Tag: vGPU
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Running GPU and AI Workloads on VKS (VKS Series, Part 14)
GPUs are where VKS stops being interchangeable with generic Kubernetes. Here is the vGPU VM class, the GPU Operator, and how VKS becomes the substrate for VMware Private AI.
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NVIDIA AI Enterprise Explained: What’s in the Suite, How It’s Licensed, and Whether It’s Worth It
A practitioner’s breakdown of what NVIDIA AI Enterprise actually bundles, how its per-GPU licensing lands on VMware vSphere, and when the subscription earns its keep versus when you can skip it.
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VMware Private AI Foundation Upgrade: Moving from VCF 9.0 to 9.1 Without Breaking Your GPUs (Private AI Series, Part 24)
A practical 9.0 to 9.1 upgrade runbook for VMware Private AI Foundation, plus a closing verdict on the platform after 24 parts. The order of operations, the vGPU driver branch trap, and host-by-host GPU domain remediation.
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Troubleshooting VMware Private AI Foundation: 7 Failures That Actually Bite (Private AI Series, Part 23)
The seven failures I hit most often on VMware Private AI Foundation with NVIDIA, from a dark GPU on the ESXi host to a NIM pod crashing on CUDA out of memory, with the real error strings and the checks that isolate each layer.
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GPU Monitoring with VCF Operations for VMware Private AI: The Signals That Actually Catch a Failing Workload (Private AI Series, Part 17)
VCF Operations gives you GPU dashboards out of the box, but the metric most teams trust is the one that lies. Here is what to watch on a Private AI Foundation estate, why GPU utilization misleads, and the hardware-health signals the default dashboards never surface.
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Deep Learning VMs in VMware Private AI Foundation: The Data Scientist Workbench (Private AI Series, Part 10)
What a Deep Learning VM in VMware Private AI Foundation actually is, how the image is built, the first-boot steps that quietly break deployments, and when to move off it to a VKS cluster.
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Installing the NVIDIA GPU Operator and vGPU Drivers for VMware Private AI Foundation (Private AI Series, Part 9)
A practical runbook for installing the NVIDIA GPU Operator and matching vGPU host and guest drivers on VMware Private AI Foundation, with the validation checks and version-skew traps that decide whether GPUs actually schedule.
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Prepare a GPU Workload Domain for VMware Private AI Foundation (Private AI Series, Part 8)
A field-tested, bottom-up procedure for standing up a GPU-accelerated workload domain on VCF 9.0 for Private AI Foundation: firmware, the vLCM vGPU driver, Shared Direct, a single-zone Supervisor, and the mistakes that actually bite.
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VMware Private AI Reference Architecture and Sizing: A Practical Blueprint (Private AI Series, Part 7)
How to size a VMware Private AI Foundation build the right way: two-domain design, choosing the deployment model, and working from workload back to GPU hosts and BOM on VCF 9.1.
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GPU Partitioning for VMware Private AI: Choosing Between vGPU, MIG and Passthrough (Private AI Series, Part 6)
Time-sliced vGPU, MIG-backed vGPU, GPU passthrough and the new ESXi 9 Update 1 hybrid mode each fit different Private AI workloads. Here is how to design the split, with a capability matrix and a reference topology.
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VMware Private AI Foundation Planning and Prerequisites: GPU Hosts, Drivers and Readiness (Private AI Series, Part 4)
A practitioner’s planning guide for VMware Private AI Foundation with NVIDIA on VCF 9: GPU host selection, the vGPU driver and GPU Operator interoperability matrix, sharing-mode choices, and the readiness checks that decide whether your first deployment lands clean.
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How to Deploy VMware Private AI Foundation with NVIDIA on VCF 9 (VCF 9 Series, Part 26)
A field-tested runbook for deploying VMware Private AI Foundation with NVIDIA on VCF 9: the two deployment paths, the three licenses you need, GPU host prep, the right sharing mode, and the guided workflow, plus the gotchas that stall bring-up.
Architect’s Toolkit
VMware Cloud Foundation
- VCF Documentation
- VCF 9 Planning & Preparation Workbook
- VCF Bill of Materials (BoM)
- VMware Compatibility Guide
- VMware Interoperability Matrix
- VMware Configuration Maximums
- VMware Ports & Protocols
- VMware Hands-on Labs
- RVTools Download
Nutanix
AI & Cloud-Native Platform
- AI Infra Sizing & Cost Calculator
- NVIDIA Build (Model Catalog)
- NVIDIA AI Enterprise Reference Architecture
- NVIDIA NIM Performance Benchmarking
- NVIDIA NGC Catalog
- NeMo Microservices Helm Chart
- Helm Charts Repository
- Hugging Face Models
Architecture & Design
About the Author
Dr Pranay Jha
Dr. Pranay Jha is a Cloud and AI Consultant with 18+ years of experience in hybrid cloud, virtualization, and enterprise infrastructure transformation. He specializes in VMware technologies, multi-cloud strategy, and Generative AI solutions. He holds a PhD in Computer Applications with research focused on Cloud and AI, has published multiple research papers, and has been a VMware vExpert since 2016 and a VMUG Community Leader.
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