MCP Dev Summit Bengaluru 2026

Modern observability stacks make it easy to collect telemetry, but not to derive value from it. Teams accumulate unused metrics, high-cardinality signals, and noisy dashboards, leading to rising costs and poor signal quality.

This talk introduces a practical mental model inspired by the Rumsfeld Quadrant to reason about observability in terms of signals we measure vs signals we actually use. In our analysis of a our Observability stack, nearly 70% of collected signals showed little to no usage, reflecting a Pareto-like distribution of signal value.

We present a closed-loop approach that we used to analyze observability metadata and continuously optimize the system. MCP was used as the coordination layer to expose metadata and connect analysis, reasoning, and action workflows.

We will walk through how low-value signals were identified, how recommendations were generated and applied in a real-world large scale observability platform.