Riverbed launched a broad strategy to bring unified observability to customers worldwide and accelerate growth.
Front and center in the company’s strategy is the development of an expanded unified observability portfolio, which will unify data, insights and actions to solve one of the industry’s most daunting problems: how to provide seamless digital experiences that are high performing and secure in a hybrid world of highly distributed users and applications, exploding data and soaring IT complexity. Riverbed also launched a new brand identity, including the introduction of Alluvio by Riverbed (for Unified Observability), reflecting the evolution of the Company and technology.
“This marks an exciting new chapter for Riverbed,” said Dan Smoot, Riverbed President and CEO. “We’re capitalizing on our trusted brand, the dynamic growth, and market momentum for our visibility solutions to position Riverbed as a dominant leader in the rapidly growing observability market. Through our vision to deliver a highly innovative, differentiated SaaS-based Unified Observability portfolio, we will meet an urgent customer need and disrupt the market. We are focused on helping our customers transform massive amounts of data into actionable insights, so they can drive enterprise performance and deliver exceptional digital experiences.”
Riverbed has invested and focused the company’s R&D efforts in the last year to develop technology and a unique approach to unified observability that is comprehensive, unified and easy-to-operate. Alluvio by Riverbed, the Company’s Unified Observability software portfolio, is being designed to provide IT with a unified view to see through massive complexity, and transform data into actionable insights across the entire digital ecosystem and enable automated self-healing. This will enable organizations to provide seamless digital experiences that drive enterprise performance for both the employee experience (EX) and customer experience (CX).
“The name Alluvio derives from alluvium — the place where riverbeds unite and create the most nutrient-rich environment to mine for gold – with the ‘o’ standing for observability,” said Jonaki Egenolf, Riverbed’s CMO. “Metaphorically, it represents the coming together of discrete telemetry streams where insights that are hard to find, but worth their weight in gold, reside. Our Alluvio unified observability solutions help customers find that gold as fast as possible, turning actionable insights into business value so companies can stay competitive, productive and satisfy users’ fierce appetite for seamless digital experiences. Together, with our Acceleration portfolio, we are able to help customers first illuminate and then accelerate every interaction – and ultimately empower the experience for users everywhere.”
The Alluvio by Riverbed portfolio includes Riverbed’s visibility tools for network performance management (NPM), IT Infrastructure Monitoring (ITIM) and Digital Experience Management (DEM), which encompasses application performance management (APM) and end user experience monitoring (EUEM), that are available today and used by thousands of organizations across the world.
Riverbed’s vision of the Alluvio unified observability portfolio is to capture every packet, flow, and end user transaction across multi-cloud and on-premises networks, applications, and user systems at full fidelity; and then apply intelligence through machine learning and artificial intelligence, and help IT quickly identify and resolve digital service quality issues so organizations can maintain productivity and deliver on user experience expectations.
Riverbed will begin a Beta for a SaaS-based Alluvio unified observability solution in May 2022, with a general release expected later this year. To date, several organizations, including Fortune 500 companies, are trialing the solution, and providing valuable, positive feedback, highlighting that the Riverbed vision and approach to unified observability will eliminate data silos and alert fatigue, as well as improve decision-making, apply expert knowledge broadly and continuously improve digital service quality, all with a simple user interface.
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 ...