01
Private LLM serving is still a melting demo: queue heat, GPU lanes, and scale behavior are undocumented, and telemetry does not explain latency or token cost under load.
Case 07
LLM Infrastructure Runtime
Private LLM serving as a controlled furnace: queue heat, GPU lanes, intentional scale, and cool telemetry exhaust — operable runtime, not a melting demo.
01
How it works
From request heat to cool telemetry.
LLM Infrastructure Runtime by Andrey Lesnikov — treat model serving like a furnace you operate: queue, lanes, scale, observe.
-
01
Absorb the heat
Request pressure shows up as queue depth — a signal you can act on, not a silent stall.
-
02
Burn on GPU lanes
vLLM / KServe paths run as explicit lanes, including canary weight when you need progressive risk.
-
03
Scale on purpose
Autoscaling follows queue and latency contracts — capacity is designed, not guessed at 2am.
-
04
Read the cool exhaust
Traces, token metrics, and errors leave the rack so the runtime stays operable under load.
02
Evidence
From problem to proof.
How the system is framed, operated, and proven — not a slide deck summary.
02
You need the full governed execution plane (gateway policy, MCP, canary routing, OpenAI-compatible boundary). Prefer AI Runtime Platform.
03
AI Runtime Platform owns the decision loop. Cloud-Native AI Gateway and Cost / Token Observability sit on the request and spend edges.
Constraints
GPU/CPU placement, model latency, token cost, prompt boundaries, provider limits, data privacy, and fallback behavior.
03
Related
Nearby systems.
AI Runtime Platform
AI workloads often start as API calls but become production systems that need identity, policy, scaling, telemetry, and clear ownership
Every model call: policy + trace + budget
Cloud-Native AI Gateway
AI usage needs routing, policy, budget awareness, and provider resilience
One boundary: rate, budget, fallback, OTel
AI Infra Control Plane
Private AI platforms need shared governance across identity, policy, audit, cost, and SLO signals — not scattered service configs
Private AI with explicit platform contracts
Available for meaningful infrastructure conversations