Even as meeting the demands of AI infrastructure intensifies, preventing outages remains a top priority for data center operators — yet failures still occur. This report analyzes recent Uptime data on outages — their causes, costs and consequences.
Benchmarks may produce impressive energy-per-token metrics, but real-world AI workloads are bursty; when throughput drops and GPUs sit idle, joules per token can increase. Do not size AI infrastructure for lab conditions - plan for demand.
In AI model training, idle GPUs - not high prices - are the biggest driver of cost, with poor utilization quietly burning tens of thousands of dollars in wasted compute capacity.
Interactive AI training venue costing tool
NERC alert points to future of grid
Lower density brings server efficiency and cooling gains
Critical spares management: In-House vs. Spare-Parts-as-a-Service
Copper is becoming a systems constraint, not just a commodity issue
RTO and MTTR for data center facilities and equipment
Looking to talk with Network members about the impact of density changes on data center…
What’s your position on Spare Parts Management as-a-Service?
Addressing the data center heat recovery contradiction
How AI training choices affect infrastructure costs
CoolIT sale signals strong pipeline for DLC orders
Enterprises will deploy inference in-house — if they can
Dry cooling energy performance can rival evaporative cooling
Investments back two-phase cooling as water cold plate successor
Next-gen GPUs may not need chillers — but data centers do
Emerging tech: carbon capture at source
Vendors gearing up for 800V DC adoption
Ireland's new grid rules signal shift in data center roles
As AI models improve, availability lags behind
US data center critics pivot from moratoria to regulations
Energy crisis elevates the importance of fuel management
Modular data centers look to solve the challenges of AI
IT-OT telemetry failings are hindering real-time applications
US capacity growth stumbled in 2025: what happened?
