Intelligent Tech Channels Issue 17 | Page 65

FINAL WORD What edge computing means for infrastructure and operations Businesses can harvest analytics by using sensors at the edge of the network explains Gartner’s Santhosh Rao. M any digital business projects create data that can be processed more efficiently when the computing power is close to the person generating it. Edge computing solutions address this need for localised computing power. IT infrastructure and operations leaders tasked with managing these solutions should understand the associated business value and risks. Gartner defines edge computing as solutions that facilitate data processing at or near the source of data generation. For example, in the context of the Internet of Things, the sources of data generation are usually things with sensors or embedded devices. Organisations that have embarked on a digital business journey have realised that a more decentralised approach is required to address digital business infrastructure requirements. As the volume and velocity of data increases, so too does the inefficiency of streaming all this information to a cloud or data centre for processing. Edge computing serves as the decentralised extension of the campus networks, cellular networks, data centre networks or the cloud. Currently, around 10% of enterprise- generated data is created and processed outside a traditional centralised data centre or cloud. By 2022, Gartner predicts this figure will reach 50%. Edge computing solutions can take many forms. They can be mobile in a Santhosh Rao, Research Director, Gartner. Gartner defines edge computing as solutions that facilitate data processing near the source of data generation. vehicle or smartphone, for example. Alternatively, they can be static, such as when part of a building management solution, manufacturing plant or offshore oil rig. Or they can be a mixture of the two, such as in hospitals or other medical settings. The capabilities of edge computing solutions range from basic event filtering to complex-event processing or batch processing. A wearable health monitor is an example of a basic edge solution. It can locally analyse data like heart rate or sleep patterns and provide recommendations without a frequent need to connect to the cloud. More complex edge computing solutions usually involve gateways. In a vehicle, for example, an edge solution may aggregate local data from traffic signals, GPS devices, other vehicles, proximity sensors and so on, and process this information locally to improve safety or navigation. More complex still are edge servers, such as those that are part of next- generation 5G mobile communication network architectures. Servers deployed in 5G cellular base stations will host applications and cache content for local subscribers, without having to send traffic through a congested backbone network. In especially complex applications, edge servers can form clusters or micro data centres where more computing power is needed locally. Examples can be found in offshore oil rigs and retail outlets. As with all rapidly evolving technologies, evaluating, deploying and operating edge computing solutions has its risks. Risks come in many forms, but a key one relates to security. Using edge computing particularly for IoT, exponentially increases the surface area for attacks. A nascent vendor landscape compounds this risk. Unsecure endpoints are already used in distributed denial-of-service attacks or as entry points to core networks. Another concern is that the cost of deploying and managing an edge computing environment can easily exceed the project’s financial benefits. Moreover, projects can become victims of their own success; scalab ility can become a serious issue as IoT endpoints proliferate. Edge computing has enormous potential to enable digital initiatives supported by IoT, but I&O leaders need to tread carefully.  65