Optimizing Dynatrace Spend: A Strategic Observability Guide

The conversation centers on a user's efforts to optimize Dynatrace monitoring costs, moving from a fixed-cost model to a more dynamic, consumption-based approach. Initially, the user questions why costs remain steady despite fewer detected problems, leading to a discussion that clarifies Dynatrace charges based on data volume, not problem count. This realization prompts a strategic shift: instead of broadly reducing full-stack monitoring, the focus moves to intelligently switching monitoring modes (from infrastructure-only to full-stack) for individual servers only during critical, pre-scheduled events like batch jobs or patching, leveraging Dynatrace's API. A highly innovative element is introduced with the idea of using "Cost and Carbon" hardware data for predictive monitoring, enabling automatic full-stack activation when subtle performance deviations are detected. The conversation also tackles the political complexities of enterprise IT, particularly regarding cybersecurity team boundaries, concluding that this intra-server, dynamic approach enhances overall observability posture and risk management while achieving cost efficiency.