Infrastructure · · 8 min
Building infrastructure for AI workloads
Start from the workload, not the hardware catalogue. Notes on sizing, scheduling, and growing over time.
Infrastructure decisions are easiest to get right when they start from a clear picture of the workloads it needs to serve.
Profile first
Training, fine-tuning, batch inference, and real-time serving each stress different parts of the system. Understanding the mix shapes every later decision.
Design for sharing
Capacity is rarely used by one team. Quotas, queues, and isolation let multiple groups share resources without interfering with each other.
Plan for growth
Leave room in power, cooling, networking, and storage architecture so capacity can be added without redesigning the system.