Network performance is everything in today’s competitive landscape. Consumers justifiably expect services that respond to their needs quickly and are available at all times. In fact, speed is one of the most important considerations for most users, with 63 percent of mobile users stating they would abandon an app that takes more than five seconds to load. In order to meet these high expectations, organizations need to prioritize network solutions that allow them to deliver services quickly and reliably. Fortunately, the development of edge computing architecture has made it possible to deliver on both fronts.
What is Edge Computing?
Long a favored buzzword within the tech industry, the basic concepts of edge computing are quite simple. Edge computing architecture shifts key processing tasks away from a centralized location and pushes them to servers and devices on the outer “edges” of the network. Under this framework, much of the data being gathered from edge endpoints never makes its way back to the network core for processing and analysis. Instead, this data is processed almost immediately by local computing resources, allowing devices and applications on the edge to react to changing circumstances and shifting demand very quickly.
True edge computing was made possible in recent years thanks to three innovative technological developments. The first of these developments is cloud computing, which succeeded in breaking the longstanding connection between hardware and software and completely redefined the way organizations view data management. While the distributed nature of edge computing is often held up in contrast to the more centralized aspects of cloud computing, the truth is that edge computing relies heavily upon cloud computing principles.
The second innovation is the rapid increase in the processing capabilities of devices on the network edge. Internet of Things (IoT) devices that maintain a constant internet connection to other devices and systems grow more powerful every year, allowing them to perform more and more processing tasks on their own without having to rely on transmitting data back to distant servers for analysis. Smartphones are perhaps the best example of this trend. Even when disconnected from their core network, these devices are still able to gather information and respond to it independently.
Expanded wireless connectivity provided the final piece of the edge computing puzzle. With the development of 4G and 5G cellular technology, it’s easier than ever for organizations to integrate IoT devices into their cloud networks to expand their edge capabilities. When paired with flexible edge data centers and even mobile micro data centers, these devices are helping to revolutionize industries like manufacturing and healthcare while also empowering the smart cities of the future.
5 Benefits of Edge Computing
1. Enhanced Speed
From a performance standpoint, edge computing is able to deliver much faster response times. That’s because locating key processing functions closer to end users significantly reduces latency. In traditional networking, data is typically collected on the edge and transmitted back to centralized servers for processing. If a response is needed, these servers then send instructions back to devices on the edge. But with edge computing frameworks, this processing is handled much closer to the source of the data. Devices can respond much faster since they spend less time waiting for data packets to traverse the distance from the edge to the core and then back again.
2. Bandwidth Relief
By keeping more data on the network edge, the overall volume of traffic flowing to and from central servers is reduced. That frees up much needed bandwidth throughout the entire system as a whole, eliminating troublesome bottlenecks and unnecessary processing tasks. For the growing number of organizations managing data-intensive digital media services, the ability to cache high-demand content in regional edge servers puts far less strain on the broader network. End users get the benefit of faster performance since their local network isn’t competing with other regions for limited bandwidth resources.
3. Improved Data Management
Data gathered on the network edge is incredibly valuable because it contains valuable insights into user behavior. Unfortunately, much of that information is also useless “noise,” which is why powerful analytics tools are needed to process that unstructured data to identify meaningful trends. Networks typically transmit all information gathered on the edge back to centralized servers capable of sifting through massive troves of big data. A well-designed edge computing network, however, can use a combination of local devices and edge data center resources to better manage that data. Rather than transmitting all of that data back to the core, edge networks can process some of it locally and only pass on certain types of information. This frees up valuable processing resources throughout the network and greatly improves the quality of data insights generated by big data applications.
4. Better Security
Although edge computing expands the overall network surface area and increases the number of end points, this doesn’t necessarily mean there are more vulnerabilities to exploit. While it’s obviously important that IoT edge devices are properly secured, the distributed nature of edge networks makes them much more difficult to compromise. If a breach occurs in one area, the compromised portions of the network can be cordoned off without having to shut everything else down. Organizations can also leverage the additional processing resources of the edge network to improve their threat analysis data, which allows them to identify and respond to potential cybersecurity threats much more quickly
5. Improved Reliability
Since edge computing architecture distributes processing tasks throughout the network, it tends to be more resilient than more centralized systems. In a traditional network, everything goes down when the main servers experience downtime because all services and applications rely on them for instructions and processing. Edge computing frameworks, on the other hand, are far less consolidated. Even if the core servers are forced to go offline briefly, many essential services can still be delivered on the edge thanks to a combination of local processing and regional edge data centers. This is incredibly important for use cases involving healthcare and autonomous vehicles, where even a few seconds of downtime could quite literally cost lives.
The Role of Data Centers and Cloud Services in Edge Computing
In order to implement dynamic edge computing networks, organizations will need to expand their use of regional data centers and be more strategic about how they utilize cloud computing resources. If they rely on bare metal servers, they can start expanding their edge capabilities by placing those assets within colocation facilities that are closer to their end users. This is especially important for companies looking to expand their services into growing markets far from more established data center hubs.
The same strategy applies to organizations that rely more heavily on cloud computing services. Rather than simply provisioning generalized cloud resources, companies can improve their edge capabilities significantly by choosing where they’re utilizing those resources. Deploying applications, virtual machines, and storage in cloud data centers closer to target markets brings the same benefits as placing physical servers in those locations. At Evoque, we’re committed to helping organizations deploy their applications and services in the most effective way possible. With our combination of distributed colocation, cloud onramps, and cloud engineering services, our infrastructure has the flexibility to get you to the edge quickly to deliver a better experience for your customers. To learn more about how we can improve your enterprise’s network performance, talk to one of our solutions experts today.