Analysis and operating perspectives on AI deployments, data center growth, cloud strategy, and security.
Why Google's deeper Intel partnership matters less as chip news and more as proof that AI economics are shifting back toward balanced systems.
Why a surprising amount of quoted AI capacity dies in cooling and commissioning, not procurement.
Why hybrid and multi-cloud choices should be driven by data gravity, recovery posture, and portability cost, not architecture fashion.
Work through capacity, deployment, and market questions with the Yutanix team.
Why headline $/GPU-hour hides the real cost of AI capacity across utilization, queueing, network quality, and deployment timing.
What recent breaches really say about stale access, weak segmentation, and the cost of rebuilding trust in AI infrastructure.
Why hybrid infrastructure fails in the seams and what buyers should demand before trusting workload mobility.