Monitoring vLLM in Production: Metrics, PromQL, Alerts, and Runbooks
A production-oriented guide to monitoring vLLM 0.23.x with Prometheus and Grafana: latency, queueing, preemption, KV-cache pressure, throughput, alerting, and incident diagnosis.
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Why vLLM Scales: Paging the KV-Cache for Faster LLM Inference
Why traditional LLM serving wastes GPU memory – and how vLLM’s PagedAttention model enables larger batches, higher throughput, and more predictable latency.