DATA OPS
BigQuery Cost Spike Detector with Microsoft Teams Alert
Triggered by a BigQuery export webhook, compares a team's just-completed query cost against its trailing average and, on an anomalous spike.
How it runs
The automated pipeline, trigger to output.
- TriggerBigQuery job-completion webhookHTTP webhook
- ActionFetch team's trailing 30-day baseline costBigQuery
- LogicCompute spike ratio vs baseline
- LogicExit if within normal range
- OutputPost spike alert with SQL to MS TeamsMicrosoft Teams
What it does
Reacts in near real time to completed BigQuery jobs: when a single query from any team costs far more than that team's recent baseline, it surfaces the query text and cost to a Microsoft Teams channel so someone can intervene before the bill compounds.
When to use it
When a single fat-finger query (a missing partition filter, a cross join) can cost hundreds of dollars and you cannot wait for tomorrow's digest. Use it for live spike interception rather than scheduled reporting.
How it works
- 1A webhook trigger receives a BigQuery job-completion event (via log export / Pub/Sub bridge).
- 2A BigQuery action fetches the trailing 30-day average cost for that job's team label.
- 3A logic step computes the ratio of this job's cost to the baseline and checks the spike threshold.
- 4If the job is not anomalous, the flow exits quietly.
- 5On a spike, an MS Teams action posts the team, cost, multiple-over-baseline, and the SQL for quick triage.
Set it up
What you configure once, before turning it on.
- 1Connect BigQueryDatasets, queries, schemas.
- 2Connect Microsoft TeamsChannels, chats, files.
- 3Connect HTTP webhookTrigger any URL on agent actions.
- 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.
More Data Ops workflows
BigQuery Per-Team Budget Breach Alert to PagerDuty
Tracks month-to-date BigQuery scheduled-query spend per team and, when a team crosses its monthly budget, pages the team's on-call in PagerDuty and snapshots the spend breakdown…
dbt orphan model detector with Linear cleanup tickets
Scans your dbt manifest for models that no other model, exposure, or BI tool consumes.
Weekly BigQuery Cost Trend Sheet and Exec Digest
Compiles week-over-week BigQuery scheduled-query cost by owner and dataset into a Google Sheet with trend columns.
Backfill Missing Owner Labels on BigQuery Scheduled Queries
Finds scheduled queries with no owner label, infers the likely owner from creator metadata and target-table lineage, proposes a label.
Daily BigQuery Scheduled-Query Cost Attribution to Owners
Each morning, totals the prior day's on-demand bytes-billed per scheduled query, maps each query to its owner from a label, and posts a per-owner cost leaderboard to Slack.
dbt source freshness watcher with severity-routed alerts
Checks Snowflake loaded-at timestamps against each dbt source's freshness SLA, then routes warnings to Slack and hard breaches to a PagerDuty incident so stale data never…
Run it inside a business
This workflow drops into a full company template. Import the org, and this is one of the playbooks its agents run.
Run this workflow in your colony.
14-day trial. No DevOps. No Sales call. Provisioned in under a minute.