Amid all the hype, hope, and handwringing about artificial intelligence (AI), another technology tide has quietly been rising, and attracting massive amounts of investment.
It's all around us and keeps proliferating unabated -- in sensors, trackers, production machines, appliances, wearables, vehicles, and buildings. Welcome to the edge, which is likely to shape and shift our jobs and businesses before AI makes its mark. Many of the devices and products seen here at ZDNET represent the edge wave.
The edge and Internet of Things (IoT) are big business. At least 23% of respondents to a survey from the Eclipse Foundation say they spent between $100,000 to $1m on IoT and edge in 2022, and 33% expect to spend this much in 2023. One in 10 anticipate spending more than $10m in 2023. More than half (53%) of enterprises currently deploy IoT solutions, with an additional 24% planning to introduce them within the next 12 to 24 months.
Hybrid cloud is the vehicle on which edge projects are riding. At least 42% of respondents suggest that edge deployments are made possible by hybrid cloud. The intersection of edge and the cloud -- typically seen as polar opposites in technology landscapes -- has not been lost on cloud vendors, especially Amazon Web Services (AWS).
"More and more new use cases and customer requirements have increased the need to have edge computing on top of cloud," says Yasser Alsaied, vice president of IoT for AWS, in a discussion with ZDNET. "Edge infrastructure is important for companies that want their applications closer to their users."
These use cases involve real-time applications that require local data processing, low-latency applications, and data-residency requirements, Alsaied continues. Edge applications are useful to "companies that operate workloads on a ship that can't upload data to the cloud due to connectivity constraints," he says. Such capabilities are needed in highly regulated industries, such as government, healthcare, and financial services, "that need to store and process sensitive data within a geographic boundary to meet regulatory requirements."
Other examples of where edge is needed are at "companies that need to process massive volumes of data locally for real-time insights and responses, such as automobiles," he continues.
However, one key challenge is that companies have yet to fully understand the requirements of IoT and edge, which "can become complex, and not all companies grasp it," says Alsaied. "For many organizations, connecting a few devices is simple, but things get more complicated when they want to scale -- such as updating a fleet, onboarding new devices, and keeping platforms secure and future-proof."
Other challenges seen with edge/IoT deployments include the following:
Skills: They need "to navigate the breadth of technologies and skills needed in the ecosystem," says Alsaied.
Standardization: They "encounter challenges related to adoption, scaling, and device management," he says. "For instance, they often need help connecting legacy equipment that wasn't designed for digitization, or guidance on how to connect digitized operational technology with the IT backend quickly and cost-effectively."
Security: Such concerns "are a top challenge for IoT projects, which hinders moving from pilot to production."
Systems: Customers have concerns with future-proofing investments -- "they have to consider how IoT investments will impact legacy equipment, work with earlier IoT investments, drive ROI, or incur technical debt in the future."
The good news is much of the knowledge and toolsets that have evolved with cloud services are applicable to edge and IoT. Expect to see "more innovations to extend the benefits of the cloud to wherever companies need them," says Alsaied.
"This involves the same tool sets and the same capabilities as in the cloud, from on-premises data centers, to IoT devices, to space and beyond -- delivering high-performance, intelligent applications that can overcome the latency, residency, and process challenges for the modern era."