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Riverbed Adds Runbooks and Sentiment Analysis to Aternity Intelligent Service Desk

Riverbed announced advanced AI-driven automated remediation with the addition of customizable runbooks (Riverbed automation) and integrated sentiment analysis to Aternity’s Intelligent Service Desk.

The customizable runbooks in Aternity enable more sophisticated remediations — replicating advanced investigations by correlating end-user impact and real-time granular performance data to identify incident root cause in order to tackle IT’s most challenging issues. The new Intelligent Service Desk capabilities also enable IT to understand end-user satisfaction through the integration of sentiment analysis across remediation workflows, from issue detection to resolution.

Aternity’s Intelligent Service Desk dynamically models expert decision-making and logic-driven remediation by leveraging customizable runbooks. Unlike other DEX offerings that utilize numerous remediation scripts for narrow use cases, Aternity’s Intelligent Service Desk enables broader AI-driven automation capacity, eliminating the need for human intervention. For unresolved issues, an IT service management (ITSM) ticket is routed to the right level with the necessary context for swift resolution. Now, Aternity’s flexible automation logic streamlines and correlates user feedback via Sentiment Surveys, enabling optimal engagement levels to resolve simple and complex issues efficiently.

Key features and benefits of Riverbed Aternity’s Intelligent Service Desk integration include:

- AI-Driven Correlation and Anomaly Detection of device and application issues

- Intelligent automation across remediation workflows, resulting in incident prevention

- Out-of-the-box and customizable runbooks, automatically triggered by Service Desk Alerts

- Interactive user feedback via Sentiment Surveys to prioritize and optimally resolve issues

- Seamless integration with ITSM tools such as ServiceNow for targeted, intelligent ticketing

“Today’s announcement builds on Riverbed’s years of experience in AI and automation. Riverbed Aternity’s expansion of its Intelligent Service Desk capabilities marks a significant milestone to empower organizations with more sophisticated remediations and sentiment to augment human decision-making,” said Richard Tworek, CTO, at Riverbed. “By offloading repetitive and lower-value tasks to AI-driven algorithms and intelligent automation, we’re enabling Digital Workplace teams to not only build a more proactive approach to remediation but also free up more time for human ingenuity.”

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Riverbed Adds Runbooks and Sentiment Analysis to Aternity Intelligent Service Desk

Riverbed announced advanced AI-driven automated remediation with the addition of customizable runbooks (Riverbed automation) and integrated sentiment analysis to Aternity’s Intelligent Service Desk.

The customizable runbooks in Aternity enable more sophisticated remediations — replicating advanced investigations by correlating end-user impact and real-time granular performance data to identify incident root cause in order to tackle IT’s most challenging issues. The new Intelligent Service Desk capabilities also enable IT to understand end-user satisfaction through the integration of sentiment analysis across remediation workflows, from issue detection to resolution.

Aternity’s Intelligent Service Desk dynamically models expert decision-making and logic-driven remediation by leveraging customizable runbooks. Unlike other DEX offerings that utilize numerous remediation scripts for narrow use cases, Aternity’s Intelligent Service Desk enables broader AI-driven automation capacity, eliminating the need for human intervention. For unresolved issues, an IT service management (ITSM) ticket is routed to the right level with the necessary context for swift resolution. Now, Aternity’s flexible automation logic streamlines and correlates user feedback via Sentiment Surveys, enabling optimal engagement levels to resolve simple and complex issues efficiently.

Key features and benefits of Riverbed Aternity’s Intelligent Service Desk integration include:

- AI-Driven Correlation and Anomaly Detection of device and application issues

- Intelligent automation across remediation workflows, resulting in incident prevention

- Out-of-the-box and customizable runbooks, automatically triggered by Service Desk Alerts

- Interactive user feedback via Sentiment Surveys to prioritize and optimally resolve issues

- Seamless integration with ITSM tools such as ServiceNow for targeted, intelligent ticketing

“Today’s announcement builds on Riverbed’s years of experience in AI and automation. Riverbed Aternity’s expansion of its Intelligent Service Desk capabilities marks a significant milestone to empower organizations with more sophisticated remediations and sentiment to augment human decision-making,” said Richard Tworek, CTO, at Riverbed. “By offloading repetitive and lower-value tasks to AI-driven algorithms and intelligent automation, we’re enabling Digital Workplace teams to not only build a more proactive approach to remediation but also free up more time for human ingenuity.”

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Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

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