Edge IoT: Better Service Quality, More Headaches

iot edge

Consolidated network monitoring is key to remote visibility in massive environments.

As Internet of Things-driven networks proliferate, edge computing is moving into the spotlight. Latency issues, data management, and uncertain connectivity make a compelling technical and business case for moving processing and data to the edge to power devices, sensors, kiosks and embedded systems. In environments requiring real-time responsiveness and adept handling of massive data flows, enhanced edge delivers service quality.

But while assuring the quality of centralized systems is a manageable problem, doing so with myriad systems along the edge can be a daunting challenge. “Too frequently, traffic at the edge goes unmonitored until a problem is reported,” notes a recent report by Enterprise Management Associates, a Boulder, CO, research and consulting firm.

Authors say that correct information about edge-based issues can be scarce or non-existent. They conclude: “Comprehensive and cost-effective monitoring at the network edge is needed to reduce the risk of performance delays and outages at the edge of hybrid IT environments.”

See also: Edge Computing Brings IT and OT Together

Bringing processing closer to the edge is supposed to deliver greater quality to the services rendered through IoT. Ironically, these initiatives can create new service quality issues. So edge visibility has become the new frontier to assuring performance at the farthest reaches of IoT networks.

EMA’s survey of 250 network managers finds a strong focus on active monitoring and packet-based monitoring. The type of data currently used for sustained network availability and performance monitoring include synthetic traffic (40 percent), management system APIs (40 percent), and packet inspection (35 percent).

The challenge: Multiple tools and technologies for addressing edge processing quality. EMA recommends a consolidated approach to network monitoring that provides as much remote visibility as possible. This includes the employment of “network packet brokers and network visibility platforms.”

With enterprises turning to edge computing to offload workloads from more centralized systems and scale to their growing IoT networks, quality needs to become a priority.


About Joe McKendrick

Joe McKendrick is RTInsights Industry Editor and industry analyst focusing on artificial intelligence, digital, cloud and Big Data topics. His work also appears in Forbes an Harvard Business Review. Over the last three years, he served as co-chair for the AI Summit in New York, as well as on the organizing committee for IEEE's International Conferences on Edge Computing. (full bio). Follow him on Twitter @joemckendrick.

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