DATA OPS
BigQuery Runaway Scheduled-Query Cost Circuit Breaker
Hourly it scans BigQuery job history for scheduled queries that scanned far more bytes than their historical baseline, alerts the team.
How it runs
The automated pipeline, trigger to output.
- TriggerHourly
- ActionRead scheduled-query bytes billedBigQuery
- LogicFlag cost spikes vs baseline
- ActionDisable runaway transfer configBigQuery
- OutputPost cost alert to SlackSlack
- ActionPage on overspend thresholdPagerDuty
What it does
It detects scheduled queries whose bytes-billed suddenly spike well above their normal range, usually from an exploded join, a dropped partition filter, or a backfill gone wrong. It alerts on the anomaly and can pause the transfer config so the next scheduled run doesn't repeat the burn.
When to use it
Use it on a project where a single misbehaving scheduled query can rack up thousands in on-demand cost overnight. Ideal for finance-sensitive analytics warehouses that lack hard slot reservations.
How it works
- 1An hourly schedule fires.
- 2A BigQuery action reads `INFORMATION_SCHEMA.JOBS` for scheduled-query jobs in the last hour, pulling total bytes billed per query.
- 3A logic step compares each job's bytes against its trailing 30-day median and flags jobs exceeding a multiple of baseline.
- 4For each runaway, a BigQuery action disables the underlying transfer config to stop the next run.
- 5A Slack output posts the query, cost delta, and the pause action taken.
- 6A PagerDuty action opens an incident when the projected daily overspend crosses a dollar threshold.
Set it up
What you configure once, before turning it on.
- 1Connect BigQueryDatasets, queries, schemas.
- 2Connect SlackChannels, DMs, threads, mentions.
- 3Connect PagerDutyIncidents, on-call, escalations.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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Run this workflow in your colony.
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