Evolving Architectures for Edge Computing
With more compute power being put into shrinking footprints, a new class of workload has found a path outside of the datacenter.
Edge computing is a topic that has taken new life in the past year. With more compute power being put into shrinking footprints, a new class of workload has found a path outside of the datacenter. The ability to perform machine learned tasks at the edge for low latency results and data containment is now fully within reach for any organization. Despite being a new and rapidly evolving field, early adopters are finding certain patterns to use and certain patterns to avoid that impact everyone from application development, system administrators, and even procurement teams.
This session will present a variety of the reasons intelligence organizations are finding edge computing useful, which use cases are getting the most traction, prototypical applications architectures for edge computing, and IT operations concerns when leaving the data center. This class will target all levels of proficiency, but will be most informative for groups constructing their own tooling and looking to enable field analytics.
Presenter: Ryan Kraus, Lead Data Science and Edge Computing Architect, Public Sector
Ryan began his career as an Aerospace Engineer specializing in analysis methods and processes. Equal parts curiosity and carelessness lead Ryan into the dark world of IT infrastructure where he began building HPC and Kubernetes systems for scientific computing. Now he works at Red Hat helping Government organizations architect their next generation infrastructures for the next generation of science.