The Internet of Things and the growing list of devices we use on a daily basis is driving monumental changes in computing. In Cisco’s latest Global Cloud Index, the company forecasts that by the end of 2021, our collective devices will create 847 zettabytes (847 trillion GB) of data per year. Cisco also projects annual global data center IP traffic to reach 20.6 ZB.
At such staggering volumes, data cannot be effectively managed, analyzed, and stored in traditional enterprise data centers or the cloud. Even today, businesses are struggling to ensure their overall network performance with dated methods. Our modern environment requires modern, advanced approaches to computing. It’s why 79% of IT teams are prioritizing putting content closer to their customers. It’s also why edge computing is becoming an increasingly popular solution.
The edge is the point at which traffic enters and exits your network. It’s also where the underlying data transport protocols may change. Edge computing allows your network to process information at or near the point of its origin, whereas traditional data centers and cloud computing required data to travel to the center of your network and back.
Edge computing takes the method of localized processing a step further – including devices themselves and local edge data centers on your network. In effect, edge computing integrates core cloud services with those of a truly distributed data center.
By placing key data, workloads, services, and applications at the edge of your network – and closer to your users – you increase the speed of your network and reduce latency. With edge computing, devices can also determine what data should be stored and processed locally and what needs to be sent to a local node or the cloud for additional use. From smartphones, tablets, and laptops to IoT devices and sensors, edge computing helps to minimize the bandwidth used between these devices and your central data center.
By minimizing or eliminating the need for computing at the center of your network, you can protect against major bottlenecks and points of failure. Without mass volumes of data moving from the edge to center and back, you’ll improve your network performance, reduce your transmission costs, and even promote scalability into the future.
Moving such key operations to the edge of your network give users virtually-instant access to content. It allows IT teams to strategically choose where different data sets are processed to maximize the speed of their network. While long-term processing needs can be managed by a facility farther from users, business-critical data can be processed at an edge data center. The shorter distance between your users and critical operations helps you use your bandwidth more efficiently, minimize latency, and improve your network’s reliability.
Previously, only large corporations and government organizations leveraged edge computing. But faced with the the explosion of data and increasing demands for speed and mobility, many IT leaders are turning to this solution.
According to BI Intelligence, the manufacturing, utilities, energy, and transportation industries are expected to adopt edge computing first, followed by smart cities, agriculture, healthcare, and retail. Key adopters are also businesses offering commercial internet application services – from social networks to ERPs and CRMs. Of course, businesses that demand near-instant data benefit from edge computing. Think of the dramatic difference mere milliseconds make with high-frequency trading algorithms used in finance and investment.
Drilling down further, edge computing is becoming the go-to strategy for a wide spectrum of technology that includes:
Edge computing is worth considering for any data-intensive tasks that can operate more efficiently when closer to your end-users or data sources. The questions you have to ask are “What functions need to move to the edge of our network now, and which will need to adopt edge computing in due time?
Download our whitepaper to learn more about the benefits of edge computing and key considerations.
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