Turn product scenarios, workload traces, latency SLOs, and failure requirements into an evidence-based GPU capacity plan.

An update on OCI model volumes, inference-aware routing, KServe, llm-d, multi-node inference, GPU scheduling, and the remaining gaps.

Run Kubernetes with NVIDIA GPU support inside WSL2 on a laptop, from k3s setup and validation to the limits of local GPU workloads.

How vLLM improves LLM serving efficiency with PagedAttention, better KV-cache utilization, higher throughput, and steadier latency.