AI inference just plays by different rules
The Register ● Covered by 3 sources
AI agents performing inference workloads generate unpredictable, concurrent data access patterns that overwhelm cloud storage systems designed for human-speed applications, requiring architectures that decouple performance from capacity. AWS EBS volumes experience burst credit exhaustion and latency spikes from 1 millisecond to 50+ milliseconds when AI inference traffic overwhelms the storage layer, as demonstrated by a fintech e-commerce platform whose AI shopping assistant caused a system-wide outage within 15 minutes of launch. Organizations must architect for extreme tail latency performance (p99/p999 under mixed load) and adopt software-defined storage solutions that can deliver consistent sub-millisecond latency even during concurrent OLTP and inference workloads, rather than attempting to scale through read replicas or additional IOPS provisioning.
Why it matters
Why no cloud storage architecture was designed for what agentic AI is about to demand
