Riverbed Technology announced new SteelCentral network performance management (NPM) solutions specifically designed to provide visibility to applications across the hybrid enterprise – data centers with a mix of both public and private networks and a combination of on-premises and SaaS/cloud apps, which is fast becoming the new normal.
The new and updated SteelCentral NPM appliances – NetShark and NetProfiler – provide faster and more granular views of the performance of both on-premises and cloud applications. This is essential to meet the growing demands of application performance for more users connected to more networks that is the continual state of IT today.
Today’s applications are making more connections to deliver the same data. Browsers and servers are getting smarter about how they break up and access data and this creates more connections. Web pages are getting content from more and different places – like ads, Google maps, social media links – and this also increases connection counts. Also, certain protocols, such as Microsoft’s protocol for O365 and Exchange, create more connections. The new SteelCentral solution enhancements provide the increased storage, memory, and power that Riverbed’s customers need to monitor this expanding environment of increasing connections and flows as required by the hybrid enterprise.
“As enterprises embrace BYOD and modern web, mobile, and SaaS applications, the amount of traffic on the network grows exponentially, so visibility becomes more important than ever,” said Mike Sargent, SVP and GM, SteelCentral at Riverbed. “With so much business depending on the flawless performance of applications and networks, companies need to prevent outages rather than troubleshoot them and that’s exactly what these faster SteelCentral solutions enable.”
The new Riverbed NPM appliances give IT teams the application visibility and control they need in hybrid IT environments, and as more people and devices are connected to the network.
The new NetProfiler appliances and features provide software and licensing changes that significantly increase scale across the board for NetProfiler users, including:
- Supports twice the number of de-duplicated flows per minute (FPM) on a smaller hardware footprint
- Supports twice the reporting devices per flow record; collates and de-duplicates flow information from up to 10 devices per single flow record for a more granular view of network performance
- Supports 10x the number of analytics policies
- Bundles analytics license with enterprise and standard NetProfiler licenses so all customers get proactive anomaly detection and early warning notification
- Covers triple the number of end-user locations in the Services Dashboard
The new NetShark appliances are available in three models – the low-end 2170, mid-range 4170, and the high-end, modular 6170 – all with the following performance enhancements:
- Larger, redundant system and packet storage (up to 72TB of packet storage)
- Significantly more memory (32/64GB) for higher flow export rates to NetProfiler
- Higher 10G port density
- NetShark Virtual Edition is also now available on Microsoft Hyper-V
SteelCentral Flow Gateway, which provides the flow collection and de-duplication for NetProfiler, adds a new two-million-flows-per-minute licensing tier to support the higher flow counts within NetProfiler with a smaller hardware footprint. New versions of the SteelCentral NetExpress all-in-one network performance-monitoring appliance for small- and mid-size enterprises are also available.
The newest SteelCentral NPM products are currently available.
The Latest
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 ...
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 ...