*1.Where are you in your AI journey?(Required.)

Not started

Experimenting / pilots

Early production workloads

Scaling AI across teams

*2.What infrastructure environments support your AI workloads today or are expected to? (Select all that apply)(Required.)

Nutanix

Public cloud (AWS, Azure, GCP)

Kubernetes / OpenShift platforms

Traditional virtualization (e.g., VMware)

Dedicated GPU clusters

Not currently running AI workloads

*3.Your AI infrastructure is best described as:(Required.)

Well-architected and standardized

Evolving with a defined approach

Built across multiple teams and tools

Assembled as needed per use case

*4.What is the biggest constraint to scaling AI workloads?(Required.)

GPU availability / cost

Data pipeline / storage performance

Network performance

Orchestration (Kubernetes / scheduling)

Operational complexity

*5.When working with or evaluating AI workloads, how clear is the root cause of performance issues?(Required.)

Immediately clear

Usually identifiable with effort

Often unclear without deep investigation

Rarely clear

*6.Based on your experience or expectations, AI workload performance is:(Required.)

Highly predictable

Somewhat predictable

Frequently varies

Unpredictable

*7.What is hardest about operating AI infrastructure today (or expected to be hardest)?(Required.)

Managing GPU cost / utilization

Understanding system-wide dependencies

Troubleshooting performance issues

Scaling reliably

Coordinating across teams

*8.How do teams typically determine what’s impacting AI performance?(Required.)

Unified, end-to-end system view

Correlated signals across tools

Multiple tools analyzed separately

Based on experience and investigation

*9.Which statement best reflects your current or expected AI operations?(Required.)

We have a clear, shared understanding of system behavior

We understand most layers, but not end-to-end

Different teams see different parts of the system

We piece things together during incidents

*10.As AI workloads grow, what is becoming harder to manage?(Required.)

Cost predictability

Performance consistency

System-wide visibility

Operational complexity

Demographics

*11.What is your role?(Required.)

Infrastructure / Platform Engineering

DevOps / Cloud

IT Operations

Architecture (Enterprise / Solutions)

Executive (CIO, VP, Director)

Data / AI / ML Engineering

*12.Your seniority:(Required.)

Executive

VP

Director

Manager

Individual contributor

*13.What is the size of your environment?(Required.)

<100 VMs

100–1,000 VMs

1,000–10,000 VMs

10,000+ VMs

*14.What is your work email address? (For raffle purposes)(Required.)

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