OpenAI Request Logs: Debug Prompts, Errors, and Usage

Live benchmark snapshot

What to instrument first

• • Start with one production workflow and one owner before scaling instrumentation across teams.
• • Track cost, usage, latency, and errors together so the first dashboard supports real tradeoff decisions.
• • Use request logs to explain spikes and validate alert thresholds before expanding coverage.

Common cost drivers to monitor

• • Retries and fallback loops can multiply spend even when token pricing looks cheap.
• • Prompt/context growth silently increases input token cost over time.
• • Latency regressions often correlate with retries and timeout-driven duplicate requests.

Recommended next steps

• • Instrument one workflow with project tags and request logs.
• • Build a baseline dashboard for cost, usage, latency, and errors.
• • Add alerts and a weekly review cadence before scaling to more teams.