Build Reliable AI Applications Faster: How to Trace Issues from Agent to Infrastructure

In this webinar, we’ll walk through how modern engineering teams trace issues end-to-end across the full AI application stack. We’ll start with Application Performance Monitoring, where distributed traces surface where time is actually being spent. From there, we’ll follow a real-world debugging workflow down through code-level profiling to identify inefficient methods, into database query performance to catch slow or malformed queries, and finally into the agentic layer. There, LLM Observability lets you trace agent behavior, run structured experiments to validate prompt and model changes, and continuously evaluate for quality, security, and safety from pre-production through production.