What is Edge Computing?
From an IT perspective, computing has become both exponentially more flexible and complicated.
21:16 23 December 2019
Why? There are a number of driving forces behind this including containers, virtualization, the cloud, and the IoT.
These types of technology not only drive innovation, they make it possible to achieve things no one ever thought possible, not even those in IT. But even with all the advantages, they also come with a number of challenges, especially from the deployment standpoint. However, from the end-user perspective, things like the cloud have made life incredibly easy.
Easing the lives of end-users is what it’s all about, right?
Giving users a centralized location to house data and run applications makes computing life simple and seamless. Think of Android smartphones. These devices move between clouds, connect to IoT devices so easily that users aren’t even aware it’s happening until a thermostat changes, a door unlocks, photos are automatically uploaded, or they’re logged into various accounts.
The biggest part of a consumers’ computational day takes place in the cloud. In fact, the world now relies on cloud-based infrastructure. It houses and processes our data, and connects our devices. And with the help of applications designed by the likes of Python software development teams, data processing has become more efficient and flexible than ever.
However, it’s the processing of data and the connecting of devices to a centralized data center that is of utmost importance. And that’s where edge computing comes into play.
Let me explain.
What is the Edge?
The edge is about geographical distribution, not a geographical limitation. So long as there’s an internet connection, the cloud can stretch across the globe. But although that cloud can cast a vast net you don’t want every single bit of data processing to happen at the heart of the cloud.
Why? Two reasons. First, you’d have to transfer the data all the way back to the main servers. Second, processing it would take valuable CPU resources that could be better used doing cloud-centric things (like storing, syncing, and securing your data).
So what do you do? You take processing to the edge.
Effectively, edge computing is all about processing data at its source. Let’s say, for example, you have either a computer or IoT device that collects data from users. The next step in this pipeline is for the device to send the data halfway around the globe, so it can be processed at a centralized location.
What if that device is in a hospital and is crucial to saving lives? That latency between collecting the data, processing, and reporting it could make a massive difference. But what if the device that collects the data does its own processing and then syncs it to the cloud?
What about autonomous vehicles? Driverless cars, trucks, buses, and trains need their onboard processors to make millions of computations with unrivaled speeds, otherwise, people could get injured, products could get damaged, and work could fall incomplete. To make these vehicles work properly, they need to process information on board, work with the data, and then send it to the centralized location.
That’s the heart of edge computing. And in certain cases, it brings an unheard-of level of efficiency and safety.
Benefits of Edge Computing
So we already know that edge computing makes processing data more efficient. What other benefits does it bring? One major one is security. Think about it this way: instead of sending data packets to a data center for processing and back to the collecting device, you send them only once - after they have been processed.
The less data you transmit, the less likely it’s going to be stolen. It doesn’t mean it’s 100% guaranteed, but the likelihood of a hijacking is reduced.
Another benefit is distributed processing. Instead of relying on a single data center to process massive amounts of data, numerous edge devices take care of it. This removes a significant load from the data center. When you take into consideration that thousands upon thousands of businesses might be using the same cloud as you, that distribution of data processing becomes important.
There’s also a cost saving associated with edge computing. Think about it this way: if your business has to process a number of data types, not all of them must be processed in the same fashion. Edge computing allows you to categorize the data. So you might have mission-critical, highly sensitive data you could process on the edge and then transmit it to the data center via a highly encrypted, large data pipe for lightning-fast transmission.
All other data could be processed either on the edge and transmitted via slower pipes or sent directly to the data center for processing. This flexibility makes it possible for you to prioritize your data processing, while delivering an added layer of redundancy, thereby enjoying possible cost savings.
Edge computing also brings reliability you won’t find otherwise. Consider remote, rural areas that don’t have stable connectivity. Without edge computing, you could wind up with data loss, due to spotty connections. With edge computing, data is locally stored and processed.
That data could be held in local storage until the device has a reliable connection. Once the connection is solid, data is transmitted. In this instance, edge computing is more capable of preventing lost data packets due to poor connectivity.
We are really only now on the cusp of edge computing. Given the rate at which this technology is being explored and deployed, it’ll only be a matter of time before edge computing is widespread. So if your company depends on the collection of data in a remote location and the processing of data in a centralized location, edge computing should be on your radar.