Nutanix NCP-AI study guide
Nutanix NCP-AI · Work through your exam, one topic at a time.
The Nutanix Certified Professional - AI (NCP-AI) is a professional-level certification for infrastructure engineers, platform architects, and virtualization specialists who design, deploy, and operate AI workloads on Nutanix infrastructure. It validates that you can reason about the full stack rather than a single product: the AI architecture and its components, GPU virtualization and workload placement, AI-ready deployment patterns such as GPT-in-a-Box, the data services layer (storage, Objects, and databases), Kubernetes-based containerized AI workloads through the Nutanix Kubernetes Platform, day-two operations and lifecycle management, and the security, governance, and multitenancy controls that surround shared GPU capacity. The Nutanix NCP-AI study guide has 7 sections and about 1,804 words.
01Nutanix AI Stack Architecture and Components
This domain tests whether you can place each AI capability in the correct Nutanix stack layer and select the right service for a workload, not merely name products. Nutanix Cloud Infrastructure (NCI): AOS distributed storage, AHV hypervisor, and the Prism Element/Prism Central management plane.
255 words, about 1 min02AI Workload Infrastructure and GPU Virtualization
This domain tests GPU consumption models on AHV and how to match training versus inference requirements to host and VM design. Passthrough: the entire physical GPU is assigned to one VM; simple and often fastest, but no sharing and limited mobility.
279 words, about 1 min03Nutanix GPT-in-a-Box and AI-Ready Deployment
GPT-in-a-Box is Nutanix's validated, on-premises AI-ready blueprint: NCI/AHV compute, NVIDIA GPUs, NKP Kubernetes, GPU Operator, and model-serving/MLOps tooling. The exam tests deployment prerequisites and the distinction between a blueprint and a product.
252 words, about 1 min04Data Services for AI: Storage, Objects, and Databases
AI pipelines have different data paths: shared training sets, high-throughput checkpoints, S3 data lakes, and transactional metadata. NCP-AI tests choosing the right Nutanix data service and protecting it.
269 words, about 1 min05Nutanix Kubernetes Platform and Containerized AI Workloads
NKP, formerly Nutanix Kubernetes Engine, provides lifecycle management for CNCF-conformant Kubernetes clusters from Prism Central. The exam focuses on GPU node pools, storage integration, and workload isolation.
267 words, about 1 min06Operations, Monitoring, and Lifecycle Management for AI Environments
AI environments add GPU health, driver compatibility, and capacity pressure to normal Nutanix operations. The exam tests monitoring, upgrades, and lifecycle discipline.
246 words, about 1 min07Security, Governance, and Multitenancy for AI
AI multiplies data sensitivity and shared-resource risk. NCP-AI tests isolation across network, identity, storage, and Kubernetes.
236 words, about 1 min