vLLM

High-throughput LLM inference serving with PagedAttention.

Maturity level: L2Can Build

Six perspectives on vLLM

Roadmap

Advanced — after Kubernetes and LLM fundamentals.

Architecture

Inference runtime behind API gateway on GPU infrastructure.

Company

Specialized skill for AI infrastructure and senior LLMOps roles.

Projects

Deploy vLLM on K8s with monitoring.

Interview

Inference optimization and GPU troubleshooting.

Career

Key for AI Infrastructure Engineer path.

What & Why

What: Inference engine optimized for serving LLMs with high throughput and low latency.

Why: Production LLM serving requires specialized runtimes beyond raw API calls.

Build this

Self-hosted LLM endpoint with autoscaling on GPU nodes.

Production reality

  • ! GPU OOM
  • ! KV cache exhaustion
  • ! Cold start latency
  • ! Model loading time

Interview preparation

  • How does vLLM improve throughput?
  • GPU memory management for inference

Explore vLLM in the interactive universe or train with live cohorts.