The rise of edge cloud: Improving experiences in vertical sectors
We are living through an age of rapid digital transformation. Many of the technological capabilities that enhance life today would have been difficult to imagine even five or six years ago. In the first 30 years of the internet, applications primarily focused on automating content sharing between the cloud and end users. We are now entering the next era of the internet, which includes automating physical and human tasks. As a result, cloud-native applications have emerged in many industries, including manufacturing, retail, automotive and entertainment.
Shifts in enterprise and residential application consumption models necessitate changes in infrastructure, too. Previously, most workloads lived in a centralized cloud, but now platforms distribute workloads to meet the requirements of a flawless user experience. This could be latency or other factors such as data sovereignty, operational considerations for production sites that rely on cloud compute, or IoT applications where vast amounts of data is generated at the edge and doesn’t need to hit a centralized cloud — for example, security applications that utilize AI to analyze video content for threats.
These kinds of applications are compute intensive and delay sensitive, and traditional centralized cloud architectures do not meet the latency requirements that a new generation of applications require. They need a more adaptive and distributed cloud model, with compute and storage cloud resources physically close by, at the edge of the network, as this is where content is created and consumed. This approach is referred to as “edge cloud.”
Edge cloud technology is already enabling the next generation of retail. Amazon has register-free grocery stores worldwide, several of which are in the U.K. The launch of these stores marked a significant change for the retail industry, and we will likely see this model replicated by other brands in the coming years.
Amazon Fresh uses Amazon’s “Just Walk Out” technology, which tracks customer purchases via sensor fusion. In-ceiling cameras, shelf-level sensing, real-time image recognition and deep learning are utilized to automatically add items picked up from a shelf to a shopper’s store app. Those same technologies can also recognise when a product is removed from a physical shopping cart and returned to the shelf. To achieve this, a large amount of instant data transfer is required between the store and the cloud — near-petabytes of data transfer on a daily basis.
It’s the edge cloud that enables this. According to ReportLinker, the edge data center is set to grow by $13.7 billion in the next five years.
