In this keynote analysis from Nutanix .NEXT 2026, theCUBE's John Furrier and theCUBE Research analyst Paul Nashawaty break down how Nutanix is repositioning from a hyper-converged infrastructure company to the declared operating model for enterprise AI factories. With more than six press releases emerging from the keynote, the analysts examine CEO Rajiv Ramaswami's central thesis that Nutanix now serves as the operating model for AI factories and what that systems-level ambition means for the stack. Nashawaty explains how the acquisition of D2iQ and the resulting Nutanix Kubernetes Platform (NKP) underpin a unified strategy bridging VM and container workloads, with Kubernetes and cloud-native capabilities integrated by default across a single management plane.

The conversation also explores how shadow AI has emerged as a first-class enterprise governance problem — a far more complex challenge than legacy shadow IT — and how Nutanix is tackling it through unified compliance and policy controls across its full platform. Nashawaty notes that NKP has tracked at over 300% of targets in the 18 months since launch, reflecting strong market pull toward consolidated container management. The discussion also highlights a significant evolution in Nutanix's storage strategy, with new partnerships spanning Dell PowerFlex, Everpure and NetApp marking a clear departure from its proprietary HCI roots. Furrier underscores Nutanix's deliberate multi-silicon neutrality — partnering with both NVIDIA and AMD — as a Switzerland-style positioning that offers enterprises operational optionality in an AI-driven infrastructure market. From managing agentic sprawl to enabling bare metal Kubernetes at scale, the analysis outlines why modernizing to a cloud-native foundation is no longer a project — it's the price of entry for AI.

In this interview from Nutanix .NEXT 2026 in Chicago, Gregory Lehrer, vice president of business development and ecosystem at Nutanix, joins Todd Lieb, vice president of cloud partnerships at Dell Technologies, to talk with theCUBE's John Furrier and co-host Alison Kosik about how ecosystem partnerships are becoming a core competitive advantage in the enterprise AI era. Lehrer details how Nutanix's partner count has more than doubled year over year — with 5,000 attendees and over 100 sponsors on the show floor — reflecting the accelerating pull from enterprises building out AI infrastructure. Lieb frames the Dell-Nutanix relationship not as a point solution but as a layered platform play, with Nutanix sitting between Dell's AI factory hardware and the models and use cases running above it.

The conversation explores how the definition of partnership has shifted from go-to-market alignment to deep co-engineering, as customers demand fully integrated solutions spanning storage, compute, Kubernetes and agentic workloads. Lehrer underscores Nutanix's commitment to platform neutrality — working across Dell, AMD, NVIDIA and others — because enterprises no longer tolerate single-vendor lock-in. Lieb describes the overlapping partner ecosystems through a Venn diagram lens: the goal is to maximize customer choice and accelerate AI deployment regardless of where workloads land. Both guests highlight a growing ISV certification backlog as evidence of surging demand, with Lehrer noting that quality integration — not logo count — is the real measure of ecosystem health. From onboarding 1,000 new customers in a single quarter to building the containerized AI stacks that enterprises need to compete, the discussion outlines why a broad, well-integrated ecosystem has become the engine of scale.

In this interview from Nutanix .NEXT 2026 in Chicago, Tarkan Maner, president and chief commercial officer of Nutanix, joins Saud Al-Mishari, principal group product manager at Microsoft, and Scott Manchester, chief product and technology officer of Nerdio, to talk with theCUBE's John Furrier about navigating the great EUC migration era and how a three-way partnership is delivering unified hybrid experiences for modern enterprises. Maner frames the scale of the moment: with over 200 million cores changing hands as organizations exit legacy virtualization environments, end user computing has emerged as the critical modernization battleground. Al-Mishari details how Microsoft is evolving Windows365 from cloud PCs for humans to cloud PCs for AI agents — freeing workers from legacy application interfaces so agents can handle routine interactions. Manchester, who built Azure Virtual Desktop at Microsoft before joining Nerdio, explains how the two companies have maintained a partnership rooted in extending the platform's value rather than duplicating it.

The conversation also touches on the technical foundation enabling this migration surge. Al-Mishari explains how AVD Hybrid extends Microsoft's global connectivity plane — with UDP relays and ISP peering across every Azure region — directly into on-premises environments, cutting the latency that degrades user experience above 90 milliseconds. Customers migrating to the combined stack have reported reductions of more than 80% in help desk tickets, a concrete confidence signal the panel cites as evidence the experience gap has closed. Maner points to marquee deployments at State Street and Blue Cross Blue Shield — organizations navigating everything from VMware exits to HIPAA-regulated EUC workloads — as proof that outcomes at scale are achievable when ecosystem partners align on security, manageability and availability. From mapping user profiles across task workers, knowledge workers and regulated verticals to building a platform where AI agents can operate legacy applications autonomously, the panel outlines how the Microsoft-Nerdio-Nutanix ecosystem is positioned to guide enterprises through infrastructure modernization without disrupting the end user experience.

In this interview from Nutanix .NEXT 2026 in Chicago, Ketan Shah, vice president of products at Nutanix, joins Sandeep Singh, senior vice president and general manager of enterprise storage at NetApp, to talk with theCUBE's John Furrier and co-host Alison Kosik about the newly announced partnership between the two companies and how it equips enterprises to modernize infrastructure for AI and agentic workloads. Shah outlines the partnership's core premise: meeting customers where they are by combining Nutanix's cloud platform with NetApp's intelligent data foundation, while reusing existing hardware to reduce the friction of modernization. Singh underscores the elevated role of storage in the AI era, explaining how it has evolved from simply storing data to enabling real-time ransomware detection, immutable point-in-time recovery and high-performance access to KV caches that reasoning models depend on.

The conversation also explores how the partnership addresses the C-suite dimension of AI adoption, as token budgets, governance and cost per token become board-level concerns. Shah identifies three journeys Nutanix is driving — infrastructure acceleration, optimization and consumption — noting that sovereign on-premises deployments offer enterprises a path to lowering token costs while maintaining operational control. Singh reinforces that governance must be implemented across multiple layers of the stack, with time to first token and token throughput emerging as key operational metrics. Looking ahead, both leaders point to business continuity, hybrid cloud operations and agentic AI collaboration as the next frontiers for the partnership, with a general availability release planned for later this year. From IT administrators evolving into platform engineers to the convergence of AI-native and cloud-native architectures, the discussion illustrates how Nutanix and NetApp are positioning enterprises to turn AI ambition into measurable operational results.

In this interview from Nutanix .NEXT 2026, Thomas Cornely, executive vice president of product management at Nutanix, joins Ketan Shah, vice president of products at Nutanix, to talk with theCUBE's John Furrier about how enterprises are modernizing infrastructure to run agentic AI workloads at scale. Cornely and Shah describe what they call one of Nutanix's biggest releases in company history — spanning agentic AI readiness, a unified VM and container experience, expanded hardware ecosystem support and simplified management for distributed and sovereign environments. Shah explains how the "leverage what you have" philosophy underpins the release, enabling customers to run Nutanix on a wider range of servers and integrate with existing storage from Dell, NetApp and Lenovo — lowering the hardware barrier to entry in a supply-constrained market.

The conversation also explores how enterprises are navigating rapid AI sprawl and the governance challenges it creates. Shah unpacks the company's AI Gateway, a new capability that gives organizations visibility into agent activity, enforces rate limits and redirects token consumption across model endpoints — addressing cost and security governance as agentic workloads proliferate. Cornely frames sovereignty not merely as a data protection concern but as a financial and competitive strategy, highlighting the new Service Provider Central offering that enables MSPs and neo-clouds to deliver a full managed services stack — from VMs to AI as a service — on Nutanix infrastructure. From co-engineering validated solutions with Cisco, Dell and Lenovo to delivering an AI catalog inside NKP for developer self-service, both executives outline why Nutanix sees the agentic AI era as its broadest platform opportunity yet.

In this interview from Nutanix .NEXT 2026, Sachin Chheda, general manager of Nutanix Elevate Service Provider at Nutanix, joins Bryan Smith, chief executive officer of Expedient, to talk with theCUBE's John Furrier and co-host Alison Kosik about how enterprises are turning AI ambition into measurable business outcomes through modern hybrid cloud infrastructure. Chheda details two major conference announcements: SP Central, a multi-tenancy platform enabling service providers to build scalable, secure AI-native services on Nutanix, and the broader "Powered by Nutanix" program supporting IaaS, PaaS and cloud-native workloads. He explains how Broadcom's consolidation of its partner base has created an urgent opening for Nutanix, with displaced service providers forced to rebuild their business models — many turning to Nutanix and partners like Expedient to do so.

The conversation also explores how the AI conversation has matured from experimentation to ROI-driven deployment, with organizations now demanding clear returns and timelines. Smith highlights Expedient's approach of meeting clients where they are — making incremental infrastructure changes that deliver maximum impact without requiring wholesale transformation. The panel breaks down the build-versus-buy equation, noting that supply chain pressures have introduced a "wait tax" of 20–30% on hardware costs per quarter of delay, a dynamic that service providers can absorb by purchasing hardware nine to 12 months in advance. Smith also shares that Expedient has completed over 400 migrations in the past year with only a single rollback, crediting agentic tooling built on Nutanix's Move platform for the acceleration. From data sovereignty requirements in EMEA to unlocking the mid-market through multi-tenancy, the discussion illustrates how intelligent infrastructure — the convergence of cloud, data and AI — is becoming the platform for sustained enterprise growth.

In this interview from Nutanix .NEXT 2026, Erik Littlejohn, president and chief executive officer of CloudWave, joins Mike Donahue, chief operating officer of CloudWave, to talk with theCUBE's John Furrier and co-host Alison Kosik about how mid-market healthcare organizations are navigating the dual pressures of AI adoption and escalating cybersecurity threats. Littlejohn maps the mounting financial strain on community and rural health systems — from Medicare reimbursement cuts tied to the Big Beautiful Bill to relentless ransomware campaigns targeting organizations with IT staffs as small as five or six people. Donahue narrows the focus to CloudWave's core market of sub-thousand-bed hospitals, where IT is a cost center rather than a business priority, and where shadow AI has emerged as a critical governance gap — with clinicians routinely sharing protected health information with open consumer AI models to assist with diagnoses and discharge instructions.

The conversation also explores how CloudWave is evolving into a next-generation managed service provider by migrating a hundred customers onto the Nutanix platform — a shift partly accelerated by Broadcom's pricing changes and the need to deliver cost-efficient private cloud infrastructure to under-resourced hospitals. Littlejohn and Donahue detail how Nutanix's simplicity frees IT staff to focus on clinical workflows rather than hypervisor management. The discussion turns to agentic AI, where Littlejohn outlines CloudWave's ambition to build self-healing systems and proprietary AI applications that surface operational insights across its customer base — while Donahue cautions that maintaining human-in-the-loop oversight in clinical environments significantly complicates ROI measurement. From expanding security risk assessments to encompass AI governance audits to confronting AI-accelerated cyberattacks, the panel underscores why under-resourced health systems increasingly depend on scaled partners to manage the risks and rewards of AI adoption responsibly.

In this interview from Nutanix .NEXT 2026, Dan Regalado, chief information officer of Wynn Resorts, joins theCUBE's John Furrier and co-host Alison Kosik to discuss how a luxury resort operator is modernizing its hybrid infrastructure and applying AI to deliver seamless, personalized guest experiences at scale. Regalado explains Wynn's infrastructure philosophy — running cloud workloads where velocity and scalability matter and on-premise systems where security and stability are paramount. He details the company's migration from VMware to Nutanix at its Boston property, a carefully phased transition that now supports nearly 500 virtual machines powering casino gaming platforms, smart room automation and on-property sports betting. Regalado also notes Wynn is actively exploring Nutanix's on-premise and hybrid AI capabilities as it weighs data sovereignty and cost efficiency against its current cloud-first approach.

The conversation also explores how Wynn is approaching AI through three distinct lenses: operational efficiency, automation and personalization. Regalado describes a model where AI workers function as teammates alongside human staff — handling repetitive tasks through robotic process automation and accelerating software development through vibe coding — while freeing frontline employees to focus on the hospitality that defines the Wynn experience. He underscores a core company principle: technology will not replace the human warmth that drives guest satisfaction, but will empower teams to deliver it more consistently and at greater scale. Regalado also touches on how AI is reshaping C-suite dynamics, with leadership now meeting weekly to track adoption progress and actively prioritizing AI fluency in new hires. From using AI to surface real-time customer sentiment insights to personalizing how individual guests are recognized and rewarded, Regalado outlines how Wynn is building a future where human creativity and AI capability reinforce each other.

In this interview from Nutanix .NEXT 2026, Ashish Mohindroo, general manager and senior vice president at Nutanix, joins Olivier Zieleniecki, global vice president of worldwide partners at MongoDB, to talk with theCUBE's John Furrier and co-host Alison Kosik about how the two companies are building a production-ready platform for AI-native applications across on-premises and hybrid environments. Mohindroo and Zieleniecki announce an expanded integration between Nutanix Database Service (NDB) and MongoDB, certifying MongoDB across replica set and sharded cluster configurations to deliver a managed service that fills a critical gap for on-prem and hybrid customers. Zieleniecki explains how MongoDB has evolved from a document database into a unified data platform — now functioning as an active memory layer for AI-native applications — serving more than 65,000 customers across Fortune 500 enterprises that need flexibility to run transactional, streaming and real-time analytics workloads anywhere.

The conversation also explores how NDB abstracts database complexity through a single unified API, allowing developers to provision, clone and manage multiple databases — SQL or NoSQL — without rewriting application logic across environments. Mohindroo highlights meaningful performance and availability gains when MongoDB runs on NDB, including stronger disaster recovery and business continuity for enterprise workloads. Zieleniecki breaks down how the partnership model itself has fundamentally changed, shifting from competitive ISV dynamics to customer-first co-selling, where pre-integrated solutions reduce the burden of choice in a rapidly evolving AI market. Both guests underscore that data quality is foundational — AI systems are only as effective as the data feeding them. From consolidating fragmented data stacks to positioning the database as the fourth pillar of modern infrastructure alongside storage, compute and networking, the discussion maps a clear path for enterprises building the next generation of AI agents and applications.

In this interview from Nutanix .NEXT 2026, Ty Peavey, director of infrastructure services at Dartmouth College, joins Deepak Goel, chief technology officer of cloud native at Nutanix, to talk with theCUBE's John Furrier and co-host Alison Kosik about how a proactive VMware migration laid the foundation for running AI and cloud-native workloads at scale. Peavey recounts how Dartmouth seized a rare window — expiring VMware and hardware contracts converging simultaneously — to run a competitive evaluation that led the team to choose Nutanix with AHV over VxRail and ESXi-based alternatives. The migration collapsed complex three-tier hardware down to standard 2U servers, eliminated siloed job roles in favor of generalist infrastructure engineers and now supports roughly 1,000 VMs and 600 containers across two NKP clusters — all managed by a team of 11.

The conversation also explores the convergence of cloud-native and AI-native architectures, with Goel arguing that Kubernetes has become the natural home for agentic workloads — offering the lightweight scaling, security controls and scheduling properties that AI agents demand. He outlines why virtualization and containers are complementary rather than competing: containers maximize hardware utilization and agility, while VMs provide the isolation, lifecycle management and GPU scheduling efficiency that bare-metal deployments cannot easily replicate. Peavey grounds the discussion with three practical questions every organization must answer before scaling AI — how to deploy it securely, how to fund it sustainably and how to keep pace with functionality that evolves faster than adoption. From consolidating a fragmented infrastructure stack to managing token costs as a new operational currency, both guests make the case that platform discipline is the foundation for the AI era.

In this interview from Nutanix .NEXT 2026, Rajiv Ramaswami, chief executive officer of Nutanix, joins theCUBE's John Furrier and co-host Alison Kosik to discuss the company's evolution from a hyperconverged infrastructure leader into a full agentic AI platform. Ramaswami charts Nutanix's deliberate shift — from HCI and end-user computing to a platform capable of orchestrating containers, virtual machines and AI pipelines across hybrid and multi-cloud environments. He argues that AI has moved from experimentation into operations: enterprises must now manage not just applications and infrastructure but data pipelines, model governance and autonomous agents. A core technical focus is GPU optimization — Nutanix has extended its hypervisor to handle topology-aware workload placement and key-value cache offloading, keeping GPUs fully utilized and driving down cost per token, the unit of economics enterprises are now watching most closely.

The conversation also explores how Nutanix's expanding ecosystem — more than 100 partners at the event, spanning cloud, server, storage and chip providers — validates its platform ambitions. Ramaswami details new AI PaaS services set to launch this summer, offering developers curated open-source components alongside cost, access and governance controls for model deployment. The discussion shifts to sovereign clouds, where governments worldwide are funding infrastructure build-outs not just to protect data but to stimulate local economies and help domestic industries adopt AI at scale — an opportunity Ramaswami sees as particularly significant for Nutanix. He identifies simplicity and governance as the company's core long-term bets: the more accessible and cost-effective AI becomes to consume, the faster enterprise adoption grows, and sound governance ensures security, data privacy and access controls keep pace. From defining hyperconverged infrastructure to becoming the platform of choice for every application in an AI-driven world, Ramaswami outlines why Nutanix is positioning itself as the enabling layer for intelligence everywhere.

In this interview from Nutanix .NEXT 2026, Dan Ciruli, vice president and general manager of cloud native at Nutanix, joins Anindo Sengupta, vice president of product management at Nutanix, to talk with theCUBE's John Furrier and co-host Alison Kosik about the rapid convergence of cloud-native and agentic AI infrastructure and what it takes to build a unified enterprise platform for the next phase of AI. Ciruli and Sengupta describe Nutanix's strategic position as the software layer between chip infrastructure and AI models — the "middle of the cake" in a five-layer AI stack. Ciruli outlines how NKP now includes an AI path layer that delivers developer-ready tooling like Kubeflow and KServe as part of the infrastructure itself, removing the burden of configuration from application teams. Sengupta introduces SP Central, a new capability enabling service providers to build multi-tenant GPU clouds and offer managed compute to enterprises, providing flexible access to accelerated infrastructure without depending on constrained hardware supply.

The conversation also explores the economics of agentic AI, where a single user action can trigger hundreds of agent interactions and token costs escalate fast. Ciruli explains why enterprises will face a critical build-versus-buy decision — choosing between per-token API pricing, service provider compute time or owning on-prem infrastructure outright — and why AI FinOps is the inevitable next chapter of cloud cost management. Sengupta details how Nutanix Enterprise AI's gateway product governs model and tool access across agent deployments, while inference engineering techniques like quantization and KV cache management reduce cost per token without sacrificing performance. The discussion closes on the expanding edge opportunity, including a new partnership with RapidFort to harden software supply chain security and early deployments pushing containerized workloads to the far edge — including backpack-sized Kubernetes clusters for government use. From token economics to the hyperconverged edge, Ciruli and Sengupta outline why Nutanix is built to manage the infrastructure demands of the agentic AI era.