HPE announced an expansion of its retail-ready portfolio to help customers improve connectivity, security, insight, and performance across their operations.
The expanded solutions help retailers manage transactions, data, and shopping experiences with confidence across their entire landscape, from the back office and warehouse to the front of the store and curbside.
HPE's expanded retail solutions bring together the self-driving networks of HPE Aruba Networking CX switching and Mist AIOps at the branch edge with the latest HPE Nonstop solutions at the core, demonstrating how secure, resilient connectivity underpins retail modernization. These solutions are combined with HPE AI-native insight and assurance to give retailers the performance and confidence needed to support in-store operations and modern customer experiences.
Built for environments that require absolute continuity, the HPE Nonstop Compute NS9 X5 and NS5 X5 solutions help retailers keep transactions running and data available during peak demand, while new 8-port models in the HPE Aruba Networking CX 6000 Switch Series enable flexible deployment at checkout lanes and overhead crawl spaces through a compact, completely silent design.
“In modern retail, a single lost transaction is a lost customer or a damaged reputation. HPE is raising the bar for retail by combining resilient edge connectivity, self-driving AI-native operations, and fault-tolerant compute to give retailers the insight, automation and assurance they need to meet existing and future shopper demands,” said Sujai Hajela, EVP & GM, Campus & Branch, HPE. “This unified foundation combines key HPE solutions to help retailers deliver continuous operations and consistent performance at scale, building trust in the next era of retail, where every transaction counts and every experience matters.”
By strengthening the store edge, user experience visibility, and business insight, HPE addresses retailers’ needs for uptime, security, and scalability from the point of customer interaction through core business systems, introducing new innovations that include:
- For Business Insight: HPE is expanding access to retail insights, provided by the Mist AIOps platform, by integrating the Marvis virtual network assistant with HPE Juniper Networking Premium Analytics. This integration brings location intelligence and network performance data, including engagement and occupancy analytics, into Marvis' natural language interface, helping retailers move from reactive troubleshooting to proactive decision-making. As a result, IT, business operations, and marketing teams can quickly gain actionable insights to respond faster, optimize operations, and improve customer experiences.
- For the Edge: The HPE Aruba Networking CX 6000 Switch Series includes new 8-port Power over Ethernet (PoE) and non-PoE models that securely connect point-of-sale (POS) terminals, Internet of Things (IoT) devices, and staff systems to the network. Compared to legacy solutions, the new switches offer increased PoE capacity to support modern retail devices such as wireless access points, cameras, and sensors, enabling retailers to deploy new in-store services like digital signage, smart checkout, and edge analytics without reworking their network infrastructure. Advanced telemetry, IoT probing, and total system monitoring support self-driving operations, reduce dropped connections, and deliver more accurate energy usage insights.
- For User Assurance: HPE Aruba Networking User Experience Insight, part of HPE Aruba Networking Central, acts as an early warning system for organizations modernizing their networks. With support for Wi-Fi 7, User Experience Insight Sensors identify issues introduced by upgrades or network changes before users are impacted, helping protect revenue. Used alongside agents, the sensors deliver a comprehensive view of end-user activity, allowing IT teams to baseline network performance, continuously test network health, track trends, and plan for device growth and AI-native use cases.
HPE Nonstop Compute delivers continuous, fault-tolerant solutions for backend payment processing, inventory management, and other mission-critical applications. The platform keeps applications running without interruption, even during hardware failures or network disruptions, reducing downtime and protecting revenue during peak shopping periods.
To support the increasing demands of digital and AI transformation in retail, HPE is introducing new enhancements to the Nonstop portfolio:
- Higher performance and scale: HPE Nonstop solutions support linear, distributed scale to up to 4,000 nodes through multi-generational clustering and deliver up to 15 percent more performance capacity, based on internal benchmarks comparing HPE Nonstop Compute NS8 X4 and HPE Nonstop Compute NS9 X5. The Nonstop OS software scales easily to handle growing transaction volumes, preparing the core infrastructure to handle greater workloads and new data-rich applications like real-time analytics and AI.
- Enhanced data protection: Transparent Data Encryption (TDE) provides stronger security for sensitive customer data and helps retailers meet evolving data privacy and compliance regulations.
Both the HPE Nonstop Compute and HPE Aruba Networking CX Switching solutions are available as a service through the HPE GreenLake cloud platform, allowing retailers to align IT investments with business outcomes through a flexible, subscription-based model.
By deploying a unified data fabric across the edge and core, retailers gain the foundation needed to drive customer engagement and operational efficiency. HPE Aruba Networking CX enables easy expansion to new stores and devices, while new AI-native capabilities simplify operations and provide deeper insight into shopping experiences. At the core, an enhanced HPE Nonstop environment delivers the memory and bandwidth for real-time analytics, and high-volume omnichannel services without compromising availability.
The HPE Nonstop Compute solutions and HPE Aruba Networking CX 6000 Switch Series are available now.
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 ...