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IoT and edge computing: The perfect match

Sat 7 Sep 2019 | Alan Conboy

IoT edge computing

Alan Conboy, Office of the CTO of Scale Computing, explores the role of edge computing in the age of IoT

With the Internet of Things (IoT) generating more data than ever before, organisations must seriously consider what edge computing has to offer. According to a study from the International Data Corporation (IDC), 45 percent of all data created by IoT devices will be stored, processed, analysed and acted upon close to or at the edge of a network by 2020.

In a world that is increasingly data-driven, a large amount of data is being generated outside of the traditional data centre. Edge computing places the physical computing infrastructure at the edges of the network where the data is being generated, and in many cases, this is where the data is needed most.

Thanks to its small hardware footprint, edge infrastructure can collect, process, and reduce enormous amounts of data that can then be uploaded to a centralised data centre. Edge computing acts as a high-performance bridge from local computer to private and public clouds.

Relying on edge computing

There is significant evidence to suggest that IoT will not work without edge computing – or at least not effectively enough to realise its long-term potential. The inherent latency of cloud is no longer cutting it when it comes to deploying machine intelligence and getting real-time results. Edge computing is here to solve that problem, and by mitigating the latency associated with the cloud, it ensures that the latest IoT developments are available to businesses across every industry.

Industries with remote sites, such as retail, finance, industrial, remote office branch office (ROBO) and IoT will undoubtedly benefit from edge computing. In retail, for example, retailers need reliable computing that can provide maximum uptime for point of sale, inventory management and security applications for the numerous store locations on the edges of their networks. Banks and other financial institutions with multiple branch offices also require reliable computing to support rapid, business-critical transactions.

Edge computing is well-positioned to meet the growing deployment of IoT devices head-on, as it is capable of processing large amounts of data quickly and efficiently.  This requirement is only likely to become more pronounced when the communication of that data to the cloud is no longer reliable or fast enough to be effective.

In the case of ROBO deployments, small branch locations are now increasingly running core, mission-critical applications and the infrastructure they reside on needs to evolve to match the critical nature of the workloads they are running.

For the most part, edge computing sites have very precise computing requirements, therefore typically requiring smaller deployments than the primary data centre site. Many organisations may have dozens or hundreds of smaller edge computing sites and they cannot afford to roll out complex, expensive IT infrastructure to each site.

Facing the challenge head-on

Many applications running at the edge are becoming as critical as those in the data centre, so how can organisations match the resiliency, scalability, security, high-availability, and human IT resources found in the data centre? How can they address the growing mismatch between the importance of the applications and the infrastructure and IT that supports them at the edge?

The solution is that in order to support critical applications with little or no on-site IT staff, edge computing appliances must be as, if not more,  reliable, easy to deploy and use, highly available, efficient, high performing, self-healing, and affordable than data centres. In many instances, to keep applications running without dedicated IT staff onsite, systems require automation that eliminates mundane manual IT tasks where human error can cause problems.

Factors to consider

Edge computing systems can be relied on to stay up and running as automation monitors for complex system failure conditions and takes immediate action to rectify any issues. This eliminates the downtime that would take a system offline and require an IT staffer to come onsite to bring it back online. Even when hardware components fail, automation can shift application workloads to redundant hardware components to continue operating.

One of the key aspects of edge computing infrastructure systems is that they are easy to deploy and manage. Many businesses that have hundreds of sites can’t afford to spend lengths of time deploying complex hardware to each site. They need to be able to plug in the infrastructure, bring systems online, and remotely manage the sites going forward. The more complex the infrastructure, the more time they will spend deploying and managing it.

Edge computing systems are able to run with minimal management required. They need to be self-healing to provide high availability for applications without requiring IT staff resources, with automated error detection, mitigation, and correction. Management tasks should be able to be performed remotely and with ease. In addition, these systems should be scalable up and down, dependent on the requirement of the edge location, to ensure organisations are not saddled with excessive overhead for resources they don’t need.

When you delve into the benefits that edge computing brings to the IoT landscape, it is no surprise that its popularity continues to soar. Edge computing can act as a high performance bridge to the cloud, all in a small hardware footprint, which businesses are increasingly relying on to look after their data.

Experts featured:

Alan Conboy

Office of the CTO
Scale Computing


edge IoT
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