
Virtual Instruments introduced VirtualWisdom 5.6, a new version of its infrastructure performance monitoring and analytics product that supports Cisco's SAN Telemetry Streaming and AppDynamics' application monitoring technology, dashboard drilldowns and proactive charts for troubleshooting.
The integration with Cisco's SAN Telemetry Streaming (STS) technology in the new Virtual Instruments VirtualWisdom 5.6 release eliminates the need to deploy Traffic Access Points and hardware probes to capture wire data in SAN environments built on Cisco's MDS 32 Gbps Fibre Channel (FC) technology. Additional integration with AppDynamics enables granular insight into applications and their dependencies to improve end-to-end visibility from the application infrastructure to the storage.
"The traditional SAN environment has visibility from the compute to the storage, but it really didn't understand the applications or the workloads running across that infrastructure," said Tim Van Ash, VP of Products, Virtual Instruments. "By being able to bring AppDynamics and STS together in those environments, we can now say what applications are out there, what workloads are generating against the infrastructure, how that is impacting the infrastructure and what we need to do to meet the needs of those applications."
Van Ash said customers provided feedback that they didn't understand how their applications were using the infrastructure or how to optimize application performance. So, Virtual Instruments expanded beyond its NAS and FC SAN focus into application-centric infrastructure performance management and partnered with vendors such as Cisco.
Last year's Virtual Instruments VirtualWisdom 5.4 release included support for Cisco's NetFlow protocol, enabling visibility directly off the IP network into application flows going into physical or virtual servers and into virtualized storage, Van Ash said.
With VirtualWisdom 5.6, Virtual Instruments built a special integration probe to consume the STS data. Cisco's 32 Gbps line card equipped with the SAN telemetry chip does the monitoring, and the performance data goes directly from the switch to VirtualWisdom. The STS capability delivers about 32 metrics per application conversation with 10-second granularity, compared with the VirtualWisdom performance probe's 400 or so metrics with per-second granularity, according to Van Ash.
"The value in deploying Cisco STS only is that it's [a] pure software solution. But if you want the visibility to absolutely assure the performance in mission-critical applications, the hardware capabilities are still available from Virtual Wisdom as add-ons," Van Ash said.
Virtual Instruments VirtualWisdom now supports application discovery through Cisco's AppDynamics and NetFlow, native host discovery via Secure Shell and Windows Management Instrumentation, and manual data import.
"This enables us to fill in the blind spots that [application performance management] APM tools have traditionally had," Van Ash said. "It's all about mapping applications to infrastructure -- knowing where they live so that you can track the workloads that are being generated by those applications and how infrastructure is responding to those workloads."
Virtual Instruments VirtualWisdom 5.6 also automatically generates charts to help customers analyze and respond to alerts the tool triggers in the event of problems. The prior 5.4 version provided text-based explanations and recommendations. But users can now receive a summary identifying typical causes and charts to help them troubleshoot and resolve issues.
Van Ash said the guided investigations are designed to extend Virtual Wisdom from the architects and engineering groups that typically used the product to the operations team and help desk that are at the front line of support and may not have the same level of technical expertise.
New management dashboards and drop-down menus in VirtualWisdom 5.6 can further help users interpret data the tool collects and solve problems. Summary views are available showing the overall health, performance and infrastructure utilization.
Virtual Instruments VirtualWisdom 5.6 is free to existing customers with current support contracts.
The Latest
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.
The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...