A few months ago, I was working with a customer who was running critical workloads on VMware on-premises. They were already using AWS internally for a GenAI chatbot, but now they wanted to expand AI use cases to predict and remediate infrastructure issues, including agentic AI solutions.
The challenge? They didn’t want to rely on any public cloud due to data privacy and compliance concerns. They wanted to leverage their existing VMware on-premises infrastructure. At that time, they were running vSphere 8 and VCF 5.x, which had some limitations for AI workloads.
Enter VMware Private AI Foundation with NVIDIA in VCF 9. Suddenly, their vision for on-prem GenAI for IT operations became achievable.
What’s New in VCF 9 for Private AI?
VCF 9 introduces several game-changing features that make on-premises AI workloads practical and high-performing:
Direct GPU Access
With DirectPath I/O, VMs can directly access NVIDIA GPUs. This means AI workloads—like predictive infrastructure analysis—run faster with minimal latency, something that was harder to achieve on vSphere 8 and VCF 5.x.
NVIDIA HGX Platform Integration
VCF 9 integrates NVIDIA HGX with Blackwell GPUs and NVSwitch, providing high-throughput GPU-to-GPU communication. For our customer, this meant they could run complex GenAI models to analyze and predict infrastructure issues without overloading the system.
Built-in AI Services
- Model Store & Model Runtime: Simplifies management of AI models, including agentic AI solutions that can act autonomously.
- Pre-built Microservices & Blueprints: Enable rapid deployment of AI workflows for IT remediation, similar to what they were doing for the chatbot, but now fully on-premises.
vMotion for AI Workloads
VCF 9 allows near-zero downtime live migration of VMs running AI workloads. This means predictive AI models can continue running even during host maintenance—critical for always-on IT operations AI.
Private AI as a Standard Feature
VCF 9 makes Private AI services a standard part of the platform, enabling organizations to deploy AI safely on their own infrastructure while maintaining full control over sensitive data.
How This Customer Benefits
Before VCF 9, deploying GenAI workloads for predictive infrastructure management on-prem was complex and risky:
- GPU access was shared, limiting AI performance
- Deploying and updating AI models required manual effort
- Scaling workloads for predictive analytics was difficult
- Live migrations of AI workloads risked downtime
With VCF 9 Private AI Foundation, everything changed:
- High-performance AI: Direct GPU access + HGX platform allows real-time analysis.
- Automated lifecycle management: Model Store and Runtime manage updates, patches, and rollbacks automatically.
- Scalability: They can deploy additional AI models for IT remediation as needed.
- Zero downtime: vMotion ensures continuous operation even during infrastructure maintenance.
- Data privacy: AI runs fully on-premises, addressing compliance and security concerns.
In other words, the customer could now extend GenAI beyond chatbots to intelligent infrastructure management without touching public cloud services.
Real-World Use Case: Predictive IT Remediation
With VCF 9:
- AI models analyze metrics from VMware hosts, storage, and network devices in real-time.
- Predictive alerts detect potential issues before they impact workloads.
- Agentic AI models can take automated remediation actions, such as reallocating resources or restarting services.
- IT teams focus on strategy rather than firefighting, saving time and cost.
This was not feasible with vSphere 8 / VCF 5.x without complex scripts, third-party tools, or public cloud dependence.
vSphere 8/VCF 5.x vs VCF 9 for Private AI
| Aspect | vSphere 8 / VCF 5.x (Existing Setup) | VCF 9 Private AI Foundation with NVIDIA | Customer Perspective |
|---|---|---|---|
| AI Workload Performance | Shared GPU access, limited throughput, slower AI model training | DirectPath GPU access + NVIDIA HGX integration, high-performance AI training & inference | Faster insights, better SLA for AI-driven applications, improved ROI |
| AI Model Deployment & Management | Manual deployment, updates, patching, scaling | Built-in Model Store & Model Runtime, pre-built microservices & blueprints | Reduced operational overhead, fewer errors, shorter deployment cycles |
| Scaling AI Workloads | Complex scaling, manual configuration, limited GPU utilization | Easy horizontal & vertical scaling with optimized GPU allocation | Architects can plan growth efficiently, support multiple GenAI use cases |
| Live Migration / Downtime | vMotion has higher downtime for AI workloads | Near-zero downtime vMotion for AI workloads | Continuous operation, critical for predictive infrastructure & real-time AI |
| Public Cloud Dependency | AWS used for GenAI chatbots; risk of data exposure & recurring costs | Fully on-premises AI deployment | Reduced dependency on public cloud, improved data privacy, regulatory compliance |
| Cost & TCO | High operational costs due to manual processes, cloud subscription fees for AI workloads | Lower TCO: optimized GPU usage, automated AI lifecycle, reduced public cloud costs | Clear cost savings, faster ROI, budget-friendly AI expansion |
| Predictive & Agentic AI | Hard to deploy safely on-prem, relied on scripts or third-party tools | Fully integrated AI foundation capable of predictive & agentic AI | Enables next-gen AI solutions (e.g., predictive infrastructure, auto-remediation) |
| Decision-making for IT Leaders | Slow AI adoption, reliance on multiple platforms | Unified platform for on-prem AI & VMware workloads | Faster strategic decisions, less vendor dependency, simplified architecture planning |
In Nutshell,
- VCF 9 + NVIDIA Private AI enables high-performance GenAI on-premises
- Direct GPU access and HGX integration unlock real-time AI analytics
- Built-in AI services simplify deployment, updates, and scaling
- Near-zero downtime vMotion keeps AI models running continuously
- Fully on-premises deployment ensures data privacy and compliance
For enterprises exploring on-prem AI for IT operations, VCF 9 Private AI Foundation is no longer just an option—it’s a practical, secure, and scalable solution.
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