The Fourth Pillar of Observability: Recognizing Diagnostic Procedures

Amnon Heiman discusses the evolution of observability from version 1.0, focusing on metrics, logs, and traces, to Observability 2.0, which introduces context as a key component. Heiman argues for recognizing diagnostic procedures as the "fourth pillar" of observability, likening them to medical diagnostics like MRIs that are targeted, costly, and initiated based on specific hypotheses. These procedures are crucial for understanding system behavior but require explicit recognition and modeling to be effectively used by AI agents, especially in making nuanced decisions during system diagnostics. The lack of a structured approach to capturing the context, cost, and risk of these procedures could hinder the ability of AI to perform complex diagnostic tasks that humans handle intuitively. Heiman emphasizes the need for a unified description and execution framework for diagnostic procedures to enable AI to effectively match or exceed human diagnostic capabilities, thereby enhancing the overall observability framework.