Edge Computing 101: How Does Edge Computing Differ from Cloud and Fog Computing?

Edge Computing

Driven in part by COVID lockdowns and in part by a constant stream of articles touting its benefits, cloud computing has become an everyday part of life at most businesses. The cloud isn’t without merit—its ability to combine scalability, economies of scale, and easy access to applications has pushed this delivery model out of obscurity and into the mainstream.

But the concept of the cloud is only one in a variety of delivery models. Fog computing and edge computing have continued to find a place in IT departments, offering their own benefits to end users and leaders. Especially as internet of things (IoT) devices become more popular, many organizations may find that the cloud might not be their end—but simply their beginning.

In our last blog, we discussed the idea of edge computing, exploring how the rapid adoption of IoT and the pursuant data explosion will push the concept of the edge into the spotlight while highlighting the weaknesses of the cloud. Briefly mentioning the concepts, we would today like to compare and contrast the three models and help you understand what’s right for you.

A Variety of Computing Models: Which One Works for You?

Edge Computing, Fog computing, and Cloud computing address a lot of the challenges in terms of performance, security, and cost-effectiveness. But how do they differ? We look at what each of these means and how the differences impact you.

Cloud Computing: The Familiar and Present Method

Built to provide a highly-centralized way of collecting and processing data, the idea of the cloud is all about using whatever device you have to access data. Whether you’re using a phone, tablet, computer, or other device, the premise is simple—use the device to access processing power somewhere else.

The easiest concept in understanding cloud computing is the idea of software-as-a-service (SaaS). Whether in your personal life—using Google Stadia to ‘stream’ a video game—or in your professional life, the concept is simple: Your device connects to the server, the server processes the information, and you are presented the output.

The cloud allows access wherever you have an internet connection to whomever has the credentials to access it. This allows for the greatest ability to capture big-picture data and make informed decisions based on a large variety of inputs and sources.

Challenges with the Cloud

But as with the idea of Google Stadia, the idea and the ability to execute exist on two separate planes. Processing power isn’t the concern. After all, the data is being processes in a server farm. The real challenge is latency. Each input has to travel hundreds or thousands of miles between your device and the datacenter. It then has to be processed before data travels the same distance back to you.

The cloud has its benefits in the current landscape. Many applications can work with the latency challenges. For example, a couple seconds between entering data in ERP and seeing an output is palatable. But what happens when the number of devices making requests skyrockets? Rather than a few thousand users requesting processing power, it’s millions—and the information transfer between the two runs into a traffic jam.

Fog Computing: The Misunderstood Middle

Lying somewhere between edge computing and cloud computing, the fog provides a slightly more localized (decentralized) approach than the cloud. Pitched as a way to make “connected” ecosystems more efficient, the Fog brings processing closer to the user.

The core processing power exists in a local environment, akin to a box or on-premises server. Though not entirely reliant on datacenters, much of the heavy lifting is still done remotely, helping users to have immediate access to the tools they use most often.

The term fog computing was coined by Cisco, and it defines a mix of a traditional centralized data storage system and Cloud. Computing is performed at local networks, still using decentralized servers for big picture processing. Not only does it bring processing power closer to the user, it allows for some offline access to data.

Devices can access data more efficiently, as resources and services are better distributed. In essence, as a result of fog computing, companies are able to use the computing power on nodes — between devices that collect or generate data and the official enterprise cloud platform — to quickly generate insights and make decisions that matter.

The Edge: Closest to the User, Minimal Latency

If the cloud provides centralized processing and the fog offers local processing, the edge offers direct processing. An idea implemented to bring processing power as close to the requester as possible, much of the calculation is done on the device itself.

It starts with a disparate network topology: One system on–premise; a couple in the Public Cloud – AWS, Azure, Google, and sometimes all 3; a couple of legacy systems co-located in data centers managed by a 3rd party; and then more recently, mission-critical applications hosted on  SaaS platforms. All these systems and networks are vying for the edge, which ends on your laptop with information your company needs immediately to compete.

With extensive demand for processing—the internet of things will create over 90 Zettabytes of data—edge computing will reduce the traffic between processing location and the device requesting it, a necessity as the data burden proliferates.

Some activities move to the local nodes, others are sent for centralized processing, but the edge is as decentralized as possible, resulting in Edge computing promising to deliver three key benefits—speed, security, and scalability.

  • Speed: As the computation happens at the location where the data is generated, and there is no transfer of data over the network, latency is reduced, thus giving better inference time.
  • Security: By eliminating the pipeline between processing and inferences, no data leaves the device or is transmitted over the network, so there is no concern for data privacy and security.
  • Scalability: As the Edge computation increases, having edge computing data centers co-located with the devices allows organizations to scale the edge computation needs at a faster pace and still being very cost-effective.

Connecting the Dots with Virtually

If you need real-time data to complete mission-critical tasks that keep your company profitable and safe, then it’s time to tie all these systems together using Edge Computing technology.

If your company has plans to compete in markets where getting an edge on the Edge means more market share, then select a service provider that can navigate all the different products and services without costs jumping over the barrier and sending the project right over the edge.

At Virtually Managed IT Solutions, we specialize in getting companies to the Edge. Delivering support, expertise, and insights for digital transformation, our team works with you to get your company up and running. Get to know more about us, our services, and our partners—and be sure to contact us to learn more.

Additional Edge Computing Resources

Edge Computing

Playing at the Edge

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