Implementing AI Observability: Tracing LLM Calls End-to-End

When a Python microservice misbehaves in production, you reach for logs and distributed traces. When an LLM-powered application misbehaves, most teams are flying blind. Tokens leak, latency spikes, costs explode — and all you have is a user complaint. That gap is what AI observability is designed to close. What you actually need to trace Classic...