AI allocations disappeared much faster than planned due to rampant token usage. "We've seen scenarios where customers had a budget for a month that was spent in a week," he said. NAI can steer appropriate work toward privately deployed open-weight models, where customers pay for infrastructure rather than individual tokens. "If I'm doing basic scripting of Python coding, I don't need a frontier model," Cornely said. "I could do that with an open-weight model." Private Inference in NAI 2.8 adds Low-Rank Adaptation fine-tuning for models containing fewer than 8 billion parameters, multi-graphics processing unit inference using tensor parallelism, batch inference and speculative decoding. Nutanix claims that speculative decoding can increase token-generation speed by up to 2.5 times, though Cornely acknowledged that results depend on the model and its infrastructure configuration. The release also expands auditing. Consumption controls can be applied to individual agents, then aggregated across users, agents and teams. MCP activity logs can record which data sources and applications an agent has accessed, as well as what actions it has taken. However, inspecting prompts is not the product's default purpose, Cornely said. "Your MCP servers are only as secure as the backend infrastructure and the back-end set of API keys and role access controls," he said. NKP 2.19, scheduled to be available soon, will extend Kubernetes management across virtualized and bare-metal environments. NKP Metal automates operating system, firmware and container deployment, while NKP on AHV integrates with Nutanix Flow for network isolation. An application catalog will offer curated deployments of the open-source Kubeflow, Milvus and Slurm tools favored for AI development. The platform has also received Cloud Native Computing Foundation Kubernetes AI Conformance certification, Cornely said. Nutanix also said its Unified Storage product has received enterprise-level Nvidia certification. It's used to feed data to GPUs with low latency and high throughput. Use of Nutanix storage is optional. For service providers, SP Central provides a multitenant control plane for providing infrastructure, application, cloud-native and AI services. The Powered by Nutanix: Verified Services program provides onboarding, delivery materials and badges intended to help partners build recurring services businesses. Although the announcements strengthen Nutanix's pitch to customers of Broadcom Inc.'s VMware virtualization software, Cornely said displacing VMware needs to be part of a broader modernization effort. "You don't just replace the VMware with the same old thing," he said.

Nutanix Bets Big On Agentic AI With New Controls For The Hybrid Cloud

Nutanix is extending its cloud platform for production agentic AI with new inference, governance, Kubernetes and multitenancy capabilities aimed at helping enterprises and service providers build, run and secure AI agents across hybrid environments. Nutanix has enhanced and expanded its Nutanix Cloud Platform for production agentic AI with the addition of a dual-native architecture featuring a new Model Context Protocol, or MPC, agent gateway as well as streamlined container management. San Jose, Calif.-based Nutanix Wednesday unveiled Nutanix Enterprise AI 2.8, which offers centralized control for AI inference and agentic AI. Also new is Nutanix Kubernetes Platform 2.19, which is slated to streamline container management for bare-metal and virtualized environments. NKP 2.19 includes a built-in AI catalog for building and running agentic AI applications. [Related: Nutanix Goes Big On Agentic AI, Adds Multi-Tenant Cloud Capabilities] Thomas Cornely, Nutanix's executive vice president of product management, told CRN the enhancements come at a time when agents are running on CPUs and GPUs and containers on both legacy and virtual machine infrastructure. "You have your core infrastructure, your agentic, compute-centric tier, and your intelligence tier," Cornely said. "Very few companies, and I would argue actually no other companies, have a platform that allows you to support all of this and give you a consistent way to govern, monitor, operate and just build these end-to-end solutions. This is where Nutanix comes to play." Cornely said Nutanix is combining the core pieces enterprises need to build, run, secure and govern agentic AI across hybrid environments, giving IT a consistent way to control how agents access cloud models and enterprise applications and data on-premises or in public clouds. That work builds upon 16 years of Nutanix platform development and applies it to an AI model in which agents run on containers, consume applications on virtual machines, and connect to GPU-based intelligence in the cloud or on-premises. Nutanix Enterprise AI 2.8 gives customers a centralized agent gateway for AI inference and agentic AI, Cornely said. Customers are already seeing token consumption and costs rise as AI use expands, making visibility and controls critical, he said. The gateway lets customers see who is consuming tokens, which models they are using and how much they are spending. IT teams can then set access policies, cap usage, and route workloads to the right models based on cost and performance. "Not all tasks should be getting tokens from the most expensive, highest-performance model," he said. "Use some of the high-end models for the most advanced requests. Use your open-weight models for your more common requests." NAI 2.8 also includes private inferencing and a centralized MCP layer to govern how agents access applications. Cornely said the goal is to avoid fragmented MCP configurations and give IT one place to manage policies for developers and AI builders. The next layer is Nutanix Kubernetes Platform 2.19, which underpins NAI because agentic AI workloads run on containers, Cornely said. NKP originally came from Nutanix's D2IQ acquisition, and is Cloud Native Computing Foundation-compliant, open-source centric, and designed to simplify Kubernetes deployment, management and multitenant operations. NKP demand is rising as more agents run on containers, Cornely said. NKP 2.19 adds Cloud Native Computing Foundation AI conformance, GPU optimization and an AI catalog with open-source components plus Nutanix's AI Gateway, private inferencing and MCP capabilities. "We're also adding into NKP 2.19 an AI catalog which basically will provide a set of services built into the platform to make it easier for AI builders to build agents using [NKP]," he said. "They're complemented by some of our own, like our AI Gateway, our NAI for private inferencing, our MCP servers." Cornely said NKP 2.19's "dual-native" architecture can run on Nutanix's AHV hypervisor, bare metal or public clouds, giving customers flexibility to test AI services in the cloud or on available on-premises infrastructure before moving into production. That architecture also supports Nutanix's service provider strategy. Cornely said Service Provider Central, or SP Central, extends the management plane with service provider-governed multitenancy across virtual machines, data, networks and containers, helping MSPs modernize VMware-based environments while adding AI services. "SP Central allows you to do VMs and containers and do more advanced AI services at the tenant level," he said. "This is good for MSPs because they're all modernizing and extending their set of offerings." Cornely said neoclouds that now serve a small number of large tenants will need more agile multitenancy as they target enterprise customers. Nutanix sees VMs, containers, AI services and SP Central as the foundation for that shift. Anthony Jackman, chief innovation officer of Pittsburgh, Pa.-based solution provider, data center services provider and Nutanix channel partner Expedient, said Expedient's entire AI product line is cloud-native by design, running on Kubernetes, and its default is NKP. "Every customer of ours gets their own NKP cluster where we run all of the services we're providing to them," Jackman told CRN. "But we're also working with Nutanix's gateway product and NAI. Our offering is not quite available to the market yet but will be within a month. We've been running it in the lab and working with Nutanix's development team for many months." Nutanix's history is a continuing attempt to make everything as easy and consumable as possible, and that's a very positive thing, Jackman said. "It's not always as relevant for our clients directly because they have us there to do it for them," he said. "It does benefit us in that we can make it easier to operate at scale, make it more consistent across clients, which leads to a lower price and a better experience." Jackman said Expedient has been working with Nutanix on multitenancy for several years and was the first customer to use it. "We worked with their engineering team, and we're going to have our offering out the door shortly to customers, which is I think really going to open up the number of customers that can take advantage of this," he said. "It's the quickest, most cost-effective way to consume cloud, and it's largely the same Nutanix experience that we've always known. It just opens it up to more clients to start small and get big." Jackman also said NAI 2.8 and its new MCP gateway is very important to customers. "You know AI that doesn't have hands doesn't really do much for you," he said. "And giving it hands that are not controlled is something that enterprises should not do. This is about centralizing control and making it easy. We're leveraging it to put a security wrap around AI and make it easier for our clients to adopt it in a secure manner. I think it's really great to see them expanding that capability. They're listening to their customers and listening to the market."

Nutanix Gives Enterprises The Freedom To Run Production Agentic AI Their Way

* Nutanix Cloud Platform (NCP) is being enhanced and expanded for production agentic AI with its dual-native architecture, including the introduction of Nutanix Enterprise AI (NAI) 2.8 and Nutanix Kubernetes Platform (NKP) 2.19. * The new capabilities give customers a flexible cloud operating model designed to consistently manage and govern AI across environments, supported by a dual-native architecture for virtual machines and containers. * NAI 2.8 is available now. It provides centralised control for AI inference and agentic AI, including Nutanix Agent Gateway, now with a generally available Model Context Protocol (MCP) gateway for governing how agents connect with apps and data via MCP. Nutanix Private Inference also provides enhanced capabilities for high-performance fine tuning and inference, along with improved security and governance. * NKP 2.19 will be available soon. It is expected to provide streamlined container management for bare metal and virtualised environments, with a built-in AI catalogue designed for building and running agentic AI applications. * The new capabilities in NAI 2.8 and NKP 2.19, combined with Cloud Native Computing Foundation (CNCF) certification, enhance NCP dual-native and AI capabilities. * Nutanix: Verified Services program and Service Provider (SP) Central are now available to help partners drive new AI opportunities. WHY IT MATTERS Enterprises often struggle to deploy AI alongside the apps and data it needs to access. Nutanix aims to solve this with a governed, dual-native architecture that runs both virtual machines (VMs) and containers side-by-side. This allows customers to bring AI directly to their apps and data regardless of how they are deployed, helping accelerate ROI without adding architectural complexity. Nutanix (NASDAQ: NTNX), a hybrid cloud leader and AI innovator, today announced the general availability of Nutanix Enterprise AI (NAI) 2.8, and the upcoming general availability of Nutanix Kubernetes Platform (NKP) 2.19, along with new incentives, programs, and resources designed to help partners accelerate growth on emerging AI opportunities. Many enterprises face a major roadblock when deploying AI: AI is accelerating the shift to containers, while critical applications and data remain spread across both virtualised and containerised environments. This divide can force enterprises to add infrastructure silos, move data or rearchitect existing workloads to support AI alongside the applications and data they already run. Nutanix addresses this with a governed, dual-native architecture that runs traditional applications and modern AI side by side, allowing the infrastructure to flexibly support the workload, integrated with leading silicon partners to provide choice and flexibility to customers. By bringing AI to where enterprise data already lives, Nutanix helps customers reduce silos and accelerate ROI without costly rearchitecting or added networking and data layer complexity. Expanding on NCP capabilities, NAI and NKP are designed to enable organisations to securely run, manage, and govern AI, containerised applications and virtualised workloads through a consistent control plane. These complement the core platform capabilities for near-bare metal performance for AI on virtualised infrastructure introduced with NCI 7.6. Together, they give enterprises a flexible alternative to infrastructure stacks that limit architectural choice, drive up costs, and require disruptive platform changes. For partners, the new Powered by Nutanix: Verified Services program aims to enable them to capitalise on major industry shifts and next-generation AI deployments by empowering them to build validated, high-margin services practices that span the full customer lifecycle. To operationalise these flexible new offerings, Service Provider (SP) Central provides an adaptable multitenant cloud foundation, giving service providers the control they need to grow infrastructure, platform, cloud-native, and AI services on their own terms. "Organisations across APJ are under pressure to turn AI ambition into business outcomes, while continuing to support the applications and infrastructure they already rely on. As agentic AI adoption accelerates, the priority across the region is finding a simpler way to run AI at scale, with the governance, security and consistency required for production environments. Customers want the flexibility to adopt AI on their own terms, without embarking on large-scale rearchitecting projects. At the same time, there are significant opportunities for partners and service providers to develop new AI and cloud services that help customers accelerate their modernisation efforts," said Jay Tuseth, Vice President and General Manager - APJ, Nutanix Nutanix Enterprise AI: Helping Enterprises Bring AI to Their Data Without Rebuilding Everything NAI delivers a unified and secure platform to deploy, manage, and scale AI workloads across hybrid environments. It enables enterprises to enforce governance over their agents and models, gain total visibility over token usage, and streamline AI development with a simple interface with built-in observability metrics and easy to use model-as-a-service while ensuring security, scalability, and integration with existing infrastructure. Key NAI updates include: * Agent Gateway: This now includes a generally available MCP Gateway which serves as a secure, unified front door for AI agents to access tools and data without custom engineering. To complement this, Nutanix has also released MCP Server for NCP to help customers build agentic AI applications with secure access to the infrastructure managed by Nutanix. * Private Inference: New advanced inference and fine-tuning capabilities enable scalable, multiGPU inference for LLMs via tensor parallelism, delivering high-throughput serving and low-latency response times for enterprise LLM workloads. In addition, this enables batch inference and speculative decoding. Key features include: 1) Parameter-Efficient Fine-Tuning which supports Low-Rank Adaptation (LoRA) fine-tuning for smaller models (<8B parameters), helping organisations to cost-effectively customise open LLMs on private domain data using single-GPU compute while seamlessly deploying adapters straight to serving pipelines; 2) Scalable multiGPU serving which enables high-throughput multiGPU inference via tensor parallelism, delivering fast, distributed serving across enterprise hybrid cloud environments; and 3) Speculative decoding which accelerates LLM inference token generation by up to 2.5x using lightweight draft models, cutting output latency without sacrificing model accuracy. * Enhanced Security against Rogue AI: With the rise of agentic AI and the risk of models breaking out of sandboxes, security is paramount. NAI provides robust protection against rogue models through our platform and APIs, featuring fine-grained Identity and Access Management (IAM), custom roles and seamless model sharing. This enforces least-privilege security, helping ensure agents operate securely and restricting access to only authorised roles, as well as support for air-gapped NVIDIA NIM deployment. Nutanix Kubernetes Platform: A Trusted, Production-Ready Foundation for Modern Apps and AI With NKP, organisations can simplify container operations across containers running on bare metal and VMs without piecing together complex, custom stacks. The upcoming release will provide an AI-optimised platform for building and running agentic applications at scale, including the following features coming soon: * NKP Metal: Built to bring HCI-grade simplicity to bare-metal Kubernetes, with automated OS, firmware, and container deployment, and persistent, enterprise-grade storage natively, eliminating the complexity of patchwork platforms. * NKP Full Stack: While NKP Metal is intended to bring simplicity to bare-metal deployments, NKP on AHV remains the cornerstone for organisations requiring robust, agile virtualised environments. Combined with Nutanix Flow, NKP on AHV is designed to deliver stronger network-level sandboxing for AI agents, helping provide essential isolation to mitigate the risk of rogue attacks and lateral movement. * AI Applications Catalogue: Offers a one-click deployment path for curated, validated AI/ML software (Kubeflow, Milvus, Slurm) to help bypass manual integration challenges. * Hardware and Compliance: Planned expansion of ecosystem support with validated GPU integrations, alongside dynamic resource allocation for modern AI workloads. CNCF Certified Kubernetes AI Conformant Platform: NKP has attained formal CNCF certification to validate that NKP provides the standardised APIs and capabilities required to reliably operate enterprise AI workloads. AI Storage Performance and Validated Certifications with NVIDIA Demanding AI workloads require infrastructure that keeps data moving, maximises GPU utilisation, and reduces deployment risk. Nutanix Unified Storage (NUS) recently achieved NVIDIA-Certified Storage validation at the enterprise level, providing a trusted, interoperable foundation that helps eliminate data bottlenecks. NUS establishes a low-latency, high-throughput data path directly to GPUs, maximising GPU utilisation and ensuring linear scalability for large-scale production AI workloads. Helping Partners Build, Monetise, and Grow AI Services According to Gartner®, "By 2029, 55 percent of enterprises will migrate 100 percent of workloads from VMware to alternative infrastructure delivery solutions".* To help partners capitalise on this market shift, next-generation AI deployments and other emerging opportunities, Nutanix recently launched the Powered by Nutanix: Verified Services program. This program provides the framework to support the broader partner ecosystem in transitioning from traditional, one-time deals to high-margin, recurring revenue streams by building validated services practices. Backed by streamlined onboarding, comprehensive service delivery kits, and exclusive badging across hybrid cloud infrastructure, Kubernetes, and VM migration, the program equips partners to own the full customer lifecycle, drive faster time-to-value, and maximise long-term retention. Nutanix is also announcing the general availability of SP Central, a unified multitenant control plane that gives displaced VMware service provider partners greater choice in how they build and monetise services. Service Provider Central gives providers one consistent foundation to build and monetise a broad portfolio of infrastructure, application, cloud-native, and AI services, with the flexibility on deployment location and licensing they need. This is designed to help providers improve utilisation and protect margins while giving customers more choice in how and where they run applications and AI workloads. Industry Analyst Commentary "By introducing a "dual native" model that unifies services such as networking, security, and data protection across both VMs and containers, Nutanix is leaning into a competitive landscape where consistent policy enforcement and lifecycle management are becoming key differentiators. Enterprises are increasingly prioritising platform consistency as application portfolios span legacy, refactored, and cloud-native designs." - Matt Flug, IDC Ecosystem Partners Commentary "At Continent 8 Technologies, we've worked closely alongside Nutanix to help shape the next generation of cloud services for regulated industries. Our continued collaboration with Nutanix, including the development of Service Provider Central, is built around helping our customers adopt modern cloud and AI capabilities without adding unnecessary complexity. Together, we're enabling organisations in highly regulated industries to innovate faster and focus on their core business, while maintaining the security, compliance, and operational control they require." -- Edward O'Connor, Chief Technology Officer at Continent 8 Technologies Availability NAI 2.8 and SP Central are generally available now. NKP 2.19 will be available soon. *Gartner, 2026 Strategic Roadmap for VMware Modernization, Julia Palmer, et al., 7 April 2026 GARTNER is a trademark of Gartner, Inc. and/or its affiliates. IDC, Nutanix .NEXT 2026: Enabling Customer Choice in Compute and Deployment Architectures, April 10, 2026, Matt Flug About Nutanix Nutanix is a hybrid cloud leader and AI innovator, offering organizations a unified infrastructure software platform to safely run applications, data, and AI anywhere. Trusted by customers worldwide, Nutanix empowers more than 50% of the Global 2000 to innovate faster with AI, while modernizing infrastructure, simplifying operations, and controlling costs. Learn more at www.nutanix.com or follow us on social media.