Choose a distributed model when resilience is a top priority. Regional nodes can continue serving users if a central site or a network path is unavailable. This approach helps reduce the impact of outages and improves availability across geographies. The tradeoff is added operational complexity, since you must manage more sites, more hardware variation, and more security perimeters.
For most organizations, the practical path is hybrid. Core business systems and shared services can run across regional or colocation sites in a distributed model, while latency-sensitive or data-gravity workloads move closer to the edge. The key is applying unified automation, zero-touch provisioning, and end-to-end visibility to manage it all consistently. Pilot one or two edge use cases, measure latency and cost benefits, then expand with a repeatable blueprint.
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Edge Computing Overview
Edge computing processes data closer to its source, enabling real-time insights and reducing latency. This decentralized approach improves efficiency, optimizes bandwidth, and enhances security by minimizing data movement. It’s essential for applications like IoT, smart cities, and autonomous systems, supporting rapid decision-making and scalable, resilient infrastructure.
Unlocking Edge Innovation at Scale
This eBook explores how edge computing drives innovation across industries by enabling real-time data processing, improved decision-making, and operational efficiency. It highlights use cases, benefits of deploying edge solutions, and how organizations can leverage edge infrastructure to accelerate digital transformation and gain a competitive advantage.