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vLLM in Practice: A Developer's Guide to High-Performance Inference, Scalable Serving, and Efficient Large Language Model Deployment
Paperback
Publisher: Independently Published
Published: Mar 27 2026
Pages: 146
Weight: 0.58
Height: 0.31 Width: 7.00 Depth: 10.00
Language: English
As the material progresses, the focus shifts toward hands-on implementation. You will learn how to configure vLLM for different workloads, integrate it into existing systems, and manage performance across a variety of deployment scenarios. Practical examples illustrate how to balance resource usage with responsiveness, making it easier to build scalable AI-powered applications.
The book also addresses important operational considerations, including monitoring, debugging, and maintaining reliability in production systems. By the end, readers will have a solid foundation for using vLLM effectively, whether for experimentation, prototyping, or full-scale deployment.
This guide is intended for those who want a focused, technically grounded resource without unnecessary complexity, providing a reliable pathway into modern LLM serving workflows.
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