Devices everywhere: What the rise of edge investment means for your career

The edge can be where the action happens. And the edge is double-edged: it can be a distributed corporate network or an application running on a small device.

According to IDC, at least 44% of organizations are investing in edge IT to create new customer experiences and drive engagement. Two-thirds (66%) indicated that they planned to run artificial intelligence (AI) and machine learning applications at the edge at the time of the survey. Overall, investments in edge infrastructure will continue to grow at a compound annual growth rate of nearly 23%, IDC added.

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This means opportunities at many points for the more decentralized end of the IT spectrum emerging as the first choice zone for applications.

“Think of the edge as a location-specific cloud layer that is relevant to a growing set of use cases that are time-sensitive and data-intensive,” Mike Zirkle, vice president of 5G commercialization and ecosystem at Verizon Business, told ZDNET. “We see this playing out in autonomous mobile robots, autonomous guided vehicles, and factory floor automation, which are all local environments.”

Zinkle also pointed to emerging “near” and “far” environments. Proximate examples include “transportation, virtual roadside units, toll transactions, congestion management, and mobility use cases.”

When it comes to far edge, he added, “there are things like broadcast captioning modernization, which has to do with improving the latency of captions during live events so that captions better match the pace of what’s being said.”

At the enterprise edge, there has been a movement of AI and other intelligent processing workloads away from centralized systems. “Companies have begun to leverage advances in networking, algorithms and edge computing to run AI workloads outside of data centers and closer to where applications are used,” says a report in The Wall Street Journal.

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Integrating AI “with edge computing further highlights its importance,” Vandana Singh, senior vice president of Schneider Electric, told ZDNET. “AI algorithms deployed at the edge enable devices to process data locally, make autonomous decisions and respond in real time without relying on centralized servers. This not only reduces latency, but also increases privacy and security by minimizing the need to transmit sensitive data over the network.”

Career opportunities

Careers at the enterprise edge include edge network engineer, IoT edge architect, edge software engineer, edge solutions architect, and edge security specialist, as TechRepublic’s Kihara Kimachia describes. At the device or sensor level, career opportunities include firmware developer, RTOS engineer, and firmware engineer.

This requires skills that include designing and building edge systems – which may differ from the “core” skills found in many enterprise data centers. This distinction comes from “thinking through the architecture in terms of what you compute, where, what you store, and where,” Verizon’s Zirkle said. He added that working at the edge means learning “to apply the benefits of edge technology to your data environment and objectives. Edge computing allows you to store data nearby, which means it doesn’t have to be sent back and forth to distant clouds and data centers.” “

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Such skills “are more specialized compared to traditional IT skills,” Wayne Carter, vice president of engineering at Couchbase, told ZDNET. “They combine aspects of network engineering, software development and security protocols to address the unique challenges of edge computing environments.”

The essential skills needed to build edge systems “include proficiency in real-time data processing and an understanding of decentralized architectures,” Sturgeon Christie, CEO of Second Skin Audio, told ZDNET. “They differ significantly from traditional IT skills, which focus more on centralized data storage and processing. Developers entering the edge must be adept at areas such as machine learning and security protocols that are tailored to local and autonomous operations without constant central oversight.”

It also requires the ability to “focus primarily on optimizing data interactions and edge computing,” Carter said. “You need to design systems that support intermittent connectivity and effectively synchronize data between the edge and the cloud. You need proficiency in technologies that facilitate real-time data analysis and decision-making directly at the data source.”

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Core-to-edge skills are “a specialization in networking and connectivity that ensures “seamless communication between edge devices and central systems,” Singh said. Importantly, she added, “edge systems often require solutions to be deployed in remote or harsh environments, which may require varying degrees of reliability and resiliency while maintaining adaptability. Due to the off-site location, the design process should primarily take into account the ability to remotely manage these resources.”

The edge professional opens up new possibilities for organizations because “suddenly, applications or capabilities that require real-time or near-real-time actions are possible,” Zirkle said. “You can take mission-critical steps in time-sensitive scenarios. At the same time, you have data-intensive, time-sensitive things. Imagine what you can do with that kind of efficiency.”