Industry analysts predict that, within a few years, up to three-quarters of the data generated by enterprises will be created outside of traditional centralized data centers or public clouds. Fueled by emerging AI, AR/VR, and IoT use cases, remote devices and end users are producing massive volumes of data, creating an ever-increasing demand for low-latency, high-throughput infrastructure. The need for data to be processed and secured as close to the point of origin as possible redefines how businesses plan, deploy, and operate their IT environment.

Moreover, the vast amount of analytical data generated and the ongoing deployment of ultrafast 5G mobile technologies pave the way for network-based services to shift from running on centralized public cloud services to the edge for fast, cost-effective, secure data processing. Meeting the challenge, mobile edge platforms allow compute and storage resources to be provisioned as close to the end user as possible—either at the boundary or within the operator network. In addition, mobile edge platforms allow operators to open up their radio access network (RAN) edge to authorized third parties, enabling them to rapidly deploy innovative applications and services for use by individual and enterprise consumers.

Mobile edge platforms deliver faster response times, increased insight, and an enhanced user experience. Additionally, these platforms can improve business agility and create new customer experiences in several ways, including:

  • Improved operational efficiency, cost optimization, and risk mitigation by reducing the volume of data backhauled to centralized processing hubs;
  • Ultra-low latency and accelerated time-to-insights by tapping into and processing data at the edge of the 4G LTE or 5G network;
  • Increased availability with autonomous edge systems enabling continuous operations even when disconnected, reducing disruption and lowering costs; and
  • Addressing many of the challenges associated with distributed computing, including bandwidth, data sovereignty, latency, and resiliency.

This decentralized approach—processing data as close to its origin as possible—is already operational in many industries to support emerging use cases. These include autonomous vehicles, drone-enabled precision agriculture and crop management, offshore oil and gas monitoring, real-time video surveillance, and utility smart-grid analysis.

Despite being a relatively new technology, more and more organizations are adopting mobile edge platforms to enable new use cases. This GigaOm Key Criteria report outlines critical criteria and evaluation metrics for selecting a mobile edge platform. The corresponding GigaOm Radar Report provides an overview of noteworthy mobile edge vendors and their offerings available today. Together, these reports are designed to help educate decision-makers, providing critical insights for enabling edge processing initiatives.

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Chris Grundemann

Creative BizTech & TechBiz Consultant

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