Steep license increases since the Broadcom acquisition are accelerating a shift a lot of teams were already making: containerized, GitOps-run private clouds — and now local LLM inference on GPU-dense hardware from Dell and HPE.
Broadcom's acquisition of VMware rebuilt the commercial model around subscription bundles like VMware Cloud Foundation, priced on a per-core basis with a 16-core-per-processor minimum, and pushed customers toward packaged suites instead of à la carte purchasing. The result has been sticker shock: industry surveys put the share of organizations actively shrinking their VMware footprint in the high 80s percent, with some renewal quotes reported north of 1,000% over prior terms once minimum commitments and bundling are factored in.
Microservices and private cloud, not just cost control
The response isn't only a negotiation tactic. Platform teams are using the forced renewal conversation as cover to do work they wanted to do anyway: breaking monolithic, VM-hosted applications into containerized microservices and running them on a self-operated private cloud, so the exit from one vendor doesn't just walk into another one. GitOps delivery (Argo CD, Flux), the Gateway API, and policy-as-code — the same practices in our Kubernetes best-practices list above — are becoming the default operating model in place of click-ops through vCenter.
AI is riding the same wave
That modernization push is colliding with a second one: running AI workloads in-house instead of shipping proprietary data to a third-party API. Open-weight models — Llama, Mistral, Qwen, DeepSeek, and others — are now good enough for a large share of internal use cases, and serving them locally with vLLM, Ollama, or TGI keeps sensitive data inside the perimeter and turns a per-token bill into a fixed infrastructure cost.
The hardware catching up
Server vendors have followed. Dell's PowerEdge R760xa packs up to four double-width GPUs into a mainstream rack form factor, while the XE-series scales to eight GPUs per node for larger models; HPE's ProLiant DL380a Gen11 targets the same workload with validated NVIDIA configurations up to H100/H200 and L40S. Paired with a Kubernetes-based private cloud, that hardware turns local LLM inference into just another workload on the same GitOps-managed clusters running everything else — which is exactly the seam platforms like RuckOS and lighthouse are built to sit in.