Today’s observability stacks are rich in telemetry but poor in semantic alignment. This talk introduces the Intent Graph—a new visualization paradigm that traces the propagation of design decisions across system layers, from infrastructure to application logic to business outcomes. The Intent Graph makes dependencies between architectural choices, test coverage gaps, and runtime anomalies explicit and navigable. We walk through real-world scenarios where misaligned design intent caused failures—even when metrics looked green. Using techniques from MIT's STAMP/STPA, causal inference, and Generative AI, we show how to move from metric dashboards to intent-aware observability fabric. This talk will resonate with those seeking to build truly self-explaining systems.

It maps how design decisions, quality trade-offs, and business goals flow across the system stack, from infrastructure to app to outcomes. When this flow is broken, the system may still "work"—but it works wrong.

What you'll learn:

How to capture intent traces at design time How to correlate runtime telemetry to intent deviation How to prevent false positives/negatives in alerting through purpose-aware thresholds How to respond to incidents based on drift from intent, not just error rates

This is observability with semantics. And it is what SRE needs next.

Short description Go beyond dashboards—this talk introduces Intent Graphs to trace how design decisions shape runtime behavior and business outcomes.

Mahesh leads innovation in the area of application of artificial intelligence, data mining and machine learning in software engineering. He has led successful implementation of natural language processing driven test automation, usage and failure modeling using log analytics, empirical analysis of technical debt and application of knowledge graphs in discovering patterns and relationships for optimizing test suites and improve decision making for system integration projects. His passion is bridging the gap between theory and practice, between academia and industry and creative thinking in software. He is a regular keynote speaker in many conferences. He is currently working on addressing uncertainty in fault prognosis and diagnosis