Performing data science at the edge has become increasingly important
within virtually all phases of the public sector. From smart traffic cameras to
hospitals using data processing for faster diagnosis and warfighters leveraging
data in theater, the ability to derive actionable intelligence at the edge has
never been greater.
Fulfilling the promise of real-time edge data processing and analysis requires
significant intelligence and computational horsepower that’s close to the action.
Yet for the most part we are still in an environment where most large-scale data
processing takes place at the core within powerful data centers, while smaller
jobs and inferencing take place at the edge.
KubeFrame for AI-Edge is a turnkey, field-deployable solution that combines Red
Hat OpenShift Container Platform with Hewlett Packard Enterprise’s Edgeline
EL8000 Converged Edge System and NVIDIA processing to create a truly portable,
enterprise-supported open source AI and machine learning experience. Housed in a
case that can easily fit in an airplane’s overhead compartment, the kit can be
transported to and quickly installed in an almost unlimited variety of field locations.
Sponsored by Carahsoft, Red Hat