DATA OPS
Open a Linear ticket when an author's warehouse spend spikes
Compares each query author's daily Snowflake spend against their own trailing 14-day baseline.
How it runs
The automated pipeline, trigger to output.
- TriggerDaily schedule
- ActionRead 15 days of per-author cost from SnowflakeSnowflake
- LogicCompute per-author baseline and flag statistical outliers
- ActionOpen Linear triage issue per anomalyLinear
- OutputNotify platform channel in SlackSlack
What it does
Pulls daily Snowflake cost per author, computes each author's trailing 14-day average and standard deviation, and detects authors whose latest-day spend is a statistical outlier against their own history. For each anomaly it creates a Linear issue containing the author, the spend delta, and their top queries that day, then posts a heads-up to Slack.
When to use it
Use this when absolute thresholds are too blunt: a power user spending a lot every day is fine, but anyone suddenly tripling their own normal spend is worth investigating. Per-author baselining catches behavior changes, not just big numbers.
How it works
- 1A scheduled trigger runs once daily.
- 2A Snowflake action returns 15 days of cost per author from `QUERY_HISTORY`.
- 3A logic step computes each author's 14-day baseline and flags days exceeding mean plus a configurable number of standard deviations.
- 4For each flagged author, a Linear action opens a triage issue with the spend delta and that day's top queries.
- 5A Slack action notifies the data platform channel with links to the new tickets.
Set it up
What you configure once, before turning it on.
- 1Connect SnowflakeWarehouses, queries, shares.
- 2Connect LinearIssues, projects, cycles, triage.
- 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.
More Data Ops workflows
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.
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.
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 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…
dbt orphan model detector with Linear cleanup tickets
Scans your dbt manifest for models that no other model, exposure, or BI tool consumes.
Raw Sensor Telemetry Archive to BigQuery
Captures every incoming building sensor reading via webhook, normalizes the payload into a consistent schema.
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.
