⚙️ AI Hardware

AWS Disaggregates LLM Inference — llm-d Unlocks Scale

Inference bottlenecks are crumbling. AWS's llm-d rollout disaggregates prefill and decode, turning variable AI workloads into efficient machines.

Marcus Rivera 📅 Mar 19, 2026 ⏱️ 3 min read 👁️ 5 views

⚡ Key Takeaways

Disaggregates prefill (compute-bound) and decode (memory-bound) for optimal GPU use.
Kubernetes-native with intelligent scheduling to preserve KV cache locality across nodes.
Promises 40% TCO cuts by 2026 via inference orchestration shift, echoing storage disaggregation.

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Tech journalist covering AI business and enterprise adoption. 10 years in B2B media.

#AWS inference #Kubernetes AI #Kubernetes LLM #disaggregated serving #llm-d

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Originally reported by AWS Machine Learning Blog