ai

Introduction VCF Automation 9.x is easy to misunderstand if your mental model was built around vRealize Automation or Aria Automation. The familiar product lineage is still present, but the platform now exposes two materially different consumption paths. One path preserves the established VM-centric automation model. The other places organizations, projects, vSphere Namespaces, and Supervisor-backed services

Introduction Most enterprises would never allow an engineer to download an unknown executable from the internet and place it directly on a production server. Mature software delivery processes use source control, artifact repositories, vulnerability scanning, build records, approvals, version pinning, and rollback procedures because software has a supply chain. AI models have one too. A

Introduction A GPU cluster does not know which product launch is contractually committed, which research experiment can wait until tomorrow, or which inference endpoint supports a revenue-producing application. Kubernetes sees pods, resource requests, labels, and scheduling constraints. The business sees customers, deadlines, budgets, risk, and service commitments. That gap is where many shared GPU platforms

TL;DR The decision to stay on VMware Cloud Foundation or replatform should not be reduced to a licensing reaction, a hypervisor feature comparison, or a vendor preference. It is a private cloud operating-model decision involving workload compatibility, staff capability, migration risk, ecosystem dependencies, automation maturity, lifecycle economics, and future exit complexity. For many enterprises, the