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Excellent explanation of Metrics, Logs, and Traces, especially Understanding Traces and Spans.
Excellent breakdown of LLM observability. The distinction between metrics, logs, traces, and spans makes the topic easy to understand, while the OpenTelemetry pipeline shows how these concepts fit into a real production system. I especially liked the focus on tracing retrieval steps, tool calls, latency, and token costs rather than monitoring only infrastructure.
Sarah Pan
Software engineer exploring AI, games, and creative workflows.
This was a really useful breakdown. The metrics / logs / traces distinction also made the topic much easier to understand. I’m curious whether you think LLM observability will eventually become a default layer in AI products, the same way application monitoring is now.