LLMOPS & AI INFRASTRUCTURE • 258 / 397

Operate AI like production: serving, GPUs, latency, capacity, routing and reliability.

Model Serving

Model serving exposes a trained model so applications can send inference requests.

Think of it like

Think of Model Serving like familiar infrastructure capacity and traffic engineering, except the scarce resources are often tokens, GPU memory and model latency.

Real life

High-scale AI services depend on Model Serving to keep cost and latency under control.

SRE lens

A model server is the production process analogous to an application service.

Remember thisModel serving exposes a trained model so applications can send inference requests.

Next conceptModel Endpoint

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