cold start

Forecast demand across startup delay, track replicas already being created, and drain slowly enough to avoid repeating the same scale decision.

Trace a model startup through storage, runtime setup and device loading. Transfer floors and dependencies determine whether a minute is plausible.

Design a shared catalogue with explicit service tiers, reproducible deployments and bounded cold starts. Residency depends on burst behavior and resource reuse; placement depends on GPU groups and interference as well as memory.

Walk a single-GPU vLLM Deployment from pod scheduling to the first token, then show the three settings that turn a working manifest into restart loops and stuck rollouts.

Define warm, cached and truly cold paths, then size transfer budgets and warm capacity without promising universal sub-second restores.

Measure scheduling, image transfer, unpacking and model initialization separately. A missing-device error needs its own checks for allocation, container access and CUDA compatibility.

Eight ready slots meet a twelve-request burst. See why starting instances do not count as ready capacity, then design caches, isolation, admission and a measurable startup contract.

A 60-second demand ramp meets a 70-second startup delay. Compare the rate and ready-capacity curves, then design a controller that tracks pending launches without a blind cooldown.