Aruba, a Hewlett Packard Enterprise company, announced the availability of an embedded solution for mobile devices that delivers real-time visibility into roaming user experiences and application performance.
Developed with Zebra Technologies, an innovator at the front line of business with solutions and partners that deliver a performance edge, the Aruba User Experience Insight (UXI) AI software agent embedded in Zebra mobile computers analyzes real-time voice and data traffic and proactively flags issues that could affect application, Wi-Fi connectivity, roaming, and voice performance. The early warning provided by Aruba UXI informs remedial actions so that business-critical applications and end user experiences are not impacted. The result is higher up-time, increased productivity, and more expeditious problem remediation.
This announcement builds upon Aruba’s long-standing relationship with Zebra to bring to market innovative, mobile-based technology solutions that address critical operational issues spanning vertical markets. Aruba’s AI-based UXI agents’ network and application testing capabilities work in concert with Zebra’s Worry-Free Wi-Fi Edge Insights™ to expose a device-level view and pre-analyzed insights of the network. Results are displayed on Aruba’s intuitive UXI dashboard.
“Zebra developed WorryFree Wi-Fi Edge Insights to deliver superior device communications and management services,” said Julie Johnson, vice president of Global Product Management and Portfolio for Enterprise Mobile Computing at Zebra Technologies. “WorryFree Wi-Fi Edge Insights will provide businesses with an edge-to-cloud early warning system that can directly enhance productivity, efficiency, and profitability.”
The solution enables IT teams to automate the collection, analysis, and remediation of performance issues in real-time using data observed from the very devices that are being impacted, as simulated or historical data simply cannot provide the same level of accuracy as live data. For example, connectivity and voice performance might vary considerably while standing at floor level, moving on a forklift, or while picking at the top of a storage rack. The combination of Aruba’s UXI agents and Zebra Worry-Free Wi-Fi Edge Insights will expose these differences, enabling IT staff – locally or remotely – to precisely target solutions. The real-time nature of data collection means that even transient events that might otherwise go unnoticed are captured and analyzed.
The vast amount of data generated by Zebra mobile computers and other IoT machines can be meaningfully collected, analyzed, and acted upon by leveraging artificial intelligence (AI). Aruba pioneered the application of AI to automated network and application performance monitoring. Aruba UXI, a component of Aruba’s AIOps suite, is AI-powered and its Incident Detection feature baselines application performance over time and automatically identifies and alerts when it detects service-impacting changes in behavior. The cloud-based service allows IT to proactively resolve issues before they impact operations, and minimize alert fatigue, often without ever stepping foot on the site being monitored. AIOps runs as a service within Aruba ESP (Edge Services Platform), the industry’s first cloud-native platform designed to automate, unify, and secure the Edge.
“COOs are laser focused on improving operational efficiency, reducing downtime, and making the best use of skilled labor,” said Michael Tennefoss, VP of IoT and Strategic Partnerships at Aruba, a Hewlett Packard Enterprise company. “Many of the most vexing problems are transient in nature and extremely challenging to troubleshoot. Capturing real-time information right at the point of impact gives the most insightful view of what’s happening, and best informs how to fix it. And that’s exactly what the combination of Zebra’s new Worry-Free Wi-Fi Edge Insights and Aruba’s UXI accomplishes.”
The Aruba UXI Agent will be available in October of 2021. Target markets include healthcare, hospitality, logistics, and retail applications.
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