AI in Observability: Challenges and Insights

This chapter explores the integration of AI technologies with observability practices, focusing on the complexities of handling telemetry data in distributed systems. It highlights the challenges practitioners face in utilizing performance metrics effectively and the importance of a methodical approach to data analysis for understanding errors and improving systems. The discussion also sheds light on the development of Query Assistant, emphasizing user engagement and iterative problem-solving as key factors in its success.