Virtana at Nutanix .NEXT 2026: The Next Frontier of AI Ops is Deep Observability for Nutanix AI and NVIDIA
Building an AI Factory is easy; keeping it running efficiently at scale is where most enterprises stumble. With GPU costs soaring and AI pipelines becoming more complex, visibility isn’t just a ‘nice to have’—it’s the difference between a successful deployment and an expensive science project.
As enterprises shift from “let’s see if this works” to “this has to work 24/7,” the underlying infrastructure gets messy. Between hybrid cloud silos and the massive cost of NVIDIA GPUs, most teams are winging it. At Nutanix .NEXT 2026, Virtana is showing you how to turn the lights on, linking AI workload behavior to the underlying platform health so you can run AI 24/7 with confidence. Set time to meet with us at .NEXT.
Virtana AI Factory Observability (AIFO) is a part of the Virtana Platform, a unified observability and optimization foundation that connects infrastructure signals to application and AI outcomes across hybrid environments.
Find Virtana in the AI Pavillion at the .NEXT Solutions Expo. What you’ll see:
- Unified Observability: One view across Nutanix AI pipelines, Kubernetes, infrastructure, and NVIDIA GPUs—no tool-hopping.
- Contextual Correlation: Automatically connect model/pipeline performance to cluster, storage, network, and GPU health.
- No More Silos: The same operational view whether training on-prem (AHV) or running inference in the cloud.
The Reality Check: Is Your AI Actually Productive?
A major theme at .NEXT 2026 will be the evolution of Nutanix Enterprise AI (NAI) as a foundation for enterprise-grade AI factories — supporting model development, deployment, governance, and lifecycle management across hybrid environments.
At the event, Virtana will demonstrate how AI Factory Observability (AIFO) integrates with NAI to deliver:
- End-to-end visibility across AI pipelines, Kubernetes clusters, and infrastructure
- Correlation between model performance and platform health
- Operational insights for training, fine-tuning, and inference workloads
- Unified monitoring across on-prem and cloud-based NAI deployments
By aligning AIFO with Nutanix Enterprise AI, Virtana’s deepest and broadest observability enables platform, infrastructure, and data science teams to operate AI environments with shared context and measurable outcomes.
GPUs Are Too Expensive to Sit Idle
High-performance AI depends on reliable, efficiently utilized GPUs.
At .NEXT 2026, Virtana will highlight advanced GPU observability capabilities designed for NVIDIA-based AI stacks, including:
- Real-time GPU telemetry — utilization, memory, power, temperature, and health
- Idle and under-utilized GPU detection to improve ROI
- Workload-to-GPU correlation for training and inference jobs
- Early detection of thermal, power, and reliability issues
- Performance analysis for multi-node, multi-GPU workloads
This integration helps enterprises ensure that expensive GPU resources are continuously optimized and aligned with business priorities.
Showcasing A Unified View: From Infrastructure to AI Outcomes
A key focus of Virtana’s .NEXT 2026 presence will be demonstrating how AIFO delivers a single, unified operational view across:
- Nutanix AHV and hybrid infrastructure
- Kubernetes and AI orchestration platforms
- NVIDIA GPU clusters
- Nutanix AI pipelines and endpoints
- Distributed training and inference workflows
Through live demos and use-case walkthroughs, Virtana will show how teams can move from fragmented monitoring tools to a cohesive AI operations platform that supports proactive management and continuous optimization.
Built for shared ownership: Virtana brings platform engineering, infrastructure ops, and data science teams into the same operational context, so AI services don’t fail in the seams between tools and teams.
Supporting the AI Factory Lifecycle
Virtana’s vision for AI Factory Observability goes beyond point-in-time monitoring. At .NEXT 2026, Virtana will outline how AIFO supports the full AI lifecycle on Nutanix platforms:
1. Plan & Provision
Forecast GPU demand and validate infrastructure readiness.
2. Build & Train
Monitor training efficiency and detect bottlenecks early.
3. Deploy & Infer
Ensure consistent performance for production AI services.
4. Optimize & Scale
Continuously improve utilization, cost efficiency, and reliability.
This lifecycle-driven approach helps enterprises move faster while maintaining operational discipline.
Measurable Business Outcomes for the Whole Team
Through its integration with Nutanix Enterprise AI and NVIDIA GPUs, Virtana AIFO is designed to help organizations achieve tangible results, including:
- Higher GPU utilization and reduced infrastructure waste
- Faster troubleshooting and incident resolution
- Improved SLA compliance for AI services
- Predictable capacity planning
- Lower operational risk and cost
What that means for you and your team:
- Platform Engineers can stop worrying about thermal throttling.
- Data Scientists get consistent performance for their inference models.
- CFOs see the actual utilization of that $2M NVIDIA cluster.
These outcomes are critical as AI becomes embedded into core business processes.
Looking Ahead: Building Confident AI Operations
At Nutanix .NEXT 2026, Virtana will reinforce its commitment to enabling reliable, scalable, and cost-effective AI operations. By combining deep integration with Nutanix Enterprise AI and advanced observability for NVIDIA GPU infrastructure, AIFO empowers enterprises to operate AI factories with confidence and precision.
As organizations move from AI experimentation to enterprise-wide deployment, Virtana’s vision is clear: deliver the intelligence, transparency, and control needed to turn AI investment into sustained business value.
Join Virtana at Nutanix .NEXT 2026 to see how AI Factory Observability is shaping the future of enterprise AI operations.
Meeta Lalwani
Senior Director – Product Management
