Red Hat: Edge Computing

Expert Edition: Taking advantage of data and compute at the edge

Explore the benefits, data security implications and strategies for managing complex edge systems. Our new ebook highlights how NOAA and VA aim to better serve users everywhere and shares real-world best practices from Red Hat experts.

Management of edge systems requires planning for unique circumstances, limitations

Edge computing happens in the kinds of environments where you can’t necessarily manage them moment to moment: the bottom of the ocean, outer space, battlefields, etc. Government agencies need to be able to control, manage and scale the environment remotely, without having to send humans to far off or dangerous places. Managing at scale at the edge requires a different approach than traditional datacenter locations.

Managing the unique security considerations of edge computing

One of the best ways to minimize a data breach is to reduce the amount of data sent back over potentially unsecured networks, like wireless. That requires a rebalancing of the three main components of edge computing: storage, network and compute.

Reduced cost, lower latency, faster decision making, greater flexibility: The benefits of edge computing

A primary benefit for edge computing is reducing the dependency on networks, a costly element both in terms of bandwidth and time. By moving the compute closer to the data, analysis can be performed on location, allowing just the results to be transmitted back across the network.

VA embraces AI to improve radiology screening

Following on the heels of a successful pilot that brought artificial intelligence to bear on radiology diagnoses, the Department of Veterans Affairs is looking for new opportunities to enhance its health care with AI.

Edge computing enables NOAA to push workloads closer to public consumers, not just field researchers

Frank Indiviglio, NOAA’s deputy director for High Performance Computing & Communications (HPCC), said conversations are happening about how NOAA can containerize its climate models in order to push the models themselves out to the public to understand, build upon and tweak.