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The Modern IT Landscape: Edge, Cloud, and Fog

During the cloud boom of the past decade, we’ve seen organizations across the board migrate much of their on-premise infrastructure to remote data centers. While this new architecture has proved pivotal for applications spanning from collaboration tools to big data analytics, we’re now seeing a shift in the other direction: many companies, especially manufacturers, are bringing their computing power back into their in-house devices.

While edge computing brings advantages that we cannot realize with cloud computing alone, we shouldn’t think of cloud and edge as opposed or even separate. These two distinct compute locations are, in fact, complementary; each side makes up for the other’s shortcomings, and this makes them both essential parts of today’s information systems.

Just as a general must strategize to win a war while also focusing on tactics to emerge victorious from a battle, we can think of cloud and edge computing in an analogous way. Edge computing is on the front lines, handling the day-to-day operations, while cloud is better for long-term purposes like data storage and advanced analytics because computing resources are so much cheaper and more plentiful.

Let’s look at a couple of ways that we can combine edge and cloud computing to form a whole that’s greater than the sum of its parts. Going back to our SCADA example from earlier, we’ll use edge computing for real-time control while simultaneously sending aggregate statistics back to the cloud for analysis in order to improve that control.

Ishikawa explains, “One architecture, for example, would use the SCADA system as a source of information for a machine learning infrastructure in the cloud, such as TensorFlow. Time-series data along with alarms and events could be used to train a model to detect possible failures. The training occurs in the cloud… Once you have a trained model, the processing can go back to the edge.”

Essentially, we’ll train the AI by using the cloud’s resources then ship the model back to the edge for implementation.

Another example from Beth Stackpole of Automation World is “an offshore wind turbine farm with 100 units…In this case, edge processing is tapped to make critical adjustments to individual wind turbines, yet the cloud aggregates signals from the entire fleet and combines it with weather data to support an algorithm that automatically calibrates turbine speeds and blade placement for optimal fleet performance.”

As we can see from these examples, we get the best results when we let each type do what it does best. The product is a harmonious ecosystem.

Still, there’s one fact that we have yet to touch on fog computing. In between edge devices and cloud data centers sit internet gateways, programmable logic controllers (PLCs), desktop computers, and other intermediaries. Together, these devices constitute fog computing, which can act as a go-between for cloud and edge computing while also providing their own advantages that derive from their hybrid position.

Not only does fog serve as a bridge between cloud and edge, but it also spans the gap between IT and OT professionals. These devices are more abstracted than the low-level relays and other closed-loop automation tools that OT traditionally uses, and they are likewise closer to production than IT infrastructure like a cloud.


Ultimately, these compute locations live on a continuum, and, depending on what we want to do with our data, we’ll pick the right spot to run our workloads. As a general rule, the more immediate the application, the closer to the edge we want our computing to be.

And the results don’t lie. A 2019 Automation World survey found that “Half of the companies launching edge/fog or cloud computing initiatives report significant reduction in downtime. At the same time, 38 percent are enjoying measurable improvements to production output, 37 percent tout profitability increases, and 30 percent highlight a decrease in production costs.”

One thing’s for certain. As manufacturers push towards the smart factory model of industry 4.0, edge computing will remain a major role-player for turning this vision into a reality.

Published By Yuri Chamarelli

Originally published at




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