Observability Summit North America 2026

Agentic AI systems represent a fundamental shift in software architecture: autonomous agents reason, plan, invoke tools, and orchestrate complex workflows without deterministic control flow. This breaks many assumptions behind traditional observability.

When agents independently make decisions, failures no longer follow a single request path. How do you debug emergent behavior across multiple agent steps? How do you analyze and control token-driven costs? How do you ensure reliability when outputs are non-deterministic?

This session explores why observability is a first-class requirement in the agentic AI era and how OpenSearch can act as the analytical backbone for understanding autonomous AI systems in production. We will cover practical techniques for instrumenting agent workflows with OpenTelemetry and indexing traces, logs, metrics, and AI decision artifacts into OpenSearch for deep correlation and analysis.

Attendees will learn battle-tested patterns for tracing agent reasoning and tool usage, investigating failures and hallucinations, monitoring latency and cost signals, and building dashboards that make agentic AI systems transparent, debuggable, and production-ready.