VCF 9.1: The Secure, Cost-Effective Private Cloud Platform for Production AI
What does it take to run production AI without runaway public cloud costs? This blog post introduces VMware Cloud Foundation 9.1, Broadcom's latest private cloud platform release, built to run AI, containerized, and traditional workloads securely and cost-effectively under a unified control plane. Read the blog to see how Derive Technologies can help you put VCF 9.1 to work in your environment.
What is VMware Cloud Foundation (VCF) 9.1 designed to do for production AI?
VMware Cloud Foundation (VCF) 9.1 is Broadcom’s latest release of its private cloud platform, built to help enterprises run production AI, modern apps, and traditional workloads under a single control plane on infrastructure they own and govern.
It is specifically engineered for three pressures most IT teams are facing in 2026:
- AI demand: AI is being embedded into everyday applications. IDC forecasts worldwide AI spending will grow at a 31.9% CAGR through 2029, reaching $1.3 trillion and exceeding 26% of total worldwide IT spending.
- Geopolitics and sovereignty: Data sovereignty rules, export controls on accelerators, and regional compliance requirements make workload location a board-level concern. Relying only on public cloud is increasingly risky.
- Budget compression: Many organizations are expected to fund AI from flat or shrinking budgets, so infrastructure efficiency becomes critical.
VCF 9.1 responds by focusing on lowering cost per workload and simplifying operations at scale:
- Cost efficiency for dense workloads:
- Enhanced NVMe Memory Tiering extends effective memory pools by tiering DRAM and NVMe, which is especially useful for memory-bound AI and database workloads.
- Extended vSAN Dedup and Compression reduces cost per usable terabyte.
- Topology Aware Scheduling places workloads with NUMA and accelerator locality in mind, improving performance for GPU and AI pipelines.
- Ubuntu OS Enterprise Support broadens the supported workload ecosystem without adding operational overhead.
- Operational scale and automation:
- Real-Time Operational Observability turns telemetry into actionable insights.
- Increased VMware vSphere Kubernetes Service (VKS) scale raises the ceiling for Kubernetes clusters.
- vSphere Elastic Provisioning enables zero-touch fleet expansion.
- Expanded Fleet Size and Upgrade Scale lets a single VCF instance manage larger estates with fewer maintenance windows.
The net result is more workloads per rack, fewer operators per thousand workloads, and a measurable reduction in cost-to-serve, while keeping AI and data under enterprise control.
How does VCF 9.1 support AI, containers, and traditional apps on one platform?
VCF 9.1 is built to deliver VMs, containers, AI services, and data services with equal fluency, so you can move toward a single operating model instead of managing separate stacks.
Key capabilities that enable this include:
- Faster provisioning for VMs and Kubernetes:
- VKS and VM Fast-Deploy shorten time-to-running for both Kubernetes clusters and virtual machines.
- Simplified Container-as-a-Service turns VMware vSphere Kubernetes Service (VKS) into a self-service surface for application teams, reducing friction between platform and dev teams.
- Integrated data and storage services:
- Native Object Storage (tech preview in 9.1.x) brings S3-compatible storage directly into the platform.
- Tanzu Marketplace integration provides a curated path to certified middleware and data services.
- SQL Server DBaaS elevates Microsoft SQL Server to a first-class, managed database service within the private cloud control plane.
- AI-specific visibility and control:
- Private AI Model and GPU Metrics expose utilization, memory pressure, and model-level visibility on the same console used for the rest of the estate.
- Live Application Stack Blueprints let teams version and redeploy entire application topologies as code, from legacy three-tier apps to RAG pipelines on the latest AMD GPUs.
For your teams, this means:
- One platform to manage legacy applications, containerized microservices, and AI pipelines.
- Consistent governance and security policies across all workload types.
- Faster delivery for new services, since infrastructure and data services are available through a common control plane.
What security, resilience, and ecosystem benefits does VCF 9.1 provide?
VCF 9.1 treats resilience, security, and ecosystem integration as core architectural properties, not add-ons. This is especially relevant when you are running sensitive data and high-value AI models and need security by design.
Security and resilience
- Ransomware and disaster recovery:
- vSAN for Recovery and On-prem Ransomware Recovery provide a sovereign, in-platform path to recover from destructive attacks without relying on external escrow.
- CrowdStrike EDR integration for Ransomware Recovery adds another option for endpoint detection in the recovery workflow.
- Encryption and patching:
- Encrypted vMotion with Intel QAT offloads cryptography to dedicated silicon, removing much of the historical performance tax of end-to-end encryption in motion.
- Live Patching for TPM-Enabled Hosts reduces unplanned downtime by allowing security updates without taking hosts offline.
- Compliance and lateral security:
- Continuous Compliance Enforcement reimagines compliance as a runtime guarantee rather than a quarterly audit event.
- Self-Service Lateral Security and Automated Load Balancing put micro-segmentation and traffic management in application teams’ hands, with central guardrails.
Ecosystem and hardware/network integration
- GPU and accelerator support:
- Enhanced DirectPath I/O for the latest AMD GPUs delivers near-bare-metal accelerator performance for modern AI workloads.
- Networking across vendors:
- Unified EVPN with Arista, Cisco, and SONiC provides a consistent overlay fabric across three major data center networking stacks, including the open-source SONiC option.
- This gives network teams one operating model regardless of which switch vendor is in which rack, and helps shorten the time to onboard new sites or integrate acquired environments.
- Reference architectures and upgrades:
- VKS Reference Architectures with cloud-native ISVs offer validated starting points for platform teams.
- Customers on VCF 9.0 have a supported in-place upgrade path to 9.1, guided by the VCF 9.1 Upgrade Guide and compatibility matrix.
- Organizations earlier in their journey can use the VCF 9.1 Reference Architecture library for validated AI, container, and traditional workload designs.
Together, these capabilities help you operate a secure, sovereign private cloud that can host AI, modern, and traditional workloads while integrating with your existing hardware, fabric, and tooling choices.


