Edge computing is going to change your business, and you may not even know it yet. As businesses move towards deep learning initiatives and connect relevant products in the Internet of Things ecosystem, edge computing could help reduce latency and increase productivity.
So what is it?
Let’s take a look at what this buzzword means and how it could change your business operations in the next few years.
What is Edge Computing?
In the early days of computers, there were centralized computers that performed the bulk of work on-site. Then, personal computers built out from “dumb” terminal concepts allowed us to take our computing power home. Everything was self-contained (remember Encarta?)
Now, just about everyone uses centralized data repositories such as Dropbox or Apple Cloud Storage for hand-off, and that cloud allows us to use centralized storage hubs in which a handful of cloud providers house and process all the info.
With edge computing, we process data closer to the data source. The cloud remains the cloud, but instead of a centralized repository in which data travels a long distance, the cloud comes closer to where you are. This is the world of edge computing.
Why Consider Edge Computing?
Think of the internet like a city. In the early days when there were a few thousand people, there was very little traffic, so walking a package from your house to your customer’s house happened smoothly with few obstacles. The package contained sensitive materials, so you processed it yourself. You could do that without huge wait times because few people stood in your way as you delivered it. All told, let’s say you had an investment of about 20 minutes each time.
30 years later, that city is a multi-million person metropolis. You’ve moved from walking the package from your store to your customer’s house to biking to driving. There are so many people and so many obstacles that it can take up to an hour. It’s not practical because you expend more energy than what you make on the package and your customer is always frustrated. You could send the package through a delivery service and save your own resources, but the wait time is still an hour and the package is still too sensitive to hand off.
You can’t find a faster way to move the package; you’ve maxed out your transportation here. So, you do something radical. You set up a smaller hub filled with what your customer wants. That hub is once again, 20 minutes walking distance. Did your product or store change? No. The store, the package, the customer are all the same. What changed is where the processing first takes place.
The internet is like that city. With big data gathered from millions of IoT products in real time, it no longer makes sense to ship all that data to a centralized place for processing. Instead, edge computing allows the cloud to move closer to where your data sources are located. It removes barriers and reduces latency.
Some terms you should know for this type of computing are:
- Edge device: anything that produces the data you collect
- Edge: refers to where the data originates and varies depending on the field. In IT, this could be a laptop. In manufacturing, it could be an IoT connected machine on the production line. You need to understand “edge” in a field-specific way.
- Fat/Thin client: refers to the type of software in the edge device. Thin clients merely transmit data. Fat clients are capable of processing it (to some extent) first.
- Edge gateway: This is the barrier between your edge computing and the broader cloud network. It’s important to know for integration purposes.
What Are The Benefits?
Data allows you to act more intelligently but shipping all your data to one repository makes no sense. Instead, edge computing gives you more efficient processing in the same way our fictional business gave up trying to move across town more quickly.
A mesh network of computing puts data centers closer to your data sensors. If your connectivity is unreliable, edge computing helps gather and share data with greater efficiency. It processes your data before shipping it out.
You may hear edge computing referred to as the “cloud killer,” but in reality, it’s an evolution of the cloud. Organizations will still use the cloud to store processed data or for operations that aren’t latency sensitive while reserving edge computing for real-time analytics.
Businesses using edge computing could see the following improvements in workflow.
- Lower latency: in an era when speed is key, edge computing solutions offer higher speed collection and processing.
- Better security: information doesn’t have to transmit to the cloud before it’s appropriately anonymized or scrubbed.
- Lower bandwidth: Information coming from a single source isn’t going to tax your bandwidth when heading straight to the cloud. If you’ve got 100 devices all transmitting the same data to the cloud, however? Problem. If your devices are smart enough to process data and only send the absolute relevant data to the cloud for storage, you’re saving yourself a lot of bandwidth.
Who Should Use Edge Computing?
Companies that rely heavily on data gleaned from IoT devices would see the most significant benefit from adding edge computing to the game plan. As data comes in from internet connected devices, processing that data could be a nightmare if you’re relying solely on a central location/processing center.
Organizations with highly sensitive data should also be looking to edge computing. While the cloud is often more secure than localized storage solutions, edge computing can provide a hybrid solution. Sensitive information has a chance to process and anonymize before being moved to cloud storage. Similar to holding your cards close but eventually everyone’s cards get returned to the stack.
Build Edge Computing into Your Digital Adoption
If you’re dealing with data from IoT or sensitive data, you may want to consider edge computing solutions as part of your digital adoption strategy. Moving to the cloud as an IoT connected business model could be highly problematic as you begin gathering data and scaling devices. Instead, edge computing could help keep your costs down and build processing capabilities that maintain speeds you expect from this era.