How enterprise leaders can plan for placement, predictability, and control as workload requirements change.
By Brad Alexander
Chief Technology Officer, DartPoints
Blog
Enterprise infrastructure decisions are no longer moving on the same predictable clock. New workload patterns, capacity constraints, data governance requirements, and hybrid operating models are forcing technology leaders to think differently about where workloads run and how infrastructure should scale.
In this three-part series, Brad Alexander looks at the practical questions behind that shift: where production inference belongs, why regulated industries are moving carefully, and what enterprises should expect from a platform operator.
Inference workloads are pushing infrastructure planning beyond raw compute and storage toward placement, latency, availability, consistency, and predictable performance.
For regulated industries, responsible adoption starts with data governance, classification, sovereignty, control, and infrastructure choices that match the risk profile.
