Leveraging Multi-Cloud and AI/ML

In December, the chapter organized a virtual professional development seminar (PDS) on Leveraging Multi-Cloud and Artificial Intelligence (AI)/Machine Learning (ML) and application to incorporate the Tactical Edge. Matt Waterfield, a data center product specialist from CISCO, led the PDS by addressing that the Software-Defined Data Center (SDDC) provides critical resources enabling modern AI/ML technologies. Modern SDDCs leverage elastic fabric architectures that automatically scale resources based on real-time use and projected demand. These fabrics allow cloud and on-premise resources to present as a single transparent resource with consistent policy management and inherent security. The real value of SDDCs is realized when extended across a Software-Defined Wide Area Network (SD-WAN). SD-WAN technologies allow access and transport across any transport (SATCOM, MPLS, Fiber, 5G, etc.)

Previous distributed computing designs relied heavily on large compute and storage resources that required massive transport networks to exchange information and conduct AI/ML functions. The proposed SDDC architecture leverages edge nodes for inferencing while public and private cloud resources provide access to machine teaching/learning resources. The advent of short-depth, ruggedized tactical servers capable of deploying GPUs provides lightweight small form factor nodes capable of supporting technologies, as mentioned earlier. Additionally, the ability to function in a distributed fashion prevents persistent network connections to execute adopted Internet of Things devices' diagnostic functions. In practical terms, these technological advancements are the realization of enterprise resources extended to tactical formations.

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