MODEL SERVINGENTERPRISE AI ARCHITECTURE

Inference Autoscaling

Inference autoscaling uses queue, token rate, active sequences and model load time to add or remove capacity.

WHY IT MATTERS

CPU-based autoscaling often reacts to the wrong signal.

ENTERPRISE EXAMPLE

Scale-out begins when queue wait rises and pre-warmed capacity is below target.

ARCHITECTURE DECISION

Which leading signal predicts SLO breach earliest?

REMEMBERScale on the actual bottleneck.
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