vCF (VMware Cloud Foundation)

TL;DR VMware Cloud Foundation 9.1 matters for private AI because it does not treat AI as a separate island. It pulls AI workloads into the same private cloud operating model many enterprises already use for virtual machines, Kubernetes, storage, networking, security, lifecycle, and operations. That is the strength of VMware’s approach, but it is also

Introduction The most common sizing question about VMware Cloud Foundation is still framed as a host-count question: How many ESX hosts are required before VCF can be deployed? That question is useful for checking a deployment prerequisite, but it is not sufficient for an architecture decision. A platform can satisfy a minimum host count and

VCF 9.1 creates a familiar operational trap: a platform team can complete a release-note review and still not be ready to upgrade. The reason is that support changes do not arrive as one clean class of event. Some capabilities remain functional but are deprecated. Some hardware operates under restricted support. Some components have already been

VMware Cloud Foundation 9.0 was the platform reset. It moved VCF beyond the idea of an integrated VMware software stack and toward a more complete private cloud operating model. Unified operations, governed self-service, VPC networking, Kubernetes, cost visibility, infrastructure automation, and API-driven consumption became central parts of the platform rather than adjacent capabilities. VMware Cloud

VMware vSphere Foundation and VMware Cloud Foundation share the same infrastructure DNA. Both are built around vSphere. Both can run enterprise virtual machines. Both include vSAN capacity, VMware vSphere Kubernetes Service, and VCF Operations capabilities. That shared foundation makes the comparison easy to get wrong. VVF 9.0 is not simply a smaller release of VCF,