Dive Brief:
- Hyperscaler data center buildouts and upgrades will nearly triple cloud compute and storage capacity in the next six years, according to Synergy Research Group projections. The research firm analyzed the data center footprint and operations of 19 global cloud and internet service firms.
- While capacity was already on pace to increase steadily, an anticipated jump in high-intensity generative AI workloads is driving cloud providers to accelerate expansion, the Tuesday report said.
- “We are seeing some changes to plans for future deployment that are being driven by generative AI technology and services,” John Dinsdale, chief analyst at SRG, said in the report. “These changes are not so much to do with the number of new data centers that will be launched, but rather the capacity and power density of those facilities, as GPUs are deployed in ever-greater numbers.”
Dive Insight:
As organizations scale up usage of cloud-based services in the push to modernize, vendors aim to match demand growth stride for stride.
The hyperscalers SRG analyzed operated 926 major data centers globally in mid-2023, with plans underway to open 427 additional facilities. The number has doubled in just the last five years, the report said.
Oracle broke ground on six new data centers this year, adding its portfolio of 64 active cloud regions globally, CEO Safra Catz said last month during a quarterly earnings call. The company also brokered a deal with Microsoft to install its database hardware in Azure data centers.
U.S. data center industry employment volume grew 17% from 2017 to 2021, according to a recent PwC report commissioned by the Data Center Coalition.
The proliferation of cloud, data-intensive applications and digital technologies drove exponential growth in the industry, according to PwC. Emerging technologies are adding momentum.
The anticipated swell in generative AI workloads, which require higher-capacity server technology, has intensified competition among the three largest hyperscalers to capture market share. AWS, Microsoft and Google Cloud have all pledged to upgrade infrastructure to meet customers’ AI compute needs.
Adding graphics processing units, tensor processing units and other AI-optimized capacity doesn’t necessarily require additional space, but it does consume more energy, SRG said.
More powerful compute means higher cost, a factor that may show up on next year’s enterprise cloud bill.
IT leaders should already be prioritizing energy-aware operations, according to Gartner. The analyst firm expects half of G20 members to turn to monthly electricity rationing by 2026,
