Why Edge Computing Is So Important for IoT

The inherent latency of cloud is no longer cutting it when it comes to fully appreciate the benefits of digital transformation. 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.

2019 is the year to look seriously at edge computing, as the Internet of Things (IoT) and the global network of sensors steadily increase the amount of data that the average cloud has had to handle in the past. According to a study from the International Data Corporation (IDC), 45 percent of all data created by IoT devices will be stored, processed, analyzed and acted upon close to or at the edge of a network by 2020.

We are living in a world that is increasingly data-driven, and that data is being generated outside of the traditional data center. 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.

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

IoT Needs Edge Computing

There’s a strong argument to say that, by definition, IoT will need edge computing to work effectively and realize 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.

It is especially useful for any industry that has remote sites, such as retail, finance, industrial, remote office branch office (ROBO) and IoT. 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 plays a prominent role in the continuing deployment of IoT devices as the most effective means to process the vast amount of data they produce 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.

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.

Many edge computing sites have very specific computing needs 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.

Meeting The Challenge at the Edge

But with many applications running on the edge becoming as critical as those in the data center, how can organizations match the resiliency, scalability, security, high-availability and human IT resources found in the data center? How can they address the growing mismatch between the importance of the applications and the infrastructure and IT that supports them at the edge?

To support critical applications with little or no on-site IT staff, edge computing systems have to be more reliable, easy to deploy and use, highly available, efficient, high performance, self-healing and affordable. 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.

Important Factors to Consider

Automation also keeps the systems running by monitoring for complex system failure conditions and by taking automatic actions to correct those conditions. 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.

Edge computing infrastructure systems need to be easy to deploy and manage because businesses with hundreds of sites cannot afford to spend weeks 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 should also run with 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.

This is the year of edge computing and it’s no surprise why the industry is turning to the trending technology. With only a small hardware footprint, edge computing acts as a high-performance bridge to the cloud, which more organizations are relying on.