Summary
This document is a technical report that outlines the concept of Edge as a Service (EaaS) and its role in enhancing AI-driven IoT deployments across various sectors such as automotive, manufacturing, healthcare, and retail. It describes how traditional centralized cloud architectures create performance constraints, including latency issues and compliance risks. The report details the architecture of EaaS, which integrates regional edge processing and localized traffic management within a unified operational framework. It explains the core components of EaaS, including distributed edge compute, local breakout capabilities, and centralized orchestration. The document further discusses the business challenges posed by legacy architectures and how EaaS addresses these issues by providing low-latency performance, reduced bandwidth costs, and improved compliance with regional data regulations. Additionally, it identifies specific environments where EaaS can deliver immediate impact, such as autonomous systems and regulated data environments, emphasizing the need for a re-architecture tailored for AI-driven applications.
