Most teams running AI agents in production share the same monthly experience: the bill is bigger than expected, and nobody can say exactly why. Was it the new feature? The customer who ran 400 prompts last Tuesday? A model that quietly got 3× more expensive? Without a way to slice the spend, you end up guessing — and guessing badly.
Existing observability tools tell you the bill is up. They don't help you do anything about it. We thought that was the wrong shape of product.
Tag any request with anything you want — a feature flag, a customer id, an A/B variant — and Etna will break down spend by that tag. By feature. By model. By session. By user. The first question after "how much?" is always "where?", and now it has a one-click answer.
Latency at the median, the 90th percentile, and the slowest 1% — surfaced together so you can tell whether your agent is consistently fast with rare outliers, or quietly slow for everyone. The slow ones are usually the expensive ones.
When a single call costs noticeably more than your recent average, Etna flags it with a real-time alert — and a link straight to the prompt that did it. Most cost spikes are debuggable; you just need to see them in time.
Tell Etna a daily ceiling. Cross it, and the next call is rejected — not just alerted. No more "we hit the budget at 3am, the dashboard told us, but the agent kept billing through breakfast." Limits should limit.
Other observability tools tell you the bill went up. Etna does the same — and then, because it owns the fix pipeline, it can do something about it. Spotted a feature that's quietly tripled in cost? You're one click away from a fix that brings it back down. The dashboard doesn't just describe the problem. It stages the answer.
Watch the spend.
Then fix it.
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