Building Retrieval-Augmented Generation systems that perform well on small datasets is a known problem. However, transitioning these systems to handle large-scale, production environments introduces a distinct set of challenges. This chapter establishes the foundational knowledge required to architect RAG systems that are not only effective but also scalable and can operate reliably under load.

You will begin by revisiting RAG core components from the perspective of large-system design, identifying common bottlenecks that hinder scalability. We will then examine how fundamental principles of distributed systems can be applied directly to RAG architectures. This includes studying various architectural patterns tailored for distributed RAG, defining appropriate metrics for evaluating their performance at scale, and understanding design considerations for high availability, fault tolerance, and data consistency.

By working through these topics, you will develop a solid understanding of how to approach the design of RAG systems intended for demanding, real-application use.