Beyond AI, This Other Technology Wave Is Booming

Amidst all the hype, hope and chatter about artificial intelligence (AI), another technology tide is quietly rising, and attracting massive amounts of investment.

It is all around us, and continues to spread unabated – in sensors, trackers, production machines, devices, wearables, vehicles and buildings. Welcome to the edge, which is likely to shape and transform our jobs and businesses long before AI makes its mark. Many of the devices and products seen here on ZDNET represent the Edge wave.

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Edge and the Internet of Things (IoT) are big business. At least 23% of respondents survey The Eclipse Foundation says they will spend between $100,000 and $1m on IoT and Edge in 2022, and 33% expect to spend that much in 2023. One in 10 is projected to spend more than $10m in 2023. More than half (53%) are currently deploying most enterprise 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 ride. At least 42% of respondents suggest that edge deployments are made possible by hybrid cloud. The intersection of edge and cloud — typically seen as polar opposites in the technology landscape — hasn’t been lost on cloud vendors, especially Amazon Web Services (AWS).

“More and more new use cases and customer requirements have driven the need for edge computing on top of the cloud,” says Yasser Alsaid, vice president of IoT for AWS, in discussion with ZDNet. “Edge infrastructure is critical for companies that want their applications closer to their users.”

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These use cases include real-time applications that require local data processing, low-latency applications, and data-residency requirements, Alsaid continues. Edge applications are “useful for companies that operate onboard workloads that cannot 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 geographic boundaries to meet regulatory requirements.”

Other examples where edge is needed are “companies that need to process massive amounts of data locally for real-time insights and responses, such as automobiles,” he adds.

However, a key challenge is that companies have yet to fully understand the requirements of IoT and the edge, which “can be complex, and not all companies understand it,” Alsaied says. “For many organizations, it is simple to connect a few devices, but things become more complex when they want to go large – such as updating fleets, on-boarding new devices, and ensuring the platform is secure and scalable. Keeping it safe for the future.”

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Other challenges seen with edge/IoT deployments include the following:

• Skill: They need to “navigate the breadth of technologies and skills needed across the ecosystem,” says Alsaied.
• standardization: They face challenges related to adoption, scaling and device management, he says. “For example, they often need help connecting older equipment that was not designed for digitization, or guidance on how to quickly and cost-effectively integrate digitized operational technology with the IT backend. is required.”
• Security: Such concerns are “a top challenge for IoT projects, hindering them from moving from pilot to production.”
• System: Customers have concerns about future-proofing investments – “They need to consider how the IoT investment will impact older devices, work with earlier IoT investments, increase ROI, or incur technical debt in the future. “

The good news is that much of the knowledge and toolset developed with cloud services is applicable to the edge and IoT. “Expect to see more innovation to extend the benefits of the cloud to companies wherever they are needed,” Alasaid says.

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“It includes the same tool sets and similar capabilities as the cloud, from on-premises data centers to IoT devices, to space and beyond – delivering high-performance, intelligent applications that can overcome latency, dwell and process Challenges of the Modern Age”.