NetScout Systems has been awarded a patent on its Adaptive Session Intelligence (ASI) technology by the United States Patent and Trademark Office.
The ASI Patent acknowledges the unique innovations in the core technology behind the recently announced nGeniusONE Unified Performance Management platform and powers the nGenius InfiniStream appliances.
ASI technology further extends NetScout’s more than two decades of leadership and expertise in the performance management market. The metadata generated by ASI is leveraged as part of an indexed repository of valuable information, delivering real time and actionable operational intelligence.
NetScout’s ASI technology is built from the ground up to scale to speeds of up to 100 Gigabits per second on a given network segment using creative data reduction, multi-threading, de-duplication, optimization and stateful inspection techniques.
“Continuously increasing traffic volume and complexities require performance monitoring systems that scale to extract meaningful intelligence from the network,” said Elisabeth Rainge, Research VP, CSP operations at IDC. “NetScout's ASI technology addresses the challenges of variety, velocity, volume, and veracity to deliver meaningful insight into service performance and user experience based upon the correlated analysis of application, network and service sessions."
Enabling massive analysis scale, ASI technology performs real-time data mining of user and application traffic at the network source – as it crosses the wire, eliminating the need for expensive middleware or aggregation servers. The metadata created by ASI technology is leveraged from nGenius InfiniStream appliances into a distributed database residing in nGeniusONE servers.
ASI technology is the key enabler for NetScout’s convergence of Application Performance Management (APM) and Network Performance Management (NPM) into the nGeniusONE platform. The ASI metadata includes key traffic indicators, key performance indicators, and Layer 4 through 7 problem indicators for the discovered applications and servers, without installing device agents or complex provisioning.
ASI can be hosted in physical and virtualized environments and supports hundreds of enterprise applications, including voice and video, and allows future support for new applications, with minimal engineering effort.
“When combined with the analytics capabilities of the nGeniusONE platform, ASI technology enables next-generation NPM and APM capabilities for enterprise organizations who want to reap the inherent benefits of IT convergence, virtualization, distributed data centers and other IT optimizations, but are challenged by the increasing management complexity associated with such environments,” said Anil Singhal, president and CEO at NetScout. “Some of these emerging problems also involve contention for shared resources, BYOD, traffic explosion, interaction between network, server and application components, and inherent dependencies between them. While our immediate focus with ASI is IT operations, it has been designed to create next generation solutions for Big Data analytics and CyberSecurity applications, as well.”
The Latest
In 2026, the cost of downtime or an outage is no longer just a technical inconvenience; it's a $600 billion wake up call for global businesses. As our digital ecosystems become more interconnected, each touchpoint introduces new risks and multiplies the consequences when things go wrong. And the data is clear: aggregate downtime costs for Global 2,000 companies have surged 50% since 2024, reaching a staggering $600 billion ...
Deloitte found that 74% of enterprises expect to deploy agentic AI solutions in the next 24 months. However, the rush to deployment is outpacing foundational work, though. Only 21% of enterprises have fully formed agent governance models in place. The result? AI agents deployed without guidance or governance begin to function as fragmented islands of complexity ...
Cloud spending is no longer viewed as a passthrough IT expense, but as a strategic financial lever that directly impacts innovation capacity, profitability and enterprise resilience, according to the CFO Cloud Cost Optimization Report from Azul ...
As AI moves from generating responses to performing actions, the need for trust increases exponentially. And as organizations enlist AI agents for increasingly sophisticated business processes, trust is going to be the single most important theme for spurring adoption. What can organizations do to build trustworthy AI agents? ...
I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...
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 ...