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Visibility at Scale: How Data, Telemetry, and IT Architecture Enable High-Performance Data Centers

As AI infrastructure scales rapidly, data center management has evolved from physical challenges to complex digital ones, requiring advanced telemetry, data analytics, and IT architecture. Modern hyperscale and AI facilities generate massive volumes of operational data that must be processed and acted upon in real time to maintain high performance. Visibility at scale has become a critical capability for operators seeking to optimize efficiency, uptime, and resource utilization.

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By Applied Digital · · Ai Data CentersData Center TechnologyData Center VisibilityData-driven Operations
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Key takeaways

01

As AI infrastructure scales at an unprecedented pace, the complexity of managing data center operations has shifted from purely physical challenges to deeply digital ones.

02

Today’s facilities generate enormous volumes of telemetry, and industry estimates suggest hyperscale and AI data centers produce millions of data points per second.

03

At that scale, visibility is no…

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As AI infrastructure scales at an unprecedented pace, the complexity of managing data center operations has shifted from purely physical challenges to deeply digital ones. Today’s facilities generate enormous volumes of telemetry, and industry estimates suggest hyperscale and AI data centers produce millions of data points per second. At that scale, visibility is no longer a convenience—it becomes essential for maintaining uptime, optimizing efficiency, and mitigating operational risk.

But with such an overwhelming volume of information, a critical question emerges: how do operators transform massive streams of raw data into clear, confident decisions that keep systems running flawlessly?

In this latest episode of Architects of Acceleration Volume II, host Philbert Shih, Founder and Managing Director of Structure Research, is joined by Josh Rossow, Data Center Mechanical Engineer at Applied Digital, and Preston Burkhalter, VP of Data Center Technology at Applied Digital. Together, they explore how modern data centers are evolving into highly intelligent environments—where integrated IT architecture, telemetry, and advanced analytics form a unified operational backbone.

Key takeaways from this episode…

  • How integrated IT architectures consolidate disparate data streams into a single operational view for faster decision-making.
  • The role of sensor networks and telemetry in enabling real-time control, predictive maintenance, and system optimization.
  • How digital twins and machine learning are shaping the future of data center operations and scalability.

Joshua Rossow is a Data Center Mechanical Engineering SME at Applied Digital, specializing in high-performance cooling systems, infrastructure reliability, and data-driven operations, with skills including chiller systems and Python. He brings over a decade of power and energy industry experience from Basin Electric Power Cooperative, where he progressed from performance engineer to project manager, leading large-scale utility projects, optimizing plant efficiency, and ensuring environmental and pipeline compliance. Earlier in his career, he managed wastewater treatment engineering projects at LAS International and later ran his own construction business, building strong expertise in project execution, cost estimation, and customer-focused delivery.

Preston Burkhalter is a technology executive and Vice President at Applied Digital with 20+ years of experience leading mission-critical infrastructure across hyperscale, colocation, and enterprise data centers, specializing in scalable platforms that integrate IT, OT, and business operations. He has driven global data center transformation initiatives at CyrusOne, including automation frameworks, unified observability, cybersecurity modernization, and telemetry strategies across 60+ sites, significantly improving efficiency, resilience, and governance . Known for aligning technical strategy with business outcomes, he focuses on building intelligent, automated HPC environments with standardized architectures, real-time data visibility, and strong compliance frameworks to support large-scale growth.

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