Theme
Private AI Foundation
Notes on the infrastructure side of private AI: GPU-enabled VCF, Kubernetes, NSX, data locality, model placement, and the operational realities of enterprise AI platforms.
PAIF Part 3: In-Lab LLMs and the Output-to-Action Firewall
Private AI becomes operational when the model is not trusted to act directly. The useful pattern is an in-lab model, a structured proposal, a policy gate, and an execution path that already has controls.
VCF 9.1 Rebuild: DNS and FQDNs Were the Real Dependency
A failed VCF 9.1 registration path came down to a basic dependency: the names in the bring-up spec did not resolve exactly as the platform expected.
Designing PAIF: A Reference Architecture for Tier 3 Private AI
A practical design for private knowledge, local processing, Tier 3 private question answering, Kubernetes-first AI services, and hybrid routing when policy allows.
Building a Private AI Platform in VMware Cloud Foundation - Part 1
Why private AI infrastructure is not about replacing every public model, and why the real discussion starts with control, data locality, GPUs, and operations.
VCF 9.0 vs 9.1: IP and DNS Planning for Internal Components
A planning worksheet model for internal VCF endpoints: appliances, services, Edges, Kubernetes, workload domains, IP addresses, FQDNs, forward DNS, and reverse DNS.
VCF 9.1 Depot Setup: From Download Tokens to Activation Codes
A practical look at how VCF repository setup changes from the 9.0 download-token model to 9.1 Software Depot Registration, Download Service ID, and activation-code workflows.