DRAM problems become apparent
NVMe memory tiering was introduced in VCF 9.0 and was successful. The performance numbers are improving, the TCO story is real, and customers are interested. But it requires a reboot to enable it, and it relies on a hardware RAID controller, so implementation is slower than it should be. Too much friction for a feature that is supposed to reduce friction.
VCF 9.1 fixes this. It offers reboot-free startup, software-based mirroring that eliminates RAID controller dependency, and smarter cold page detection. The result is a lower server TCO of up to 40 percent.
Why this is important
DRAM is the single most expensive line item on a server order. In a supply chain environment where hardware costs are increasing and lead times are getting longer, anything that reduces the cost per server while maintaining application performance is worth pursuing. This is structural, not incremental. I firmly believe this feature will become as ubiquitous in hypervisors as deduplication in enterprise storage systems.
Storage becomes real. Finally.
Talking about deduplication. vSAN global deduplication and compression enhancements were implemented in GA in 9.1, and for the first time, they work in conjunction with data-at-rest encryption.
This is the missing piece. No enterprise security team likes turning off encryption to gain dedupe savings. Now they don’t have to choose. Up to 39 percent storage TCO reduction, with encryption intact. It’s a conversation that usually ends with “not yet.” Now it starts with “when.”
Kubernetes develops on VCF
Kubernetes improvements are significant on paper with up to 46 percent lower operational costs, faster deployment, and larger cluster scale. The numbers matter.
But the real story is accessibility. VCF makes container management more approachable for the same operations teams that run VMs today. If your biggest barrier to Kubernetes isn’t technology, it’s talent (and for most companies, it is), then this is the kind of platform shift that changes the adoption equation. AI workloads require this change so the use and orchestration of containers becomes more commonplace. It’s updates like this that really make a difference.
Security is extended to where it is needed
Distributed IDS/IPS now extends to Kubernetes workloads for the first time with 9Tbps inspection throughput and live patching in 80% of use cases, including TPM-enabled hosts.
This is what zero trust at the infrastructure layer looks like: not slide decks, not checkboxes, but platform capabilities. AI workloads running in containers require the same security posture as VMs. Now they can get it.
The main differences between VCF 9.0 and VCF 9.1
VCF 9: Foundation (Released June 2025)
- Integrated operations — Single management interface, Quick start deployment, one-click patching.
- VMs and containers and AI — original VKS; running Kubernetes alongside VMs as a first-class workload.
- NVMe memory level — NVMe as secondary memory tier; Up to 38% lower server TCO by reducing DRAM dependency.
- Improved data path — Up to 3x faster network switching; kernel optimization and optional DPU offloading.
- AI-enabled infrastructure — GPU vMotion, NVIDIA Blackwell support, personal AI services are included at no additional cost.
- Zero trust security — Confidential computing, vDefend micro-segmentation, IDS/IPS, ransomware recovery.
- Fleet management — Centralized lifecycle, fleet level upgrades, license portability across on-prem/cloud/edge.
What’s new in VCF 9.1 (Released May 2026)
- NVMe tier improved — Reboot-free, no RAID controller, smarter cold page detection; Server TCO is up to 40% lower.
- vSAN global dedupe GA — Generally available with data encryption at rest; storage TCO reduction of up to 39%.
- Elastic provisioning — Parallel imaging, automatic host discovery, pull-based edge orchestration.
- Kubernetes at scale — 6x cluster scale, 75% faster deployment, 75% shorter version upgrades (vs preview); up to 46% lower operating costs K8.
- 4x faster cluster upgrade — Fleet size reaches 5,000 hosts (2x increase); asynchronous and direct patching.
- No trust in Kubernetes — IDS/IPS for K8s AI workloads (9 Tbps); immediate patching in 80% of cases included. TPM host.
- Unified AI platform — Inference and AI agents on one layer; AMD and NVIDIA GPU support; multi-tenant isolation.
- Network – Avi LB and vDefend replace HW tools; EVPN-VXLAN fabric interop; automatic inter-VPC firewall.
Major efficiency improvements — 9.0 versus 9.1
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.