This blog post discusses the critical role of machine learning (ML) observability at Netflix, particularly in payment processing. It highlights practices and tools for monitoring and understanding ML models' performance, which help detect issues, ensure reliability, and improve operational efficiency. The post explains how ML observability facilitates better decision-making by stakeholders, focusing on metrics that influence real-world outcomes, and emphasizes the importance of explainable AI to foster trust in the ML-driven processes. Additionally, it outlines the challenges faced in ML observability and the strategies implemented to overcome them, paving the way for better scalability and innovation in ML systems.