The 12 Days of VMware Private AI: A Festive Learning Journey into VCF Features
Ho ho ho, tech enthusiasts! ‘Tis the season to deck the halls with GPUs and LLMs. In this holiday-themed blog series, we’re reimagining the classic “12 Days of Christmas” carol as a structured learning adventure into VMware Private AI Foundation with NVIDIA, built on VMware Cloud Foundation (VCF) 9.0. Whether you’re a virtualization veteran or an AI newbie, these 12 daily tasks will guide you from foundational knowledge to hands-on deployment in a home lab.
Each “day” includes a learning objective, recommended resources (like docs, blogs, and videos), and a simple activity. We’ll start with theory on key features like supported GPUs, LLMs, and resource requirements, then shift to practical setup, installation, and advanced operations like vMotion for GPU workloads. By Day 12, you’ll have a working Private AI environment—perfect for experimenting with generative AI in a private cloud.
Grab your eggnog, fire up your browser, and let’s get merry with VMware!
On the First Day of Christmas, My VCF Gave to Me: Understanding Supported GPUs
Kick off your journey by diving into the GPUs that power VMware Private AI. Learn which NVIDIA models are certified, why they’re ideal for AI workloads, and how they integrate with VCF for accelerated computing.
- Activity: Read the overview docs and note three key GPU models (e.g., NVIDIA A100, H100, or L40S) and their use cases for inference or training.
- Resources:
- VMware Private AI Foundation with NVIDIA Overview: Explore hardware compatibility and accelerated computing features.
- Blog: “Unleashing the Power of Private AI” for innovations in GPU support.
- Video: “VMware Private AI Foundation Capabilities and Features” (YouTube, ~10 min).
On the Second Day of Christmas, My VCF Gave to Me: GPU Virtualization Techniques
Build on Day 1 by exploring advanced GPU sharing in VCF, like vGPU (virtual GPU) for multi-tenancy and MIG (Multi-Instance GPU) for partitioning resources.
- Activity: Watch a video demo and sketch a simple diagram of how vGPU enables multiple VMs to share a single physical GPU without performance hits.
- Resources:
- Docs: “Configure vGPU-Based VM Classes for AI Workloads” in VCF 9.0.
- Blog: “VMware Private AI Foundation with NVIDIA on HGX Servers” covering GPU sharing.
- VMware Cloud Foundation Product Page: Section on GPU virtualization with NVIDIA AI Enterprise.
On the Third Day of Christmas, My VCF Gave to Me: Supported LLMs and AI Models
Shift to software: Discover the Large Language Models (LLMs) and AI frameworks supported in Private AI, including integrations with NVIDIA AI Enterprise for models like Llama or GPT variants.
| Category | Model Examples (commonly available in the catalog) |
|---|---|
| Open-source LLMs | Meta Llama 3.1 8B/70B/405B, Llama 3.2 1B/3B/11B/90B, Mistral 7B, Mixtral 8x7B/8x22B, Gemma 2 9B/27B, Phi-3 Mini/Medium, Qwen 2 7B/72B |
| Multimodal | Llama 3.2 Vision 11B/90B, Pixtral 12B, Florence-2, NV-Llama-3.1-8B-Vision |
| Embedding models | NVIDIA Embeddings (NV-EmbedQA), Snowflake Arctic Embed, BGE-M3 |
| Reranking / Routing | NVIDIA Rerankers, Jina Reranker |
| Upcoming / Recently added | DeepSeek-R1, Qwen-2.5, Nemotron-4 340B (quantized), Grok-1.5 (if licensed) |
- Activity: List five supported LLMs or model types (e.g., via Model Store and Runtime) and think about their enterprise applications, like chatbots or data analysis.
- Resources:
- Release Notes: VMware Private AI Foundation 9.0.x, highlighting AI-centric features like Model Store and Vector Databases.
- Blog: “Unleashing the Power of Private AI” on Model Governance and Runtime.
- Guide: “VMware Private AI Foundation with NVIDIA Guide” for model deployment workflows.
On the Fourth Day of Christmas, My VCF Gave to Me: Compute Resource Requirements
Delve into the compute needs for AI workloads in VCF, including CPU scaling, host configurations, and how they pair with GPUs for optimal performance.
- Activity: Calculate sample compute requirements for a small AI inference setup (e.g., based on host specs) using provided formulas from the docs.
- Resources:
- LLM System Requirements: How Much GPU RAM Do You Need? (Plus CPU-Only & Mixed Memory Options for Running Models).
- Release Notes: VCF 9.0, covering performance advancements.
- Blog: “What’s New in VMware Cloud Foundation 9.0” on enterprise-scale compute.
On the Fifth Day of Christmas, My VCF Gave to Me: Memory Resource Optimization
Explore memory configurations for AI, including high-bandwidth memory on GPUs, RAM allocation for VMs, and best practices for handling large models.
- Activity: Review memory profiles and identify how VCF 9.0 enhancements (like for 80GB+ vGPUs) improve efficiency.
- Resources:
- Blog: “Enhanced vMotion for vGPU VMs in VCF 9.0” touching on high-memory profiles.
- Docs: Deployment guide for GPU-accelerated domains.
- Vision Article: “Examining the VMware Private AI Foundation” on cost-optimized resources.
On the Sixth Day of Christmas, My VCF Gave to Me: Networking for AI Workloads
Learn about networking setups in Private AI, including high-speed interconnects, vMotion networks, and integration for data-intensive AI tasks.
- Activity: Map out a basic network topology for a VCF AI cluster, noting requirements for NFS, iSCSI, and vMotion.
- Resources:
- Deployment Docs: “Deploy a GPU-Accelerated Workload Domain” with network pool setup.
- Blog: “What’s New in VCF 9.0” on operations and networking improvements.
On the Seventh Day of Christmas, My VCF Gave to Me: Storage and Data Management
Cover storage features like vSAN for AI data, vector databases, and data indexing for efficient retrieval in LLMs.
- Activity: Research how vector DBs integrate and plan storage for a sample dataset.
- Resources:
- Guide PDF: “VMware Private AI Foundation with NVIDIA Guide” on storage components.
- Blog: “Private AI on HGX Servers” for vector DB and data features.
On the Eighth Day of Christmas, My VCF Gave to Me: Security and Compliance Basics
Understand Private AI’s security model, including data privacy, model governance, and compliance tools to keep your AI deployments secure.
- Activity: Identify three security best practices (e.g., self-service automation with governance).
- Resources:
- Release Notes: VCF 9.0 on security enhancements.
- Blog: “VCF 9 Ushers In New Support Model” touching on secure operations.
On the Ninth Day of Christmas, My VCF Gave to Me: Home Lab Hardware Setup with GPU
Transition to hands-on: Assemble your home lab hardware, focusing on adding a compatible NVIDIA GPU to a single server or nested environment.
- Activity: Inventory your hardware and install a GPU, following lab guides.
- Resources:
- Blog: “VMware GPU Homelab: Part 1 – Introduction”.
- Guide: “Build a VMware Cloud Foundation Lab on a Single Server”.
- Video: “VCF Lab Series – Part 5” for setup tips.
On the Tenth Day of Christmas, My VCF Gave to Me: Obtaining Advantage Home Lab Licenses
Secure your licenses for a non-production lab, including VMUG Advantage perks for VCF and vSphere if you’re certified.
- Activity: Check eligibility, download licenses, and apply them to your setup.
- Resources:
- Guide: “VMUG Advantage Home Lab License Guide”.
- Blog: “Free Home-Lab Licenses for VMware Certified Professionals”.
- VMUG Site: Membership details for licenses.
On the Eleventh Day of Christmas, My VCF Gave to Me: Installing VCF 9.0
Install VMware Cloud Foundation 9.0 in your home lab, configuring the base for Private AI.
- Activity: Follow the step-by-step installation, including SDDC Manager and vSAN setup.
- Resources:
- Blog: “My VMware Cloud Foundation 9.0.1 Home Lab Build”.
- Guide: “Building a Home Lab for VCF Environment”.
- Release Notes: VCF 9.0 for installation details.
On the Twelfth Day of Christmas, My VCF Gave to Me: vMotioning a GPU Workload
Cap it off with live migration: Deploy a sample GPU-accelerated AI workload and vMotion it between hosts without downtime.
- Activity: Create a vGPU VM, run an LLM inference task, and perform a vMotion—celebrate your Private AI mastery!
- Resources:
- Blog: “Enhanced vMotion for vGPU VMs in VCF 9.0”.
- Article: “How to Migrate Running GPU Workloads in VMware Private Cloud”.
- Tech Story: “How VMware’s vSphere Performs Live Migration on AI Workloads”.
