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Edge Computing Eats the Cloud?

Edge computing was previously pegged as edgy. Now it’s ubiquitous. Here’s why -- and where it’s taking a big chomp out of cloud’s lofty turf.

Pam Baker

March 2, 2023

4 Min Read
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Kadumago via Alamy Stock

Edge computing isn’t a panacea, but its timing is impeccable. The cloud is too slow to meet the needs of most edge devices making it necessary to move computing closer.

“Latency is the big killer of cloud computing, especially public cloud computing,” according to John Annand, research director of infrastructure and operations at Info-Tech Research Group. Jeff Ready, CEO and co-founder of Scale Computing agrees, predicting that “orchestrated edge systems will become a viable public cloud alternative.”

That may be a jagged pill to swallow for some organizations who recently banked everything in the cloud or are in the process of doing so. It’s likely bitter medicine for public cloud owners, too.

“By clustering together fleets of autonomously managed edge-computing platforms and distributing them close to where users live, organizations will be able to benefit from cloud-like convenience without having to compromise on performance,” Ready says.

But using edge computing in this way is not a farfetched idea. It isn’t even a novel notion.

“Edge computing is all about ubiquity; lots and lots of little edges in a huge variety of use cases but with centralized control and data management. Fog used to be the common term, but edge sounds catchier. It also sounds an awful lot like distributed computing from the 70s: Everything old is new again when it comes to IT. Well -- this vision is close to becoming a reality,” Annand explains.

Use Cases Edging Out the Cloud

So where is the emerging evidence that this edge-computing takeover is in progress?

“Edge computing provides the ability to run near-real-time data collection, analytics, decision-making and execution,” explains Matteo Gallina, principal consultant with global technology research and advisory firm ISG. So, look for it to be wherever there is an advantage in instant outputs.

Specifically, one can see edge computing hard at work in different roles suited for each industry. According to Arpan Tiwari, managing director at Deloitte Consulting, examples include the following:

  • In telecommunications, it enables the enhancement of content delivery networks and allows for deploying virtual network functions for upcoming 5G deployments.

  • In manufacturing, it enables establishing smart, efficient production lines and warehouses through advanced robotics and sensor fusion (real-time analytics and action based on IoT/ sensor data).

  • In transportation and logistics, it enables automatic guided vehicles (AGV) and self-driving cars, as well as advances in freight monitoring and intelligent transportation systems, etc.

  • In retail, it enables a reimagined customer experience via smart mirrors, intelligent shopping carts, self-checkout, digital signages, targeted advertising, and real-time inventory tracking and replenishment.

But that’s nowhere close to the end of where edge computing will reign long term.

“While the focus today is on establishing the core infrastructure (private LTE/5G) along with basic use cases, some of the more advanced and transformative use cases will come to fruition over the next three to five years once the core infrastructure is in place,” says Tiwari.

Low Entry Bar for Edge

Meanwhile, cheap data collection, better power usage, and existing networks and prevalent devices present endless possibilities.

Take Russian-owned Dragon Tree Labs for an example of how IoT computing enabled devices can and are multi-purposed or repurposed for a new end.

According to Ilya Sedoshkin, the founder and CEO of Dragon Tree Labs, its WeHead device for spatial video presence is made of four smartphones. Together the phones mimic the head movement of the remote person and “create a feeling of physical presence for the interlocutor.”

“There are reasons why we use smartphones for edge computing. The price of smartphones and their computational power are close enough to the specialized chipsets explicitly created for neural network applications. Many engineers and developers have skills in developing applications for mobile platforms. The development of smartphone applications is faster; the libraries are more mature and less buggy,” Sedoshkin says.

Additionally, Sedoshkin says that smartphones are “more compact” than a set of GPUs and peripheral components make more sense in an R&D lab environment.

He predicts this trend will continue to intensify. “Many real-world applications require the usage of a smartphone anyway, and these devices are capable of running pre-trained neural networks on edge. Smartphone manufacturers will continue increasing computational power and memory capacity on edge devices. However, R&D labs will use specialized hardware for training and testing AI/ML algorithms, and DIY enthusiasts will use specialized lightweight chipsets," Sedoshkin says.

In short, there is little to stop the encroach of edge computing on the cloud’s lofty turf. There isn’t much friction to slow it down, either.

“The future of edge computing is an evolving landscape; however, ‘ubiquitous’ is the best word that describes it because it will evolve to be all around us,” Tiwari says.

And by ubiquitous, industry watchers say they literally mean everywhere.

“Given the many scenarios where internet connectivity is unavailable or sporadic, for example cruise lines, offshore oil rigs, and remote hospitals, we’ll likely see more edge-optimized databases with offline first capabilities in the future, and any company that foresees there being a major interruption in their service due to latency issues will benefit from edge computing,” says Wayne Carter, vice president of engineering at cloud database provider Couchbase.

In the end, edge computing eats the cloud. Or, at least enough of it that the business climate changes permanently.

What to Read Next:

3 Tips for CIOs: Pitching Edge to Your Organization

Enterprise Guide to Edge Computing

Will Edge Computing Kill the Cloud?

About the Author(s)

Pam Baker

Contributing Writer

A prolific writer and analyst, Pam Baker's published work appears in many leading publications. She's also the author of several books, the most recent of which are "Decision Intelligence for Dummies" and "ChatGPT For Dummies." Baker is also a popular speaker at technology conferences and a member of the National Press Club, Society of Professional Journalists, and the Internet Press Guild.

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