VMware Cloud Foundation isn’t just a platform for traditional virtual machines anymore. With VMware Kubernetes Service (VKS), Data Services Manager, and Private AI Foundation, VCF is now a full platform for cloud-native applications, managed databases, and GPU-accelerated AI workloads, all running alongside your existing VM estate. ClearBridge’s Modern Apps & Data practice helps organizations take advantage of that, rather than running VCF purely as legacy VM infrastructure while cloud-native workloads live elsewhere.
What’s Included
VKS cluster design and onboarding
Standing up Kubernetes on VCF is more than enabling a feature — it requires thoughtful cluster architecture, networking integration with NSX, and a clear onboarding path for development teams. We design VKS environments that developers actually want to use.
Database services enablement
Data Services Manager brings managed database provisioning to VCF, similar to what teams expect from public cloud DBaaS offerings. We help organizations enable and govern this capability so application teams can self-serve databases without infrastructure becoming a bottleneck.
GPU and Private AI Foundation
As organizations bring AI workloads in-house for data sovereignty and cost reasons, GPU-enabled infrastructure and Private AI Foundation give VCF environments a credible on-premises AI platform. We help design and deploy this capability for real workloads, not just proofs of concept.
Developer platform integration
None of this matters if developers can’t consume it easily. We integrate VKS, database services, and AI infrastructure into developer-facing workflows so that modern application platforms on VCF feel like a platform, not a collection of disconnected VMware products.
Why It Matters
Organizations that don’t modernize their VCF environment for cloud-native and AI workloads often end up running two parallel infrastructure strategies: VCF for “traditional” IT, and public cloud or shadow infrastructure for anything modern. That split creates duplicated cost, inconsistent security posture, and friction between platform and development teams.
Bringing Kubernetes, managed data services, and AI infrastructure directly onto VCF, under the same operational, security, and automation model as the rest of the environment — closes that gap. It also directly supports data residency and sovereignty requirements that make public cloud AI adoption difficult for regulated organizations.
Proven in the Field
This is an area where ClearBridge has hands-on, repeated delivery experience. In Accelerating Cloud-Native Modernization with VMware VKS on VCF, our team helped modernize cloud-native workloads by deploying a Kubernetes platform directly on VCF. We followed a similar path in Modernizing Cloud Operations with VMware VKS on VCF 9, transitioning a customer from a legacy container platform to a streamlined, secure, self-service Kubernetes environment on VCF 9.
ClearBridge has also supported the DevOps and automation layer that makes Kubernetes platforms usable day-to-day. Kubernetes Platform Engineering & DevOps Automation shows our work strengthening a Kubernetes platform and DevOps automation within an HCM technology environment, the kind of engineering discipline that makes modern application platforms sustainable, not just functional at launch.
Where to Start
If your organization is running Kubernetes, databases, or AI workloads outside of VCF because the platform hasn’t been enabled for them yet, ClearBridge’s Modern Apps & Data practice can help you bring those workloads home — with the same security, automation, and operational model as the rest of your environment. See the full ClearBridge VCF Delivery Portfolio for how this connects to infrastructure, automation, and operations, or browse more of our delivery work in the Case Studies Archive.
Ready to modernize what runs on your VCF platform? Reach out to ClearBridge to start the conversation.
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