The rapid pace of the digital era is now making businesses and infrastructure providers look beyond the cloud to deliver digital initiatives. The massive increase in smart devices, IoT, digital business touchpoints, connected vehicles, security devices, and healthcare devices has led to large trove of data which is usually deployed on the cloud. Now infrastructure providers have realized that the cloud is not enough. Enter edge computing, which enables data produced by internet of things (IoT) devices to be processed closer home.

A new report released last week by Gartner predicts that by 2021, 65% of global infrastructure service providers will generate more than half of their revenue through edge-related services. This is because businesses are becoming increasingly reliant on customer interaction through digital touchpoints. The Gartner report and survey indicates that by the end of 2019, 70% organizations said they would consider edge computing to be relevant to their business infrastructure. By 2022, 50% of large organizations said they will have to integrate edge computing principles in their ecosystem.

What is edge computing

Edge computing provides server resources at the intersections of users and the cloud. This allows faster processing of data produced by IoT and connected devices instead of sending it across to data centers in the cloud. Edge computing enables real time analytics which is crucial to many industries, including manufacturing, health care, telecommunications and finance.

Edge computing vs cloud computing

Organizations need large and complex clusters of data which face bottlenecks every step of the way in the cloud. Centralized infrastructures can provide analysis that relies on historical data, but today it is becoming important for businesses to get real time analysis of the very latest information in order to optimize their processes. Now data is seen to lose its value with the time it takes to move it to the cloud or the data center, as it delays decision making for companies. With edge computing powering data analytics, organizations need not wait to get insights, they can get it in real time.

Edge Computing Use cases

Self-driving cars

Autonomous cars rely on massive troves of data which needs to be analyzed and shared rapidly with other cars on the network. Edge computing will play an essential role in that this information is processed and transmitted to the grid immediately. This allows drivers to receive warnings from incoming traffic immediately.


IoT devices and sensors are now being increasingly used in the manufacturing sector. This enables them to gather data, store and analyze it for better maintenance and efficiency. They can help to optimize manufacturing with continuous and real time data analysis to customize production. Edge computing will be beneficial to industries that operate in areas of low or no bandwidth like offshore oil rigs. Traditional data analytics infrastructure is housed on remote data centers which take time to process data and can give cause-effect data after an event. Edge computing will give them real time analysis that will help managers spot signs of any impeding disaster before it happens.


Healthcare and fitness devices are now fast becoming commonplace in the healthcare and fitness industries. The data stored on these devices can be used to update digital medical records, again requiring quick processing, to be of use during emergencies. Edge computing can speed up the process, providing doctors with up-to-date patient information. It can also impact healthcare delivery in rural areas where patients may be far from doctors. Rapid processing of their data will enable healthcare professionals to remotely consult with their patients armed with all their medical records and suggest a plan of action without needing to leave home.


Beacons, a kind of edge device are already in use in the retail industry. They collect information such as transaction details from mobile phone transactions which can then be used to provide customized deals and promotions to the customers when they walk into the brick and mortar store.

It is still too early to say that cloud computing will be taken over by edge computing. Businesses will still need the cloud to process larger amounts of big data that are not time sensitive. Public cloud servers will have IoT and technology stacks that will include edge computing. Working with a blend of edge and cloud computing will give organizations a comprehensive report of data insights they need in real time and over the long run.