APCON announced that its IntellaStore II has completed Riverbed-Ready certification through the Riverbed-Ready Technology Alliance program.
When installed with Riverbed SteelCentral virtual network performance management (NPM) solutions – including SteelCentral NetProfiler, SteelCentral NetShark, and SteelCentral NetExpress – IntellaStore II enables customers to identify and resolve complex network issues quickly.
APCON’s IntellaStore II is an all-in-one network visibility solution for midsize data centers and remote locations, and combines an advanced network monitoring switch with a dedicated application processor that is Riverbed-Ready, compatible with VMware ESXi. The product will be released for general availability in May 2015, with Riverbed offering IntellaStore II customers a 90-day full license of Riverbed SteelCentral virtual NPM solutions.
“Network speed and reliability is critical for businesses, but is a constant challenge for IT operations in midsize organizations,” said Richard Rauch, President and CEO of APCON. “The APCON Riverbed-Ready certified solution offers midsize businesses the ability to monitor any point on their network, spot and prevent slowdowns and outages, and resolve problems quickly.”
“Through the Riverbed-Ready program, Riverbed and APCON will provide customers an integrated solution that helps solve their network monitoring issues,” said Katie Colbert, VP, Global Technology Alliances at Riverbed. “This end-to-end solution provides deep visibility to inspect, direct, and protect workloads across the hybrid enterprise.”
“Two key areas where mid-tier organizations can stretch their investments further are the consolidation of forensic packet storage and the reduction of dedicated hardware for packet monitoring tools,” stated Shamus McGillicuddy, Senior Analyst at Enterprise Management Associates. “APCON’s IntellaStore II can host multiple monitoring tools, eliminating the need to maintain separate dedicated appliances.”
The Latest
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 ...
The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...
Seamless shopping is a basic demand of today's boundaryless consumer — one with little patience for friction, limited tolerance for disconnected experiences and minimal hesitation in switching brands. Customers expect intuitive, highly personalized experiences and the ability to move effortlessly across physical and digital channels within the same journey. Failure to deliver can cost dearly ...
If your best engineers spend their days sorting tickets and resetting access, you are wasting talent. New global data shows that employees in the IT sector rank among the least motivated across industries. They're under a lot of pressure from many angles. Pressure to upskill and uncertainty around what agentic AI means for job security is creating anxiety. Meanwhile, these roles often function like an on-call job and require many repetitive tasks ...