A Guide to Simplifying Large-Scale Edge Projects

The adoption of edge computing is growing across nearly every industry, with many IT infrastructure and operations leaders recognizing the need to reduce latency and enable real time processing at the edge. The recent rise in AI adoption is also accelerating the demand for optimized and efficient edge computing solutions. For example, edge devices can collect data to power AI and machine learning applications that drive efficiency, reduce safety and security risks, and help organizations deliver more value to customers.   

Due to this adoption wave, Gartner predicts that by 2025, 75% of enterprise-generated data will be created and processed outside a traditional centralized data center or the cloud.  

However, many organizations face significant challenges when procuring thousands of hardware components for large-scale edge initiatives, and then managing this multi-site distributed edge infrastructure.  

In this guide we’ll cover the challenges with large-scale edge initiatives, and ways to overcome them by streamlining hardware procurement and simplifying network management. We’ll also discuss how AHEAD’s services and software solutions can reduce edge project timelines from years to just months.