REX Analytics Lab Guide

1.REX Analytics Overview

Our mission is to predict and optimize remote end user experience in public and private cloud scenarios.


When interacting with computers or mobile devices, there are five usability aspects with significant relevance for most users: system navigation concepts, application design, user interface response times, data load times and the output quality of supported graphics and media formats.  The ultimate user experience would be delivered by environments with crystal-clear self-explanatory navigation, intuitive apps, unnoticeable user interface response time delays, immediate availability of data and best possible quality of all graphics and media formats.  Only systems that come close to this ideal allow users to naturally emerge into the digital world through a range of output devices with different capabilities and form factors, including head-mounted displays.  When adding cloud services, virtual desktop and application remoting concepts to the picture, this changes the way we need to look at user session responsiveness and media output performance.

Unfortunately, it’s hard to measure or score end-user experience in remote session and virtual desktop environments.  Until now, there is no commonly accepted benchmarking methodology and service offering where the primary focus lies on what a remote user really sees on the screen while measuring the timely correlated load patterns generated on the host platform.  As a consequence, there are no adequate metrics to define, measure and compare the quality of perceived remote end-user experience.  To fill this gap, it’s our goal to establish the Remote End User Experience (REX) Analytics Framework as a commonly accepted standard solution for benchmarking, quality management and performance optimization in End-User Computing (EUC) environments.

The REX Analytics Framework was designed to build EUC test labs and measure perceived remote end-user experience by simulating, automating and tracking a range of user interaction workloads.  The goal is to quantify user interface response times and graphical output performance.  The REX Analytics Framework includes fully automated (synthetic) test sequences, management consoles, screen and telemetry data recorders, and a unique visualization and analysis component.  The test methodology allows for insights into the user experience performance impacted by different remoting products, hardware constellations and the most relevant network factors.  The framework works across the boundaries of on-premises and cloud environments.

IMPORTANT: The REX Analytics test methodology strictly follows scientific integrity principles and best practices, ensuring objectivity, clarity, and reproducibility.

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