Donating llm-d to the Cloud Native Computing Foundation
Peter Hess
Operationalizing AI inference is hard, especially with cutting-edge models and the infrastructure they require. New workloads are variable, and APIs don’t always make it possible to orchestrate inference. The cloud‑native world is racing to keep up with the demands of modern AI, and large language model (LLM) inference is one place where that pressure is felt most intensely.
As organizations push models into production, they’re discovering that serving LLMs at scale presents a new class of...