Technology

Broadcom Inc. has announced the release of VMware Cloud Foundation (VCF) 9.1, a next-generation private cloud platform designed to enable secure, scalable and cost-efficient deployment of production AI workloads. The launch highlights the company’s focus on helping enterprises transition from experimental AI use cases to full-scale production environments while maintaining control over costs, data, and infrastructure.

The latest version of VCF introduces an AI- and Kubernetes-native private cloud architecture, supporting mixed compute environments across leading hardware providers such as AMD, Intel, and NVIDIA. This flexibility allows organisations to deploy both inference and emerging agentic AI applications with greater efficiency and hardware choice.

According to insights from Broadcom’s Private Cloud Outlook 2026 report, private cloud is increasingly becoming the preferred platform for production AI, with 56% of organisations already using or planning to use it for AI inferencing. In contrast, reliance on public cloud for such workloads has declined, reflecting growing concerns around cost predictability, data privacy, and regulatory compliance.

Cost efficiency and operational performance gains

VCF 9.1 delivers measurable improvements in infrastructure efficiency, including:

• Up to 40% reduction in server costs through intelligent memory optimisation
• Up to 39% lower storage total cost of ownership (TCO)
• Up to 46% reduction in Kubernetes operational costs
• 4x faster cluster upgrades and improved scalability

These enhancements allow enterprises to run more AI workloads on existing infrastructure, reducing the need for expensive hardware expansion amid global supply constraints.

Unified platform for AI and modern workloads

The platform integrates virtual machines, containers, and AI applications into a single environment, eliminating operational silos. It supports large-scale Kubernetes deployments, faster application rollouts, and seamless scaling, enabling businesses to accelerate AI adoption without increasing complexity.

Advanced capabilities such as AI observability tools, real-time performance metrics, and reusable deployment templates further streamline operations while ensuring governance and compliance across environments.

Built-in zero-trust security architecture

Security remains central to VCF 9.1, with the platform incorporating a zero-trust framework designed to protect AI models, data, and applications. Key features include:

• Continuous compliance monitoring and automated remediation
• Zero-downtime live patching for uninterrupted AI services
• Advanced threat detection and distributed security controls
• On-premises ransomware recovery with validation tools

These capabilities address growing enterprise concerns around data sovereignty, cybersecurity risks, and regulatory requirements in AI deployments.

Driving the future of private AI

Krish Prasad, Senior Vice President and General Manager of the VMware Cloud Foundation Division at Broadcom, said the platform is built to address three major enterprise challenges: data privacy, rising infrastructure costs, and readiness for agentic AI.

“With VCF 9.1, enterprises can deploy AI workloads on a unified platform that combines security, cost efficiency, and operational flexibility,” he noted.

As organisations increasingly move AI from experimentation to production, VCF 9.1 positions private cloud infrastructure as a strategic alternative to public cloud, offering greater control, improved performance, and long-term cost advantages.

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