The text discusses the importance of post-deployment observation and monitoring in ensuring the reliability and resilience of RAG systems. It highlights the differences between traditional monitoring and observability, with observability offering insights into the inputs and outputs of a workflow, including every intervening step. The article provides an overview of key metrics used to evaluate RAG performance, including generation metrics, system metrics, retrieval metrics, and safety metrics. These metrics help identify potential risks and maintain user experience. The text also showcases a simulation using GenAI Studio's GalileoObserveCallback to track chain interactions and provide insights into the system's behavior, tone, toxicity, sexism, PII, and other important aspects. By leveraging these metrics and observability techniques, teams can establish a feedback loop that drives iterative refinement and optimization across all facets of the RAG system.