Query and application cost

Compute-level FinOps tells you a database or warehouse is expensive. Query and application cost tells you which queries and code patterns are driving that spend, so developers can fix the cause rather than resize the symptom.

The problem it solves

A single unindexed query scanning a full table, a SELECT * over a huge dataset, or a loop issuing one call per row can quietly dominate a bill. These never show up in instance-level cost reports — the instance just looks busy. This feature reviews the work itself.

What it analyzes

• Expensive queries — full-table scans, unbounded result sets, repeated identical queries, and patterns that bill per byte scanned (as in cloud data warehouses).
• Application-level cost drivers — chatty access patterns, missing pagination, and hot paths that call a paid service far more than needed.
• Cost attribution — which query, service or code path accounts for which share of spend, so the biggest lever is obvious.

What you get

Each finding carries the estimated monthly cost, the inefficiency behind it, and a concrete recommendation — an index, a bounded query, caching, or a cheaper access pattern — framed so a developer can act on it directly. Findings sit alongside the rest of your cost and savings data.

Related

For cost problems in infrastructure-as-code, pipelines and long-running jobs, see pipeline, code and runtime cost review.