opsmeter

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Show HN: Opsmeter.io – AI cost attribution and budget control for LLM apps
1 points by opsmeter 6mo ago|0 comments
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by opsmeter 7mo ago
Usage-based AI needs the same safety engineering as any “expensive actuator”: rate limits, quotas, and automatic shutdown thresholds. Otherwise a leaked key becomes an unbounded liability.
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by opsmeter 7mo ago
This reads like an “incident without guardrails”: per-project caps/quotas, anomaly alerts (minutes), env-split keys, and an automated kill-switch should be defaults for usage-based APIs. Billing emails are post-mortems.
4.
by opsmeter 7mo ago
Nice — those two features tend to unlock the “why” behind drift. One thing we found especially useful was pairing cost/outcome alerts with a root-cause slice: when slope jumps, immediately show top contributing endpoint/feature +
5.
by opsmeter 7mo ago
“Cost per outcome” is the metric most teams actually need. In prod we saw totals look fine while cost/outcome drifted due to retries + fallback paths + context creep. Are you planning a before/after deploy comparison (prompt/
6.
by opsmeter 7mo ago
This is exactly the pain point with agents: spend isn’t linear because fanout + retries compound. One thing that helped us debug/contain spikes is tracking cost per “user-action/outcome” (not just per call) plus a retry ratio tren
7.
by opsmeter 7mo ago
One thing that surprised our team: cost isn’t just “more usage” — retries and context creep can multiply spend with the same user behavior. We now track cost/request and cost per user-action per endpoint over time, plus a retry ratio.
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Show HN: Opsmeter–attribute LLM spend to endpoints and prompt versions(no proxy)
2 points by opsmeter 7mo ago|0 comments