HYBRID CLOUD-EDGE ARCHITECTURES FOR AI-DRIVEN APPLICATIONS: OPPORTUNITIES AND CHALLENGES

IoT has seen an exponential rise in the number of devices, and actual-time processing of data has become necessary, making AI-driven applications adopt hybrid Cloud-edge designs. These systems are able to process and analyze data in an optimal way using the advantages of edge and cloud computing ; moreover, they are able to face problems associated with a prolonged delay in delivery and limited bandwidth as well as data vulnerability. The prospects of utilizing hybrid cloud-edge are discussed in this paper for handling improved network capacity for data handling, faster response time, optimal usage of resources, and enhanced security. It also considers the challenges of implementing and deploying these designs, chiefly in terms of addressing concerns with risk, data coordination, and compliance. This report has been written with the intent of tackling the possible challenges and engaging in relevant recommendations which may help in optimizing the use of such architectures.