LLM Observability Tools: What to Trace, What to Sample, What to Alert

LLM observability tool selection depends on your specific needs; the wrong choice produces months of pain.

What AI does well here

• Identify your highest-priority observability needs (production debugging, evaluation, cost tracking, drift detection)
• Evaluate tools against those needs, not generic feature lists
• Build the tracing schema before picking a tool (data model first)
• Plan the integration cost (instrumentation, retention, retrieval)

What AI cannot do

• Get observability without instrumenting your code
• Substitute tool selection for thinking about what you need to observe
• Avoid some operational burden (every tool requires maintenance)