VLLM Deployment Engineering: Production Serving, Optimization, and Scalable Model Operations (Intelligent Systems Infrastructure Series)

VLLM Deployment Engineering is a hands-on guide to running large language models efficiently in real production environments. The book explains how to transform experimental models into stable services capable of handling concurrent users, high throughput, and limited hardware resources.Readers learn how to install and configure VLLM, manage GPU and CPU workloads, optimize memory usage, and design serving architectures that remain responsive under heavy demand. Practical chapters demonstrate batching strategies, quantization trade-offs, latency tuning, and cost-effective scaling techniques.The book also covers:Building REST and streaming inference endpointsLoad balancing multiple model workersManaging versioned deploymentsDebugging performance bottlenecksSecurity and access control basicsContainerized and cloud-ready setupsEvery section is written with clear examples and configuration templates that can be adapted to personal projects or enterprise systems. No prior research background is required only basic Python and Linux familiarity.This guide is perfect for developers who want to move from notebooks to dependable model services without drowning in academic jargon. Read more