slo

Tokens per second flatters a system that is failing its users. The metrics that matter are two latencies at a percentile and the fraction of requests that meet both.

Ten thousand requests a second is a fleet of hundreds of nodes, a router that has to know what every replica is caching, and an SLO pair that decides the batch on every one of them. Here is the sizing chain, node by node.

These two flags decide how much memory the engine reserves and how many users share each step, and both are usually left at values that come from the model rather than from the product. The derivation, the SLO that bounds the second one, and the measurement that confirms both.

A single throughput number describes a configuration nobody runs. The four variables that have to be fixed, the curve that is the actual deliverable, and the bandwidth bound that turns the result from a description into a diagnosis.

A shared pool recovers the GPUs inference holds for its peaks, but a preempted training gang takes minutes to give them back and an SLO breaks in seconds. The utilization of each design, the reclaim-time arithmetic against the traffic ramp, and the floor-plus-borrow split most fleets land on.

200 milliseconds at p99 is a budget, and prefill alone spends it on a long prompt. The decomposition into network, queue, routing, prefill and first token, the prompt length the budget allows, chunked prefill in the tail, admission control that rejects what it cannot serve in time, and the utilization the SLO costs.