What is Edge Computing?


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Every year, certain terms and concepts come to dominate headlines in the technology landscape. In 2023, we’re hearing a lot about “edge computing” – or the practice of capturing, processing, and analyzing data near where it’s created.

This concept is hardly new. In fact, edge computing is already in use all around us – from wearable devices to computers parsing intersection traffic flow. But given the exponential growth in data collected by billions of IoT and mobile devices, businesses are finding that edge computing architecture provides improved ways of processing data in real-time.

The Benefits of Edge Computing

Data is the lifeblood of modern organizations, providing valuable business insight and supporting real-time control over critical business processes and operations. Traditionally, businesses have managed the influx of data through centralized data centers located thousands of miles away. While this doesn’t prevent them from accessing data in real-time, it can lead to bandwidth limitations, latency issues, and unpredictable network disruptions, which can affect overall performance.

Edge computing, however, brings computation and data storage closer to the devices where it’s being gathered. Whereas cloud computing is about processing data in a far-removed data center or public cloud, edge computing is data analysis that takes place at its point of origin in real-time. In other words, it’s the processing of data at the “edge” of the network, closer to where the data is actually being created.

As Red Hat chief technology strategist E.G. Nadhan describes it, “Edge computing brings the data and the compute closest to the point of interaction.” This decentralized approach offers organizations enhanced efficiency, reduced latency, and increased uptime – ultimately improving the customer experience and leading to greater action-led results in real time.

A particularly helpful way to think about edge computing is described by Michael Clegg, Vice President and General Manager of IoT and Embedded at Supermicro: “By processing incoming data at the edge, less information needs to be sent to the cloud and back. This also significantly reduces processing latency. A good analogy would be a popular pizza restaurant that opens smaller branches in more neighborhoods, since a pie baked at the main location would get cold on its way to a distant customer.”

Edge Computing Use Cases

The real-world use cases of edge computing are all around us. Some examples include safety monitoring of oil rigs, streaming video optimization, and drone-enabled crop management. Here are a few more examples:

Traffic Management Systems

Edge computing can enable more efficient city traffic management. For instance, it can perform functions such as adjusting the timing of traffic signals and opening and closing extra traffic lanes on an ad-hoc basis. It can also be used to optimize bus frequency given fluctuations in demand. In this instance, edge computing reduces the cost of bandwidth and latency by not requiring the transportation of large volumes of traffic data to a centralized cloud.


Healthcare systems and providers have largely relied on the cloud for storing, analyzing, and processing data, which have created security concerns and privacy issues. With edge computing, an on-premise server at a hospital enables the localized processing of data in order to maintain privacy and security. Edge computing essentially allows for real-time monitoring and analysis of patient health data through wearables and diagnostic equipment (such as glucose monitors, health tools, and other sensors) – leading to faster, more accurate diagnoses.

Smart Grids

Edge computing is becoming a core technology in the widespread adoption of smart grids, helping enterprises better manage their energy consumption. For instance, sensors and IoT devices connected to an edge platform in factories, plants, and offices are being used to monitor energy use and analyze their consumption in real-time. Similarly, smart lighting systems can use edge commuting to control the optimized use of lights in cities by controlling consumption and ensuring public safety.

With more organizations adopting edge computing strategies, the global edge computing market is expected to grow exponentially in the years to come. In fact, the market was valued at $11.2 billion in 2022 and is expected to expand at a compound annual growth rate (CAGR) of 37.9 percent from 2023 to 2030 – reaching over $155 billion.

While traditional cloud computing models are struggling to keep up with data demand, edge computing is proving a beneficial alternative, offering improved latency, security, bandwidth and privacy, in addition to reduced costs.