The worldwide x86 server virtualization market is expected to reach $5.6 billion in 2016, an increase of 5.7 percent from 2015, according to Gartner, Inc.
Despite the overall market increase, new software licenses have declined for the first time since this market became mainstream more than a decade ago. Growth is now being driven by maintenance revenue, which indicates a rapidly maturing software market segment.
Michael Warrilow, Research Director at Gartner, said: "The market has matured rapidly over the last few years, with many organizations having server virtualization rates that exceed 75 percent, illustrating the high level of penetration."
The market remains dominated by VMware, however, Microsoft has worked its way in as a mainstream contender for enterprise use. There are also several niche players including Citrix, Oracle and Red Hat, in addition to an explosion of vendors in the domestic China market.
While server virtualization remains the most common infrastructure platform for x86 server OS workloads in on-premises data centers, Gartner analysts believe that the impact of new computing styles and approaches will be increasingly significant for this market. This includes OS container-based virtualization and cloud computing.
The trends are varying by organization size more than ever before. According to Gartner, usage of server virtualization among organizations with larger IT budgets remained stable during 2014 and 2015. It continues to be an important and heavily used technology for these businesses, but this market segment is approaching saturation. In contrast, organizations with smaller IT budgets expect a further decline in usage through to at least 2017. This is causing an overall decline in new spending for on-premises server virtualization.
Gartner believes that organizations are increasing their usage of "physicalization," choosing to run servers without virtualization software. More than 20 percent of these organizations expect to have less than one-third of their x86 server OSs virtualized by 2017 — twice the amount reported for 2015. However, the underlying rationales remain varied.
The rise of software-defined infrastructure (SDI) and hyperconverged integrated systems (HCIS) are providing new options. It has put pressure on best-of-breed virtualization vendors to add more out-of-the-box functionality and provide a better experience and faster time-to-value.
"What was considered as the best approach to greater infrastructure agility only a few years ago, is becoming challenged by an array of newer infrastructure choices," said Warrilow.
Hot Topic
The Latest
In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...
Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...
In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ...
Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...
Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...
Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...
The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...
The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...
In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...
AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.