Examining the State of Edge Computing in 2021

20 Jul 2021 by Datacenters.com Cloud

What is Edge Computing?

Edge Computing is a term whose meaning depends on the person you’re asking. For some, edge computing means the rapid deployment of IoT solutions. For others, it means a home base for business-critical data to be processed for connecting to the cloud. One of the most appealing aspects of edge computing is the fact that it constantly shifts and changes shape to accommodate the needs of each particular business.

The last few years have shown that edge computing is beginning to gain steam. Enterprise businesses are starting to see the value in splitting their data loads between carrier hotels and remote locations by placing the larger compute footprint in data centers that offer greater scalability. The increased desire for edge computing has led to a boom in the data center construction market

To keep things simple, for the purposes of this article we’ll refer to edge computing as the practice of bringing computation and data storage closer to the devices that will be utilizing them. Anything that generates massive amounts of data and needs to analyze that data in real time would be a strong candidate to utilize edge computing solutions. Some examples of this would be self-driving cars, augmented reality, or wearable devices that measure a user’s biometrics.

This is a radical shift from past standards of relying on a central location that may be very far away for your users. Having data physically closer to your users allows them to access it faster, enhancing their experience on your platform.

The Devil is in the Details

The underlying goal of edge computing is to reduce latency or the time it takes for an application to execute a command. These are goals that IT departments across business sectors share, so why hasn’t edge computing adoption taken off like a rocket? Before it can become a mainstream solution that the majority of enterprises deploy, there are several kinks that need to be ironed out.

The first issue that needs to be addressed is the ability to scale. Some edge deployments utilize hundreds of thousands of nodes and clusters that have to be managed in extremely remote locations. In some instances, these rural locations have little to no IT support staff on-site. Ideally, you would want a centralized way to manage and deploy these types of solutions or else it would be too costly and complicated for many organizations.

Customization and consistency are two other issues that frequently pop up with edge deployments that need to be accounted for. Edge computing solutions vary so much from client to client that it’s very difficult for a provider to build out an edge stack. This places the burden on customers to figure out a way to ensure that they have interoperability between multiple vendor hardware and software environments. As far as consistency is concerned, it’s extremely difficult to manage all of these deployments if they don’t share a single control panel. Ideally, you’d want an environment where you develop an application once and deploy it everywhere it’s needed without any additional changes. 

5G and Edge Computing

5G is a technology that has the ability to drive edge computing to new heights. The nature of 5G makes edge computing more critical to providers than ever before. Edge Computing and 5G are technologies that go hand in hand, each complementing the other. 5G technology boosts speeds up to ten times faster compared to 4G and edge computing assists with reducing latency by bringing compute closer to the end user. For organizations looking for the fastest speeds and lowest latency, the marriage of these two technologies is a match made in heaven.

5G and edge computing are two technologies that will be forced to develop alongside one another in the years to come. The main reason revolves around the latency targets that have been set for 5G deployments. Improvements to just the radio interface alone will not accomplish these lofty goals. Edge computing will need to be utilized in order to hit the lofty benchmarks that have been set. 

As more carriers begin to deploy 5G networks, edge compute infrastructure will be able to offer faster real time processing for devices like mobile phones and IoT devices, as opposed to solely processing data in the cloud. Improvements to one solution will lead to streamlined processes with the other.

The Bleeding Edge

What does the future hold for edge computing? Healthcare and enterprise scale manufacturing are two business verticals where edge computing is currently undergoing a rapid evolution.

For companies that manufacture massive quantities of products and need to warehouse them, the use of autonomous robotics is growing fast. Solutions of that nature require large amounts of data that need to be recorded and analyzed in real time, a task perfectly suited for edge computing. The solutions that exist for these kinds of problems are still in the early stages. There will be hiccups along the way but once these processes become more well defined, we’ll see a plethora of edge computing deployments that manage the automation of warehouses and processing plants.

As the healthcare industry becomes more digitally oriented the need for edge computing will explode. A modern healthcare setting consists of countless wireless devices that are constantly monitoring and relaying data back to clinicians. Connecting all of those devices to one network and getting information to users quickly is exactly the kind of problem that edge computing is designed to solve. As we saw during the COVID-19 pandemic, the prevalence of telehealth is on the rise and will only become more popular in the coming years. The need for edge computing within the healthcare sector will only grow as the new normal for clinicians will involve a hybrid approach that combines on-site and virtual appointments.

As of now, the future of edge computing is wide open. The Edge will soon converge with massive amounts of data thanks to artificial intelligence and machine learning, allowing companies to find actionable insights in the large amounts of data that they house. Once Edge computing solutions become more streamlined applications will be able to be placed seamlessly with consistency and ease.


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