Picture the following. You are lying in the intensive care unit of an area hospital having just gone through the ordeal of major open-heart surgery. The IC medical staff is depending on medical IoT devices to monitor you. Question, do you feel better having your collected data make the journey across the Internet for analysis at a distant cloud location, or analyzed in near instant fashion at the hospital itself where the medical staff is?
Chances are you would pick the latter. This is what edge computing is all about. It is about retaining data, analyzing and processing it where it resides—at the edge. It is an analytical approach yet does not involve sending data to a centralized cloud by default as we have recently grown accustomed to. While the cloud sufficiently serves as the collector and processor for consumer IoT, it has its limitations when it comes to enterprise IT. This is especially the case for industries such as smart manufacturing and healthcare. The fact is that most traditional networks were not designed for an IoT dominated world. If your data lives on the edge, shouldn’t your processing reside there as well?
Explore the TOP 5 Reasons why you need Edge Computing
- Location matters
- Getting it right ASAP
- Edge computing reduces costs
- Edge computing is more secure
- Be closer to your customers
Let’s dig into each reason a little more…
1. Location Matters
Most people want to live as close as possible to their work to shorten their commute. Amazon manages regional warehouses designed to get products quickly to their customers. Location matters. That is why 33 percent of IT decision makers plan to invest in new edge computing technology over the next two years. (Source: IDG Research commissioned by WEI, 2019.) Just as IT moved from a centralized mainframe model to a decentralized client/server model, companies are realizing the power of distributing their intelligence-driven IoT functions at the edges, rather than depend on a centralized cloud collector. The laws of distance apply the same whether you are commuting to work or transmitting data to a centralized cloud. Distance increases latency. Connected data drives intelligence-based insights today, which drive decisions and create greater value. For many enterprises, these generated insights need to be derived as close to real time as possible to attain optimum analytical decision-making. This means data needs to be analyzed and processed as close to its data source as possible.
2. Getting it Right ASAP
Here is another universal truth. The sooner you can correct a problem, the better. It takes less time and expense to correct a problem early on. Think of a manufacturing operation that utilizes sensors to detect issues in quality control. The ability to implement a near instant remedial response to a serious fault detection provides great value. When you think about it, does it really make sense to send all of your sensory data to a cloud collector far away when the remedial processes that are driven by those analytics take place back where the data originated? While it was necessary at one time to send all sensory data on a needless round trip due to the lack of storage and processing power to act on that data, that is no longer the case today. In an environment of razor thin margins and extreme competitiveness, companies cannot always wait for data to loop to and from the cloud. Edge computing can act on process anomalies and initiate line shutdowns immediately upon discovery. Edge computing can also potentially save the life of a patient when the seconds count most.
3. Edge Computing Reduces Costs
The pipe is not free. It costs money to send data from endpoint to edge to cloud and back. Think about the amount of data that a single IoT device such as a camera can produce in a 24-hour period. Now multiple that by hundreds, even thousands of devices. All of that data then aggregates to your data center to complete its journey to the cloud. Consider the bandwidth it takes to support all of that. Now consider the added stress on your network. Only a small percentage of that traffic can be acted on, yet it consumes bandwidth that other higher value traffic might need. Then of course, there is the cost of storing all of that data, much of which will never be used. At the very least, edge computing can help by identifying what information is useful for additional processing in the cloud. The efficiencies that edge computing introduces to your network helps reduce costs on a daily basis.
4. Edge Computing is More Secure
Yes, we are all aware of the security challenges of legacy IoT devices, but edge computing is different. Edge devices are now built with embedded functionality, not only when it comes to machine learning and analytics, but security as well. One of the things that the ubiquitous prevalence of data breaches has taught us is that any centralized congregation of data is a tempting target for hackers today. The localization of data processing not only quickens response times and optimizes the efficiencies of data transmission, it increases security as well.
5. Be Closer to Your Customers
While an exclusive reliance on cloud-based analytics by internet-based retailers may make sense, it isn’t so much the case for traditional or multichannel retailers. That is because a large block of their customers are on-premises, shopping in their stores. Edge computing allows retailers to provide better responsiveness to their customers, whether it be helping them find a product or issuing them a timely coupon based on where they reside in the store.
Edge Computing Makes Sense
When it comes to today’s enterprises, the phrase ‘living on the edge’ does not equate to perilous behavior. The edge is where so much happens today. An edge computing architecture and strategy can reduce latency and costs, while increasing dependability and responsiveness to your operations and customer service. When you add it all up, edge computing just makes sense today.
Next Steps: Find out if your enterprise is ready for the edge in this video we created in partnership with Dell Technologies.