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Riverbed Launches Aternity Sentiment

Riverbed announced the launch of Aternity Sentiment.

The addition of Sentiment to Alluvio Aternity™ optimizes the digital experience by correlating employee sentiment to application and device performance, enabling organizations to pinpoint user experience issues and take prescriptive, targeted actions that increase productivity and employee satisfaction, service quality and business performance.

To effectively gauge user satisfaction, and increase response rates to capture the workplace digital employee experience (DEX), Aternity Sentiment enables organizations to deploy customizable surveys to targeted user groups across multiple devices and locations. Aternity Sentiment captures feedback through flexible survey components, including Net Promoter Score® (NPS)1, an industry standard scale for measuring customer satisfaction, to provide organizations with an enhanced view of user engagement and productivity, resulting in improved business performance. By tightly correlating objective and subject metrics through Sentiment, the Alluvio Aternity DEM (digital experience management) solution provides the full picture of the digital experience, including, nuanced remediation feedback and additional human context.

IT departments rely on Alluvio Aternity to provide the deepest quantitative insights into employee and customer experience and the ability to benchmark digital experience against industry peers. Now with Sentiment, Alluvio Aternity tightly correlates aggregated insights on application and device performance data to human reactions, providing total digital experience management for employees.

“Most impacted issues originate beyond the device. If the goal is to enhance the digital experience, DEX solutions must offer end-to-end actionable insights from the network to the actual end user. Alluvio Aternity harnesses the power of the Alluvio Unified Observability portfolio, which delivers multi-dimensional correlation and low code automation across full-fidelity, full-stack telemetry,” said Richard Tworek, CTO, Alluvio at Riverbed. “Our customers also recognize that Aternity is the only DEX solution that provides click-to-render insights and end-user experience data to show the actual user experience on any application or device. Now, Sentiment adds the employee point-of-view, including how they perceive their digital experience. With Sentiment and existing capabilities such as user journey analytics and transaction tracing capabilities, Alluvio Aternity delivers a complete view of the digital experience for the business, employees, and customers.”

Alluvio Aternity full-spectrum Digital Experience Management (DEM) features End User Experience Monitoring (EUEM) and Application Performance Management (APM), and provides insight into the business impact of customer and employee digital experience by capturing and storing technical telemetry and sentiment feedback at scale from employee devices, every type of business application, and cloud-native application service. Deployed as an agent on end-user devices or application infrastructure, Aternity measures what users actually see for every transaction, every app, running on any device. Today, Aternity manages more than four million endpoints globally, and processes over 250 billion activities daily, playing a critical role in the Digital Employee Experience (DEX). Alluvio Aternity is part of the Alluvio Unified Observability portfolio from Riverbed, which also includes network performance management (NPM), IT infrastructure monitoring (ITIM), and Alluvio IQ – the first service built on the new Alluvio Unified Observability platform, a secure, highly available and scalable SaaS platform for cloud-native observability services.

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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 ...

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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 ...

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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.

Riverbed Launches Aternity Sentiment

Riverbed announced the launch of Aternity Sentiment.

The addition of Sentiment to Alluvio Aternity™ optimizes the digital experience by correlating employee sentiment to application and device performance, enabling organizations to pinpoint user experience issues and take prescriptive, targeted actions that increase productivity and employee satisfaction, service quality and business performance.

To effectively gauge user satisfaction, and increase response rates to capture the workplace digital employee experience (DEX), Aternity Sentiment enables organizations to deploy customizable surveys to targeted user groups across multiple devices and locations. Aternity Sentiment captures feedback through flexible survey components, including Net Promoter Score® (NPS)1, an industry standard scale for measuring customer satisfaction, to provide organizations with an enhanced view of user engagement and productivity, resulting in improved business performance. By tightly correlating objective and subject metrics through Sentiment, the Alluvio Aternity DEM (digital experience management) solution provides the full picture of the digital experience, including, nuanced remediation feedback and additional human context.

IT departments rely on Alluvio Aternity to provide the deepest quantitative insights into employee and customer experience and the ability to benchmark digital experience against industry peers. Now with Sentiment, Alluvio Aternity tightly correlates aggregated insights on application and device performance data to human reactions, providing total digital experience management for employees.

“Most impacted issues originate beyond the device. If the goal is to enhance the digital experience, DEX solutions must offer end-to-end actionable insights from the network to the actual end user. Alluvio Aternity harnesses the power of the Alluvio Unified Observability portfolio, which delivers multi-dimensional correlation and low code automation across full-fidelity, full-stack telemetry,” said Richard Tworek, CTO, Alluvio at Riverbed. “Our customers also recognize that Aternity is the only DEX solution that provides click-to-render insights and end-user experience data to show the actual user experience on any application or device. Now, Sentiment adds the employee point-of-view, including how they perceive their digital experience. With Sentiment and existing capabilities such as user journey analytics and transaction tracing capabilities, Alluvio Aternity delivers a complete view of the digital experience for the business, employees, and customers.”

Alluvio Aternity full-spectrum Digital Experience Management (DEM) features End User Experience Monitoring (EUEM) and Application Performance Management (APM), and provides insight into the business impact of customer and employee digital experience by capturing and storing technical telemetry and sentiment feedback at scale from employee devices, every type of business application, and cloud-native application service. Deployed as an agent on end-user devices or application infrastructure, Aternity measures what users actually see for every transaction, every app, running on any device. Today, Aternity manages more than four million endpoints globally, and processes over 250 billion activities daily, playing a critical role in the Digital Employee Experience (DEX). Alluvio Aternity is part of the Alluvio Unified Observability portfolio from Riverbed, which also includes network performance management (NPM), IT infrastructure monitoring (ITIM), and Alluvio IQ – the first service built on the new Alluvio Unified Observability platform, a secure, highly available and scalable SaaS platform for cloud-native observability services.

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.