Building LLMs for Production

Building LLMs for Production by Bouchard and Peters bridges the gap between theoretical understanding of large language models and their practical implementation in production environments. This book is a comprehensive guide for engineers and architects who need to deploy LLMs in real-world applications.

What sets this book apart is its focus on the practical challenges of production deployment. The authors cover essential topics like model serving, scaling, monitoring, cost optimization, and security considerations. They also address critical issues like latency, throughput, and reliability that are often overlooked in more theoretical works.

The book provides valuable insights into different deployment architectures, from simple API wrappers to complex distributed systems. It also covers important considerations like model versioning, A/B testing, and handling model drift over time.

For anyone responsible for bringing LLMs into production environments, this book is an essential resource. It’s particularly valuable for ML engineers, DevOps professionals, and technical architects who need to understand the practical aspects of deploying and maintaining LLM-based systems at scale.