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Xangati Announces XSR11 Upgrade

Xangati announced the XSR11 upgrade to its suite of software tools that employ a 360-degree, cross-silo approach to provide live and continuous monitoring of an organization’s mission-critical virtualized infrastructure.

The new suite incorporates the Xangati Executive Dashboard, which provides an executive-level view of VDI and VI (Virtual Infrastructure) components of the network, including detailed recordings and reporting. Xangati focuses on network performance, availability, and capacity utilization – both instantaneously and over time – providing continuous real-time feedback for workload performance management in virtualized environments.

Xangati’s weighted capacity index ensures that customers achieve maximum capacity utilization without experiencing the “contention storms” that could degrade performance of virtualized network infrastructure.

Armed with real-time views of network activity, IT personnel can use Xangati’s health-score measurements – key performance indicators (KPIs) of network infrastructure – to provide a single, consolidated view of multiple applications and multiple platforms.

Personnel can even take look-ahead views to determine whether or when network performance will decline, and can then take quick remedial action to maximize the ROI of their network infrastructure and to ensure that they meet SLA commitments.

The Xangati MyDashboard allows users to customize their views to include, for example, just a particular application, or just the activity of a particular data center, cost center, or department – according to individual need or preference – to create a comprehensive aggregated performance index or even to create a live view of activity at a particular instant. Or a customized view can be built around multiple objects of the same type, such as groups of virtual machines, desktops, desktop pools, hosts, datastores, network interfaces, or physical endpoints or servers. MyDashboard therefore extends the benefits of real-time performance monitoring to business-unit executives and managers, allowing them to better manage application workloads in their virtualized environments.

The Xangati suite also incorporates the company’s StormTracker technology, which tracks and analyzes contention storms on the network, and for any virtualized workloads, whether VDI, VI or VNI (Virtual Network Infrastructure). Any authorized user, and even external users with authorization, can then submit a Visual Trouble Ticket, through which end-user issues can be tracked on a recording portal integrated with the organization’s service desk. This capability extends even to WMI (Windows Management Instrumentation), allowing administrators to specify multiple sets of global credentials to facilitate support for multiple Windows domains, to enable or disable WMI access globally or to individual Windows machines, or to perform bulk updates for WMI configuration.

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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 ...

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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 ...

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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 ...

Xangati Announces XSR11 Upgrade

Xangati announced the XSR11 upgrade to its suite of software tools that employ a 360-degree, cross-silo approach to provide live and continuous monitoring of an organization’s mission-critical virtualized infrastructure.

The new suite incorporates the Xangati Executive Dashboard, which provides an executive-level view of VDI and VI (Virtual Infrastructure) components of the network, including detailed recordings and reporting. Xangati focuses on network performance, availability, and capacity utilization – both instantaneously and over time – providing continuous real-time feedback for workload performance management in virtualized environments.

Xangati’s weighted capacity index ensures that customers achieve maximum capacity utilization without experiencing the “contention storms” that could degrade performance of virtualized network infrastructure.

Armed with real-time views of network activity, IT personnel can use Xangati’s health-score measurements – key performance indicators (KPIs) of network infrastructure – to provide a single, consolidated view of multiple applications and multiple platforms.

Personnel can even take look-ahead views to determine whether or when network performance will decline, and can then take quick remedial action to maximize the ROI of their network infrastructure and to ensure that they meet SLA commitments.

The Xangati MyDashboard allows users to customize their views to include, for example, just a particular application, or just the activity of a particular data center, cost center, or department – according to individual need or preference – to create a comprehensive aggregated performance index or even to create a live view of activity at a particular instant. Or a customized view can be built around multiple objects of the same type, such as groups of virtual machines, desktops, desktop pools, hosts, datastores, network interfaces, or physical endpoints or servers. MyDashboard therefore extends the benefits of real-time performance monitoring to business-unit executives and managers, allowing them to better manage application workloads in their virtualized environments.

The Xangati suite also incorporates the company’s StormTracker technology, which tracks and analyzes contention storms on the network, and for any virtualized workloads, whether VDI, VI or VNI (Virtual Network Infrastructure). Any authorized user, and even external users with authorization, can then submit a Visual Trouble Ticket, through which end-user issues can be tracked on a recording portal integrated with the organization’s service desk. This capability extends even to WMI (Windows Management Instrumentation), allowing administrators to specify multiple sets of global credentials to facilitate support for multiple Windows domains, to enable or disable WMI access globally or to individual Windows machines, or to perform bulk updates for WMI configuration.

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 ...