What is Edge Computing?
Traditional cloud computing networks are highly centralized, with data being gathered on the outermost edges and transmitted back to the main servers for processing. This architecture grew out the fact that most of the devices located near the edge lacked the computational power and storage capacity to analyze or process the data they collected. Even as more devices became capable of connecting to networks over cellular and WiFi, their functionality was relatively limited by their hardware capabilities.
All of that has changed in recent years thanks to the miniaturization of processing and storage technology. Today’s IoT devices are quite powerful, capable of gathering, storing, and processing more data than ever before. This has opened up opportunities for companies to optimize their networks and relocate more processing functions closer to where data is gathered at the network edge, where it can be analyzed and applied in real time much closer to intended users.
Since the data doesn’t have to travel all the way back to the central server for the device to know that a function needs to be executed, edge computing networks can greatly reduce latency and enhance performance. The speed and flexibility afforded by this approach to handling data creates an exciting range of possibilities for organizations.
Top Business Benefits of Adopting Edge Computing
For many companies, speed is absolutely vital to their core business. The financial sector’s reliance upon high-frequency trading algorithms, for instance, means that a slowdown of mere milliseconds can have expensive consequences. In the healthcare industry, losing a fraction of a second can even be a matter of life or death. And for businesses that provide data-driven services to customers, lagging speeds can frustrate customers and cause long term damage to a brand. Speed is no longer just a competitive advantage—it is a best practice.
The most important benefit of edge computing is its ability to increase network performance by reducing latency. Since IoT edge computing devices process data locally or in nearby edge data centers, the information they collect doesn’t have to travel nearly as far as it would under a traditional cloud architecture.
It’s easy to forget that data doesn’t travel instantaneously; it’s bound by the same laws of physics as everything else in the known universe. Current commercial fiber-optic technology allows data to travel as fast as 2/3 the speed of light, moving from New York to San Francisco in about 21 milliseconds. While that sounds fast, it fails to consider the sheer amount of data being transmitted. With the world expected to generate up to 44 zettabytes (one zettabyte equals a trillion gigabytes) of data in 2020, digital traffic jams are almost guaranteed.
There’s also the problem of the “last mile bottleneck” which data must be routed through local network connections before reaching its final destination. Depending upon the quality of these connections, the “last mile” can add anywhere between 10 to 65 milliseconds of latency.
By processing data closer to the source and reducing the physical distance it must travel, edge computing can greatly reduce latency and result is higher speeds for end users, with latency measured in microseconds rather than milliseconds. Considering that even a single moment of latency or downtime can cost companies thousands of dollars, the speed advantages of edge computing cannot be overlooked.
While the proliferation of IoT edge computing devices does increase the overall attack surface for networks, it also provides some important security advantages. Traditional cloud computing architecture is inherently centralized, which makes it especially vulnerable to DDoS attacks and power outages. Edge computing distributes processing, storage, and applications across a wide range of devices and data centers, which makes it difficult for any single disruption to take down the network.
One major concern about IoT edge computing devices is that they could be used as a point of entry for cyber attacks, allowing malware or other intrusions to infect a network from a single weak point. While this is a genuine risk, the distributed nature of edge computing architecture makes it easier to implement security protocols that can seal off compromised portions without shutting down the entire network.
Since more data is being processed on local devices rather than transmitting it back to a central data center, edge computing also reduces the amount of data actually at risk at any one time. There’s less data to be intercepted during transit, and even if a device is compromised, it will only contain the data it has collected locally rather than the trove of data that could be exposed by compromised server.
Even if an edge computing architecture incorporates specialized edge data centers these often provide additional security measure to guard against crippling DDoS attacks and other cyberthreats. A quality edge data center should offer a variety of tools clients can use to secure and monitor their attacks.
As companies grow, they cannot always anticipate their IT infrastructure needs, and building a dedicated data center is an expensive proposition n addition to the substantial up-front construction costs and ongoing maintenance, there’s also the question of tomorrow’s needs. Traditional private facilities place an artificial constraint on growth, locking companies into forecasts of their future computing needs. If business growth exceeds expectations, they may not be able to capitalize on opportunities due to insufficient computing resources.
Fortunately, the development of cloud-based technology and edge computing have made it easier than ever for businesses to scale their operations. Increasingly, computing, storage, and analytics capabilities are being bundled into devices with smaller footprints that can be situated nearer to end users. Edge systems allow companies to leverage these devices to expand their edge network’s reach and capabilities.
Expanding data collection and analysis no longer requires companies to establish centralized, private data centers, which can be expensive to build, maintain, and replace when it’s time to grow again. By combining colocation services with regional edge computing data centers, organizations can expand their edge network reach quickly and cost-effectively. The flexibility of not having to rely upon a centralized infrastructure allows them to adapt quickly to evolving markets and scale their data and computing needs more efficiently.
Edge computing offers a far less expensive route to scalability, allowing companies to expand their computing capacity through a combination of IoT devices and edge data centers. The use of processing-capable edge computing devices also eases growth costs because each new device added doesn’t impose substantial bandwidth demands on the core of a network.
The scalability of edge computing also makes it incredibly versatile. By partnering with local edge data centers, companies can easily target desirable markets without having to invest in expensive infrastructure expansion. Edge data centers allow them to service end users efficiently with little physical distance or latency. This is especially valuable for content providers looking to deliver uninterrupted streaming services. They also do not constrain companies with a heavy footprint, allowing them to nimbly shift to other markets should economic conditions change.
Edge computing also empowers IoT devices to gather unprecedented amounts of actionable data. Rather than waiting for people to log in with devices and interact with centralized cloud servers, edge computing devices are always on, always connected, and always generating data for future analysis. The unstructured information gathered by edge networks can either be processed locally to deliver quick services or delivered back to the core of the network where powerful analytics and machine learning systems will dissect it to identify trends and notable data points. Armed with this information, companies can make better decisions and meet the true needs of the market more efficiently.
By incorporating new IoT devices into their edge network architecture, companies can offer new and better services to their customers without completely overhauling their IT infrastructure. Purpose-designed devices provide an exciting range of possibilities to organizations that value innovation as a means of driving growth. It’s a huge benefit for industries looking to expand network reach into regions with limited connectivity.
Given the security advantages provided by edge computing, it should not come as a surprise that it offers better reliability as well. With IoT edge computing devices and edge data centers positioned closer to end users, there is less chance of a network problem in a distant location affecting local customers. Even in the event of a nearby data center outage. IoT edge computing devices will continue to operate effectively on their own because they handle vital processing functions natively.
By processing data closer to the source and prioritizing traffic, edge computing reduces the amount of data flowing to and from the primary network, leading to lower latency and faster overall speed. Physical distance is critical to performance as well. By locating edge systems in data centers geographically closer to end users and distributing processing accordingly, companies can greatly reduce the distance data must travel before services can be delivered. These edge networks ensure a faster, seamless experience for their customers, who expect to have access to their content and applications on demand anywhere at any time.
With so many edge computing devices and edge data centers connected to the network, it becomes much more difficult for anyone failure to shut down service. . Data can be rerouted through multiple pathways to ensure users retain access to the products and information they need. Effectively incorporating IoT edge computing devices and edge data centers into a comprehensive edge architecture can therefore provide unparalleled reliability.
CDNetworks Edge Computing Platform (ECP) enables customers to meet growing business demands by effortlessly deploying and scaling up container-based applications, resulting in ultra-low latency, high bandwidth/high performance computing. ECP places high-performance compute, storage and network resources as close as possible to end users. Doing so lowers the cost of data transport, decreases latency, and increases locality. ECP is a container orchestration system built on Kubernetes and Docker for customers to write container-based applications once and deploy them everywhere.