How to build observability pipelines with the OpenTelemetry Collector, Cribl, and Vector to cut telemetry costs 60-80% without losing diagnostic visibility.
A practical guide to instrumenting LLM applications with OpenTelemetry GenAI semantic conventions, choosing between Langfuse, LangSmith, and Arize Phoenix, tracking token costs, and running evaluation in production.
How OpenTelemetry works, why distributed tracing is different from logging and metrics, and how to instrument your services without drowning in overhead and noise.
Practical deep dives on infrastructure, security, and scaling. No spam, no fluff.
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