Autonomous Data Management at Edge: Challenges and Possibilities.

Edge Cloud Computing usually talks about compute, memory, and latency. However, for large deployments of Edge Cloud, the data at the edge is critical for edge computing be possible. Any typical edge cloud could contain heterogeneous hardware, platforms, and of course distributed heterogeneous storage. Sanil and Vinod from their experience working in Edge Computing, Cloud Native, Data Management, Storage, and CSI, provide methods and architecture to bring the data autonomy to edge computing. To illustrate the architecture and proposal, they use heterogeneous storage management solution models from SODA Foundation projects. The session discusses the demanding data management requirements at the edge, challenges, and opportunities. They think this session can trigger more technical thoughts to build an open and autonomous data management framework for Edge.

Learning Objectives

Explore Edge Data Management Requirements and Architecture,Analyse Edge Data Management challenges and opportunities,Discuss on possible collaboration among SODA Foundation, CNCF(KubeEdge, Kubernetes, CSI..), EdgeX(LF) for a unified framework,Discuss and collect inputs on the current architecture proposal and future