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AppNeta Introduces User-Level Performance Monitoring

AppNeta announced the launch of user-level performance monitoring designed to scale to tens of thousands of concurrent workstations via a SaaS-based platform.

By providing minute-by-minute insight into per-user performance and usage patterns of VPNs, WiFi, and critical Host Metrics including CPU, memory, and top applications in use, enterprise IT and network operations teams can easily gain a hyper-local understanding of workstation-level performance, regardless if their users are working from home or office.

By adding additional per-user insight that covers the the entire localized environment and adding this to the existing end-to-end insight of AppNeta Performance Manager, network operations teams can dramatically speed up mean time to resolution when user issues are reported, regardless of where work is being conducted or how users connect to business critical applications. Quickly understanding if a specific end user is leveraging a VPN or not, whether they’re connected via WiFi or ethernet, or if the local workstation’s applications are over-taxing the local CPU or memory resources, for instance, empowers centralized IT teams to map out a fast path to problem resolution.

The new deep WiFi metrics added to AppNeta Performance Manager now provide multiple dimensions of wireless quality telemetry over time in order to spot changes and chronic problems like a weak signal, low link speed, improper channel selection, and network congestion. Minute granularity along with full time range selection allows IT to visualize several key performance metrics about any given WiFi interface in use by a specific end user. The trended WiFi metrics include high-level data designed to quickly isolate problem areas like Signal Quality and Link Speed, along with additional troubleshooting metrics including RSSI, RF Noise, Airtime, Retransmit, and Stations.

When signal quality and RSSI are in the upper ranges but performance issues persist, IT can investigate other potential sources, such as local network congestion, or one or more clients dominating the fixed amount of total available bandwidth where a user is working. Alternatively, when Signal Quality and RSSI are in the lower ranges, IT can instruct remote users to move the workstation closer to the WiFi access point or connect it to a wired network.

The new VPN and Host metrics charts complement WiFi visibility by delivering user- and device-specific data. IT can now automatically determine if a user is connected via VPN, regardless if the user is wired or on WiFi, while the Host metrics include CPU and Memory utilization for a specific device, as well as Top Processes using the most CPU resources at a given time.

“AppNeta has consistently led the market in delivering highly scalable, low overhead end-to-end insight into the end user’s experience of business critical applications,” said Matt Stevens, AppNeta’s CEO. “Extending this visibility down to the per-user level and gaining additional critical viewpoints into the impact of the local environment while maintaining enterprise scale empowers IT and the business to confidently everage any required application wherever the users decide to work on any given day.”

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AppNeta Introduces User-Level Performance Monitoring

AppNeta announced the launch of user-level performance monitoring designed to scale to tens of thousands of concurrent workstations via a SaaS-based platform.

By providing minute-by-minute insight into per-user performance and usage patterns of VPNs, WiFi, and critical Host Metrics including CPU, memory, and top applications in use, enterprise IT and network operations teams can easily gain a hyper-local understanding of workstation-level performance, regardless if their users are working from home or office.

By adding additional per-user insight that covers the the entire localized environment and adding this to the existing end-to-end insight of AppNeta Performance Manager, network operations teams can dramatically speed up mean time to resolution when user issues are reported, regardless of where work is being conducted or how users connect to business critical applications. Quickly understanding if a specific end user is leveraging a VPN or not, whether they’re connected via WiFi or ethernet, or if the local workstation’s applications are over-taxing the local CPU or memory resources, for instance, empowers centralized IT teams to map out a fast path to problem resolution.

The new deep WiFi metrics added to AppNeta Performance Manager now provide multiple dimensions of wireless quality telemetry over time in order to spot changes and chronic problems like a weak signal, low link speed, improper channel selection, and network congestion. Minute granularity along with full time range selection allows IT to visualize several key performance metrics about any given WiFi interface in use by a specific end user. The trended WiFi metrics include high-level data designed to quickly isolate problem areas like Signal Quality and Link Speed, along with additional troubleshooting metrics including RSSI, RF Noise, Airtime, Retransmit, and Stations.

When signal quality and RSSI are in the upper ranges but performance issues persist, IT can investigate other potential sources, such as local network congestion, or one or more clients dominating the fixed amount of total available bandwidth where a user is working. Alternatively, when Signal Quality and RSSI are in the lower ranges, IT can instruct remote users to move the workstation closer to the WiFi access point or connect it to a wired network.

The new VPN and Host metrics charts complement WiFi visibility by delivering user- and device-specific data. IT can now automatically determine if a user is connected via VPN, regardless if the user is wired or on WiFi, while the Host metrics include CPU and Memory utilization for a specific device, as well as Top Processes using the most CPU resources at a given time.

“AppNeta has consistently led the market in delivering highly scalable, low overhead end-to-end insight into the end user’s experience of business critical applications,” said Matt Stevens, AppNeta’s CEO. “Extending this visibility down to the per-user level and gaining additional critical viewpoints into the impact of the local environment while maintaining enterprise scale empowers IT and the business to confidently everage any required application wherever the users decide to work on any given day.”

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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 ...

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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 ...

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