As our digital landscape becomes ever more complex, it is important for companies across every industry to keep up with the changes and developments in how we create and utilize increasingly valuable data. 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.

This makes up part of the reason why traditional data centers are no longer the default for data generation. In an increasingly data-driven world, Edge computing places the physical computing infrastructure at the edges of the network where the data is being generated, and in many cases, those sites are where the data is needed most.

Edge infrastructure collects, processes and reduces enormous quantities of data that can then be sent to a centralized data center or the cloud. With only a small hardware footprint, edge computing acts as a high-performance bridge from local computer to private and public clouds.

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The Edge of the Future

A special supplement tackling the fundamental questions surrounding Edge computing - from the cost, to the connectivity, to how it is processed, and more. Hear from industry experts, and from DCD's readers, to learn where the Edge will live.

A relationship built to last 

Many believe there is no doubt that IoT will need Edge computing in order to work effectively in the long-term. 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 industrial, finance, retail, and remote office branch office (ROBO) will particularly benefit from harnessing the power of 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.

IoT devices create a vast amount of data, and Edge computing continues to play a prominent role in processing all of it quickly and effectively. This requirement is only likely to become more pronounced when communication of that data to the cloud may not be reliable or fast enough to be effective.

When it comes to ROBO deployments, the infrastructure, on which small branch locations are increasingly running core mission-critical applications, must evolve to match the critical nature of these workloads.

More often than not, the needs of edge computing sites are very specific and require much smaller deployments than the primary data center site. Many organizations may have dozens or hundreds of smaller edge computing sites and they cannot afford to roll out complex, expensive IT infrastructure to each site.

How to approach the Edge 

As organizations increasingly run critical applications on the edge, requirements are closer to those of a data center. High-availability, security, scalability, resiliency, and human IT resources are easily deployed in a data center, but how can businesses address the growing disparity between the importance of the applications and the infrastructure, and the IT that supports them at the Edge?

Edge computing systems have to be more reliable, affordable, self-healing, high-performance, efficient, and easy to deploy and use in order to support critical applications with little or no on-site IT staff. 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 keep front of mind 

Automation ensures systems continue to run by monitoring for complex system failure conditions and correcting them with automatic action. 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.

Businesses with hundreds of sites cannot afford to spend weeks deploying complex hardware to each site, so edge computing infrastructure systems need to be easy to deploy and manage. 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 should require as little management as possible. 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 organizations are not saddled with excessive overhead for resources they don’t need.