ENGINEERING
Real-time BigQuery cost-spike alert to Slack with offending query
Listens for BigQuery audit-log events and, when a single query bills past a hard byte ceiling or runs far longer than its norm, posts an immediate Slack alert with the offending…
How it runs
The automated pipeline, trigger to output.
- TriggerBigQuery job-complete audit event (webhook)HTTP webhook
- LogicCheck bytes/runtime vs ceiling and norm
- ActionFetch full query text and job metadataBigQuery
- OutputPost Slack alert with offending query and costSlack
What it does
This is the fast-twitch counterpart to the daily hunt: it reacts to an expensive query within minutes of it completing rather than waiting for tomorrow's batch. The Slack message names the user or service account, the bytes billed, the estimated dollar cost, and the offending query so on-call can react before the next one runs.
When to use it
Use when a runaway query or a bad backfill can rack up real money in a single execution and you need a human paged into Slack now. Complements the scheduled regression hunt that catches the slower creep.
How it works
- 1A BigQuery completion event arrives via webhook from audit-log routing.
- 2A logic step checks the job's bytes billed and runtime against a hard ceiling and the query's historical norm.
- 3If it breaches, BigQuery is queried to pull the full query text and job metadata.
- 4A Slack message is posted to the platform channel with the query, cost, and a job link as the output.
Set it up
What you configure once, before turning it on.
- 1Connect HTTP webhookTrigger any URL on agent actions.
- 2Connect BigQueryDatasets, queries, schemas.
- 3Connect SlackChannels, DMs, threads, mentions.
- 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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