Explore the next frontier of machine learning systems in this 15-minute conference talk from Conf42 Observability 2024. Delve into the concept of model observability, its importance, and how it differs from model monitoring. Discover key components and challenges in ML observability, including data drift, performance degradation, and data quality issues. Examine specific challenges and evaluation techniques for Large Language Models (LLMs) and computer vision systems. Learn about monitoring techniques, explainability methods for various ML systems, and gain insights into future trends in model observability. Enhance your understanding of this crucial aspect of ML system development and maintenance.