Production LLM Observability: What You're Missing When Your AI Feature Goes Dark
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Three silent failure modes that standard APM misses, and the instrumentation layer that catches them before your users do. Your AI feature passes load testing. Latency is under two seconds, error rate is under one percent, the product demo runs clean. You ship it. Three weeks later, a customer reports that the AI-powered output "stopped making sense." Your dashboard shows nothing wrong. The endpoint is returning 200. The logs are quiet. This is the observability gap in production AI backends.…
1Key Takeaways
- Three silent failure modes that standard APM misses, and the instrumentation layer that catches them before your users do.
- Your AI feature passes load testing.
- Latency is under two seconds, error rate is under one percent, the product demo runs clean.
- Three weeks later, a customer reports that the AI-powered output "stopped making sense." Your dashboard shows nothing wrong.
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3Why it matters
Coding AI shifts how fast software ships and how much human review each change needs. DEV — AI reports that three silent failure modes that standard APM misses, and the instrumentation layer that catches them before your users do.
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