
The XSR12 release of Xangati's VDI, VirtualApp and WebApp Suites has been verified as Citrix Ready with Citrix XenDesktop, XenApp, and NetScaler.
Xangati XSR12 has successfully completed a rigorous verification process to ensure compatibility with Citrix’s latest products, which are at the heart of cloud and mobile initiatives world-wide. Based on its Citrix Ready status, Xangati is recommended to customers as a trusted third-party solution. Citrix enables applications to be deployed in the cloud, on-premise and in hybrid environments and to be accessible by mobile devices anywhere.
Greg Fox, director, Citrix Ready program, Citrix, said: “Citrix Ready makes it easier for customers to select the most suitable virtualization infrastructure products for their specific needs. By taking part in our program, Xangati has enabled its customers to obtain the highest quality user experience available today, and the simplest means for making an informed product purchasing selection.”
As Citrix customers step up to the latest technologies including XenApp 7.X, XenDesktop 7.X, and NetScaler 10.1, they often want to update their performance management solution. Many sites have point tools for looking at network traffic, other tools to see the health of hypervisors, and others that show NetScaler information. These silos make it hard for IT to get a clear picture of what is going on in their complex IT infrastructure. That’s why corporations that are deploying large XenApp or XenDesktop deployments turn to Xangati, especially within cloud and mobile deployment initiatives.
Xangati provides large organizations with fast second-by-second granularity of metrics collected from the entire IT infrastructure, including XenApp servers, XenDesktop servers, NetScaler ADCs and client BYO mobile devices, and without the need for agents. Xangati’s real-time dashboards, powerful DVR-like recordings, dynamic thresholds, advanced analytics, and prescriptive remediation steps to be carried out by IT save valuable time and allow corporations to get the most from their existing and future IT investments. Demos and information about Xangati’s Citrix-Ready product suites can easily be found in the Citrix Ready Xchange Marketplace.
“The powerful combination of Xangati fast data analytics with XenApp and XenDesktop flexibility is undeniable,” said Atchison Frazer, VP of Marketing, Xangati. “With Xangati’s real-time performance data visualization, analysis and remediation tools, our joint customers can quickly deliver superior service levels to end-users while gaining valuable end-to-end visibility intelligence of virtualized infrastructures.”
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 ...