Building an LLM Cost Dashboard

Cost dashboards usually fail in one of two directions: a single total that nobody can act on, or forty panels that nobody reads. Five charts, each answering a question somebody actually asks out loud, is about the right size — and each of them is a query you can run today. Three audiences ask genuinely different questions of the same data, and a dashboard that ignores the split ends up serving none of them. Finance asks what this month will be and why it differs from last month. Engineering asks what a particular change did. Product asks whether a feature can be afforded at ten times the current user count. The five charts below cover all three, in roughly that order — which is also why the top of the dashboard is a trend line and not a breakdown: the first question anyone has is whether the number is moving, and only then which part of it moved. Everything runs against the llm_request table from the logging page and the daily rollup from per-customer tracking . One rule for all of them: where environment = 'prod' , always, because eval and staging spend contaminates every trend it touches. 1 · Spend and run rate Daily spend, with a month-to-date total and a straight-line projection to month end. The projection is the panel finance looks at; the daily series is what makes a step change obvious. with daily as ( select started_at :: date as day , sum ( cost_usd ) as spend from llm_request where environment = 'prod' and started_at >= date_trunc ( 'month' , now ()) - interval '2 months' group by 1 ), mtd as ( select sum ( spend ) as spend_mtd , count ( * ) as days_elapsed from daily where day >= date_trunc ( 'month' , now ()):: date ) select d . day , d . spend , avg ( d . spend ) over ( order by d . day rows between 6 preceding and current row ) as spend_7d_avg , ( select round ( spend_mtd , 2 ) from mtd ) as mtd , ( select round ( spend_mtd / nullif ( days_elapsed , 0 ) * extract ( day from date_trunc ( 'month' , now ()) + interval '1 month - 1 day' ), 2 ) from mtd )