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Smart trace sampling prevents observability costs from scaling with your traffic
◆ 75RelevanceOn a story from The New Stack1mo ago
As you scale AI agents or RAG pipelines, trace data volume can quickly become a major infrastructure cost. Intelligent sampling lets you catch edge cases and failures without paying to store redundant "happy path" data.
Takeaways
- Adopt tail-based sampling to prioritize capturing rare AI failure modes over successes.
- Control margins by decoupling observability spend from total request volume.
- Focus on high-signal data to speed up debugging in complex agentic workflows.
Read the original at thenewstack.io
How to find failures without drowning in tracing data
fmode.me/n/how-to-find-failures-without-drowning-in-tracing-data
Written by Founder Mode using gemini-3-flash-preview, from the publisher's own summary. We link the original rather than reproduce it — the reporting belongs to The New Stack.
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