Virtual Instruments and Panduit announced a new solution for EMC VSPEX for End User Computing with XtremIO proven infrastructure. The technology integration delivers a proven approach to deploying converged infrastructure with embedded performance monitoring across all systems and environments. This enhanced solution will provide EMC customers and partners with comprehensive visibility and definitive insight into their infrastructures’ functions and operations across all virtualized and cloud environments.
The EMC VSPEX for End User Computing with XtremIO architecture is targeted at the most demanding application I/O requirements for end user computing where transaction level performance is required. Through collaboration with Virtual Instruments’ VirtualWisdom infrastructure performance management (IPM) and Panduit tapped fiber cassettes, the new XtremIO offering gives users the ability to collect, monitor, and analyze granular real-time data at the storage protocol layer through to the virtualization layer. This solution enables customers to optimize EMC VSPEX with XtremIO deployments to ensure increased application performance and availability, and highly efficient hardware utilization.
Pete Eggimann, Director, VSPEX Ecosystem program at EMC, said, “We continue to deliver on our promise to give customers best-in-class technology that allows for faster deployments, greater efficiency, and lower risk deploying VSPEX architectures. In collaboration with Panduit and Virtual Instruments, VSPEX with XtremIO deployments combine industry-leading compute, network, and virtualization technologies with real-time performance and diagnostic monitoring capabilities to ensure predictable performance levels of the most demanding and critical end user computing workloads.”
Virtual Instruments and Panduit created the EMC VSPEX with XtremIO integrated offering to help streamline platform configurations for quick and consistent deployments of virtualized desktop infrastructure and applications.
Panduit provides the cabling infrastructure, including QuickNet Tapped Fiber Cassettes, which enables Virtual Instruments to integrate the additional layer of intelligence and infrastructure performance management technology into the EMC VSPEX with XtremIO architecture. Such deployments will enable EMC partners to provide customers with expanded services and support for mission-critical workloads.
With the explosion of virtualized applications across software defined data centers, enterprises are beginning to proactively instrument performance management capabilities at the time of deployment. This reference architecture enables customers to deliver embedded performance management capabilities to identify and fix any performance degradation in real-time.
“EMC continues to lead the industry with reference architectures that provide customers with a simple, yet flexible, platform that can easily be configured based on the performance characteristics of the application. The joint EMC with VSPEX architecture reduces the complexity and risk that typically come with virtualizing IO-intensive workloads by building in tools to increase performance and availability,” said Jason Cowie, Strategic Alliances Director, Virtual Instruments.
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.