In short:
VCF 9.x is not the only necessary upgrade. For VMware customers, this is an opportunity to develop personalized AI more quickly using the infrastructure they had planned to deploy. Here’s what you need to know about memory levels and AI readiness.
Most companies have implemented AI in some form, and more and more are doing so want to to run it on their own infrastructure. But most are not ready….
A10 Networks’ AI Infrastructure Report found that 53 percent of organizations are only “somewhat confident” in their infrastructure’s ability to support future AI needs.
The result is a widening gap between AI ambition and AI infrastructure, and for most organizations, “deployed” still means a Copilot subscription or ChatGPT enterprise license, not a private LLM run on proprietary data.
Closing the gap typically requires budget cycles, infrastructure decisions, and executive sponsorship. And in the next 18 months, nearly every VMware customer will have all three.
The VCF 9.x elephant in the room
VMware vSphere 8 reaches end of general support on October 11, 2027. After the EOL date, technical guidance continues for another two years, but new patches, security updates, and hardware certifications stop. So, what’s next? VMware Cloud Foundation (VCF) 9.x has been generally available since June 17, 2025, and is the upgrade path forward.
If you’re ready to make a change, technical migration can be done easily. But licensing changes are a more complex discussion. vSphere 8 is the last version that can be licensed in perpetuity, which means moving to VCF 9.x also means moving to a VMware by Broadcom subscription. There are also hardware considerations. VCF 9.x has higher technical requirements than vSphere 8 and most current environments require a compute refresh to run well.
But let’s stop for a moment here. Two features in VCF 9.x are worth understanding before discussing any budget, as they change the value of the upgrade itself.
NVMe memory level
The first is the NVMe memory tier, which is becoming important in a market where memory supply is limited and prices are rising. VCF 9.x Our team of certified professionals and technical experts can help you determine how and where to utilize memory tiers.
VMware Private AI Foundation with NVIDIA
The second is VMware Private AI Foundation with NVIDIA, which ships with VCF 9.x. This provides customers with a secure environment to deploy and run LLM on their own infrastructure, with NVIDIA NeMo as the underlying framework and support. For regulated industries, NVIDIA Enterprise AI containers are now available in configurations that meet FedRAMP High and DoD IL5 requirements.
The private AI that is being developed most companies are not yet aware of
Building the infrastructure to run private AI workloads is where most enterprise AI programs stall. The costs are real, the talent is scarce, and the procurement cycles are long. So, organizations default to AI tools that don’t require infrastructure decisions, such as chat interfaces and vendor APIs.
VCF 9.x changes that calculus as the environment for personal AI comes with improvements that most VMware customers will already be making. By leveraging Personal AI Services (PAIS), teams can easily build secure, isolated environments with LLM, point them to internal data, run capture-augmented use cases, and see what works without separate infrastructure purchases or vendor relationships. From there, the path to production AI deployment becomes shorter and easier to understand, as platform decisions have already been made.
This does not make every workload a candidate for private AI, nor does it replace the work of identifying high-value use cases or building data pipelines to support them. But this removes one of the biggest obstacles to getting started.
How to think about VMware’s strategic planning for AI over the next 18 months
For organizations running VMware today, planning work falls into four groups:
- Inventory existing hardware and identify what will and will not meet VCF 9.x requirements. Find hardware requirements based on capacity and desired expansion.
- Model the impact of licensing based on new per-processor minimums and the shift from perpetual to subscription.
- Align hardware refreshes with compute, memory, and AI readiness needs.
- Identify two or three candidate workloads that can meaningfully test private AI within the first 90 days after migration.
SHI is building a complete VCF 9.
We’ve modeled the impact of the new Broadcom licenses across hundreds of VMware customer environments this quarter, meaning the per-core analysis isn’t theoretical. And for organizations looking to test private AI before undertaking a full VCF migration, we offer an alternative entry point via NVIDIA Spark devices that can run a functional LLM environment on a single device.
As a Dell Titanium Black partner, VMware Geo Partner of the Year 2024 (North America), VMware Technical Enablement/Support Partner of the Year 2024 (Americas), and NVIDIA Partner Network Rising Star Solution Provider Partner of the Year 2026, we are positioned to handle the financial picture and AI on-ramp as one project, not two.
Next steps for your VCF 9.x migration
Ready for your VCF 9.x journey? Order a VMware SHI Strategic Assessment to start the conversation today.
We know there are a lot of changes at VMware.
Find out why organizations like yours choose SHI as their VMware partner.
General Questions
What is VMware Cloud Foundation (VCF) 9.x?
VCF 9.x is VMware’s “full stack” for running a private cloud (compute, storage, networking, and management packaged together). If you’re using vSphere today, VCF 9.x is the general next step as vSphere 8 approaches end of general support in October 2027.
Why does the VCF 9.x migration create an “AI on-ramp”?
Because upgrades often come with hardware refreshes and platform changes that you need to run personal AI. Instead of creating a new “AI infrastructure project,” you can use VCF 9.x to set up a secure test environment and quickly prove multiple AI use cases.
What VCF 9.x capabilities are most important for AI readiness?
When you consider AI readiness, the two things that stand out the most are the NVMe memory tier (to reduce the amount of expensive DRAM you need) and VMware Private AI Foundation with NVIDIA (a packaged environment for privately testing LLM workloads).
What should we do first if we are planning a VCF 9.x upgrade?
- Take inventory of what you currently have and determine what doesn’t meet the requirements of VCF 9.x.
- Model licensing changes early (subscription shifts and minimums per processor).
- Refresh scope (compute, memory, storage — and GPU if personal AI is in scope). Align hardware refreshes with compute, memory, and AI readiness needs.
- Choose two or three pilot use cases to test (Experiment phase) so you can decide what to scale (Adoption phase). candidate workloads that can meaningfully test private AI within the first 90 days after migration.
How does SHI help with this (Imagine. Experiment. Adopt.)?
SHI helps the team Imagine right AI outcomes through use case discovery and readiness workshops, Test by validating prototypes in AI & Cyber Labs (often in 2-6 weeks using real data and integrations), and Take by implementing a proven approach into production that is equipped with security, governance, and compliance.
PakarPBN
A Private Blog Network (PBN) is a collection of websites that are controlled by a single individual or organization and used primarily to build backlinks to a “money site” in order to influence its ranking in search engines such as Google. The core idea behind a PBN is based on the importance of backlinks in Google’s ranking algorithm. Since Google views backlinks as signals of authority and trust, some website owners attempt to artificially create these signals through a controlled network of sites.
In a typical PBN setup, the owner acquires expired or aged domains that already have existing authority, backlinks, and history. These domains are rebuilt with new content and hosted separately, often using different IP addresses, hosting providers, themes, and ownership details to make them appear unrelated. Within the content published on these sites, links are strategically placed that point to the main website the owner wants to rank higher. By doing this, the owner attempts to pass link equity (also known as “link juice”) from the PBN sites to the target website.
The purpose of a PBN is to give the impression that the target website is naturally earning links from multiple independent sources. If done effectively, this can temporarily improve keyword rankings, increase organic visibility, and drive more traffic from search results.