The News
At KubeCon North America 2025, OVHcloud announced plans to expand its hybrid and multi-cloud offerings through deepened partnerships with VMware (as a premier Broadcom partner) and Nutanix (as a new NC2 partner). The company, which recently surpassed €1 billion in annual revenue with its US subsidiary exceeding $100 million, is launching multiple VMware Cloud Foundation (vCF) services including a mutualized “vCF as a Service Public” for smaller deployments, a “vCF as a Service Private” with dedicated hardware arriving in 2026, and options for customers to install vCF on certified bare metal servers. OVHcloud is also introducing an on-premises cloud platform delivering a full stack of servers, networking, and open-source software for connected or air-gapped deployments, supporting VMware, Nutanix, and OVHcloud’s OpenStack-based public cloud stack. Full details will be revealed at the upcoming OVHcloud Summit in Paris.
Analyst Take
The cloud repatriation trend that OVHcloud is positioning against represents a significant market inflection point, driven by cost unpredictability, egress fees, and operational complexity that have eroded the total cost of ownership advantages originally promised by hyperscale public clouds. While public cloud adoption remains strong, our Day 1 research shows that 61.79% of organizations operate hybrid deployment models combining on-premises and cloud infrastructure, with only 16.80% running pure cloud-native environments and 11.38% remaining fully on-premises. This distribution reflects a pragmatic enterprise reality where workloads are increasingly distributed based on cost, performance, and data governance requirements rather than ideological commitment to cloud-first strategies. OVHcloud’s “different kind of cloud” positioning, emphasizing predictable pricing, no egress fees, and bare metal options, directly addresses the friction points that have driven repatriation, particularly for workloads with high data transfer volumes or consistent compute requirements where reserved capacity economics favor dedicated infrastructure.
The expansion of VMware Cloud Foundation services reflects OVHcloud’s bet that enterprises want cloud operational models without abandoning existing virtualization investments and skillsets. The company’s emphasis on delivering an “unadulterated” VMware experience with zero learning curve contrasts sharply with hyperscaler approaches that abstract or modify VMware implementations to fit their architectures. This strategy aligns with market data showing that while organizations are cloud-native aware with 76% reporting high familiarity with cloud-native architecture principles according to our Day 0 research, adoption of pure cloud-native platforms remains selective. The tiered vCF offering (mutualized public, dedicated private, and self-managed on bare metal) provides flexibility across different enterprise maturity levels and regulatory requirements, addressing the reality that not all workloads justify the operational overhead of Kubernetes-based cloud-native architectures. For organizations with significant VMware estates, OVHcloud’s approach offers a migration path that preserves existing automation, tooling, and operational processes rather than requiring wholesale re-platforming.
The on-premises cloud platform announcement positions OVHcloud to capture workloads that cannot move to public cloud due to data sovereignty, compliance, or air-gap security requirements. Our research indicates that cloud infrastructure remains the second-highest IT spending priority at 65.9%, trailing only AI and machine learning at 70.4%, yet deployment model preferences are shifting. Organizations are increasingly evaluating where workloads run based on total cost of ownership, performance requirements, and regulatory constraints rather than defaulting to public cloud. OVHcloud’s full-stack approach of providing servers, networking, and open-source software for on-premises deployment addresses a market gap between hyperscaler outpost offerings (which often require connectivity to public cloud control planes) and traditional on-premises infrastructure (which lacks cloud operational models). The platform’s support for VMware, Nutanix, and OpenStack provides flexibility for organizations with diverse infrastructure standards, though this multi-platform strategy also introduces complexity in maintaining feature parity and operational consistency across stacks.
OVHcloud’s measured approach to AI infrastructure reflects pragmatic skepticism about GPU oversupply and workload economics that contrasts with the aggressive capacity buildouts announced by hyperscalers. The company’s focus on inference workloads, which can often run effectively on CPUs or older GPUs rather than requiring latest-generation accelerators, aligns with emerging market realities as AI deployments move from experimentation to production. Our Day 0 research shows that 64% of organizations are very likely to invest in AI tools for application development in the next 12 months, with another 30.7% likely to invest, yet the specific use cases and infrastructure requirements remain poorly defined for many organizations. OVHcloud’s caution about over-provisioning expensive, fast-depreciating GPUs reflects recognition that enterprise AI workloads will likely distribute across a spectrum of compute requirements, from high-end training clusters to cost-optimized inference endpoints, rather than concentrating exclusively on premium accelerators. This positioning could prove advantageous if the market experiences GPU oversupply or if inference workload economics favor more distributed, cost-effective compute models.
Looking Ahead
The cloud repatriation trend will likely accelerate as organizations gain operational maturity in managing hybrid environments and as economic pressures intensify scrutiny of cloud spending. OVHcloud’s challenge is scaling its hybrid and multi-cloud platform while maintaining the cost predictability and operational simplicity that differentiate it from hyperscalers. The company’s partnerships with VMware and Nutanix provide credibility and reduce customer risk, but success will depend on delivering consistent operational experience across public cloud, private cloud, and on-premises deployments which is a notoriously difficult engineering and support challenge. With 43.90% of organizations allocating 26-50% of IT budgets to application development and 60.70% prioritizing cloud infrastructure spending, according to our Day 1 research, the market opportunity is substantial for providers that can deliver cloud economics and operational models without hyperscaler lock-in or cost unpredictability.
OVHcloud’s pragmatic AI strategy positions it for the post-hype phase of enterprise AI adoption, when workload economics and operational efficiency will matter more than access to cutting-edge GPUs. As organizations move from experimentation to production AI deployments, the focus will shift from training infrastructure to inference optimization, cost management, and integration with existing application architectures. OVHcloud’s emphasis on inference workloads and avoiding GPU over-investment suggests the company is preparing for a market where AI infrastructure becomes more commoditized and price-sensitive, favoring providers with efficient operations and predictable pricing over those competing primarily on raw compute capacity. However, this conservative approach carries risk because if AI workloads concentrate at hyperscalers due to ecosystem effects, data gravity, or integrated AI services, OVHcloud may find itself marginalized in the most strategically important workload category. The company’s upcoming summit announcements and continued partnership expansion will indicate whether it can balance pragmatic infrastructure investment with the aggressive positioning required to capture enterprise AI mindshare in an increasingly competitive market where cloud providers are making multi-billion dollar AI infrastructure bets to secure long-term platform dominance.
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