Official Tools
Production Stack
Kubernetes-native deployment with Helm charts, autoscaling, health checks, and prefix-aware request routing across replicas.
vLLM Ascend
Hardware extension for Huawei Ascend NPUs, enabling vLLM on non-NVIDIA accelerators.
Structured Output
Built-in grammar-constrained decoding via JSON schemas, regex, and context-free grammars. No external libraries needed.
Community Ecosystem
LangChain / LlamaIndex
Both major LLM frameworks support vLLM as a backend via ChatVLLM and LLM interface classes.
Ray Serve
Distributed serving with autoscaling and prefix-aware routing. Ray's LLMRouter distributes across vLLM replicas.
SkyPilot
Cloud-agnostic deployment from the same UC Berkeley lab. Launch vLLM on any cloud with spot instance management.
OpenLLM (BentoML)
Uses vLLM as an inference backend, adding model versioning, packaging, and deployment management.
Common Integration Patterns
K8s + Prometheus
Deploy via Production Stack Helm chart. Expose Prometheus metrics at /metrics. HPA on GPU cache utilization.
LoRA Multi-Tenant
Serve one base model with multiple LoRA adapters via --enable-lora. Each request specifies its adapter.
OpenAI Drop-In
Point any OpenAI SDK client at the vLLM server. Zero code changes beyond swapping base_url.
Quantization
Pre-quantize with AWQ/GPTQ, serve with --quantization awq. 50-75% memory reduction for larger models.
gpu_cache_usage_perc.