IT

Artificial intelligence operates more data centers, but still can’t ease the worries of tech staff

It’s a lucrative era for technology suppliers, but as the tsunami of technology hits the market, end-user customers are increasingly overwhelmed by all of them. Artificial intelligence for rescue? Hold that idea.

Photo: Joe Mackendrick

That’s a word from the recent Uptime Institute Research This shows that technology vendors and data center operators are expanding almost non-stop. For the third consecutive year, about 80% say customer spending is above normal levels. Half expect capital investment to increase significantly over the next three to five years. About one-third predicts some slowdown in growth, but only one-sixth predicts that it will flatten or shrink.

Good news, but where are the new ones going? Predicting data center capacity remains a dark technology, and for the fourth consecutive year, suppliers have stated that it is the biggest problem facing clients. Managing a combination of different data center environments (usually any combination of on-premises, collocation, including both retail and wholesale, and the cloud) has become the second largest operator challenge.

In addition, nearly half (47%) of data center operators report difficulty finding qualified candidates, and 38% of technology providers say staff shortages hinder growth. AI is expected to be more widely adopted in the next five years, but it cannot alleviate the staff shortage. One approach is to open up recruitment to a wider variety of potential candidates, and most vendors (88%) expect more diverse staff to be hired in the next 3-5 years. ..

Both technology suppliers and data center operators share the view that AI will be increasingly used to improve the operation of facilities. “AI technology continues to advance, and pandemics have forced many data center operators to rethink their investments in remote monitoring and related software, increasing their interest in technology,” the author of the study said. Rhonda Ascierto and Jacqueline Davis of the Uptime Institute. With an increase in the proportion of suppliers by 89% in 2021 (up from 70% in 2019), we agree that AI will be widely used in data centers to improve efficiency and availability within the next five years. doing.

Only about one-third believe that AI will reduce data center employment compared to workloads within the same time frame. Only 23% of operators expect technology to reduce the level of operations staff within the next five years. “Operators are taking a measured approach to the reality of deploying AI-driven software with mission-critical features,” said Ascierto and Davis. “Technological improvements and the ability to reduce staff levels through automation are usually the result of an iterative, human-led process. It takes time to build trust in the system.”

Uptime analysts have nearly 2.3 million full-time employees worldwide by 2025, from an estimated 2 million in 2020 to support the design, construction and operation of data center infrastructure globally. We anticipate that we will need personnel. Retirement of many existing workers. ”

The biggest challenge for our customers is consistent. It’s about predicting the capacity of your data center. According to Ascierto and Davis, “For some operators, this means dealing with runaway demand in their on-premises data centers, but for others, more work is done by third parties. We expect demand to decline as we move to infrastructure. ” “In most cases, the challenges are more subtle than capacity sizing alone. The question is where to run different workloads based on cost, resilience, compliance, and other factor requirements. . “

Edge computing is also paving the way for technology design and capacity planning. Supplier confidence in Edge’s short-term growth has grown, with 60% agreeing that most of its customers will own a small edge data center within five years, up from 48% a year ago. Nearly three-quarters say they make changes to their products and services at the edge’s opportunity. “Edge computing is often located in remote locations or new locations with minimal or no staff, so edge deployment may require redesign and modification,” said Uptime. Said.

“In the last decade, availability zones have become the de facto way for hyperscale operators to stay on-service at all times, but the approach is no longer limited to hyperscale,” they add. .. “Companies are starting to deploy private cloud workloads in racks of at least three colocation sites. These sites are close enough to ensure low latency, but there are localized interruptions at one site. It’s far enough apart to avoid impacting the workload of another site. Between sites, at least in theory, it can reduce the need for fault tolerance in a single data center. Means. “

There are two reasons for this diversification: increased independence to IT services and architectural complexity. “More important work is being done in the data center than ever before, and in the event of a major component failure, recovery can be difficult and costly,” Ascierto and Davis point out.

Research also shows that there is growing awareness of the role of IT in sustainability. As larger data centers (20 MW and above) are established (suppliers expect) over the next five years, there will be pressure on the sector to improve their environmental footprint. Almost three-quarters of suppliers expect most facilities to meet their carbon reduction targets by 2022. Nearly four out of five companies have set their own goals to reduce the environmental impact of their products or services. The majority (80%) of these suppliers have redesigned their data center products / services to improve their environmental footprint over the last two years.

https://www.zdnet.com/article/artificial-intelligence-runs-more-data-centers-but-still-wont-relieve-technology-staffing-woes/#ftag=RSSbaffb68 Artificial intelligence operates more data centers, but still can’t ease the worries of tech staff

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