2010 Architecture Data Center 
CIO
SEPTEMBER 11, 2024
When Uber decided in 2022 to shift away from running its own data centers, the ridesharing and delivery company wanted a high level of control for how its workloads ran in the cloud, down to the CPU level. At the same time, the growth of Uber’s fleet required the company to expand into more data centers and availability zones.
CIO
AUGUST 29, 2023
Since 2010, TeraSky has provided end-to-end solutions to enable customers to handle data center modernization and hybrid and multi-cloud implementation. To do this, Cellebrite needed a “single pane of glass” from which they could see everything, no matter if an application ran in the data center or in the cloud.
CIO
JUNE 12, 2024
Centered on Microsoft Azure for its cloud needs, UK Power Networks will retain on-prem systems in two data centers to store highly secure, sensitive data and services that are vulnerable to cyberattacks, says CIO Matt Webb, who has been with the power company for 15 years.
CIO
DECEMBER 13, 2022
Cassandra’s early days In the mid-2000s, engineers at young, fast-growing Facebook had a problem: how could they store and access the mushrooming data created by Messenger, the platform that enabled users of the social networking site to communicate with one another? By 2013, most of Netflix’s data was housed in Cassandra.
OverOps
APRIL 23, 2019
Many organizations committed themselves to move complete data center applications onto the public cloud. Though the term ‘Hybrid Cloud’ has been around since 2010, it was only later in 2017 when the concept actually took off. This transforms two distinct solutions into a single integrated architecture.
CIO
NOVEMBER 1, 2023
And when Geely bought the company in 2010, it led to a geographical expansion, but until now there’s never been such a thorough and comprehensive effort to modernize the digital landscape, according to Altehed. Now that systems are being replaced, it’s also about creating a new architecture without those types of connections.
CIO
AUGUST 14, 2024
“Generative AI and the specific workloads needed for inference introduce more complexity to their supply chain and how they load balance compute and inference workloads across data center regions and different geographies,” says distinguished VP analyst at Gartner Jason Wong. This isn’t a new issue.
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