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.

CategoryData Ops
Enginesim
Difficultyadvanced
Triggerschedule
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerDaily schedule
  • ActionRead 15 days of per-author cost from SnowflakeSnowflakeSnowflake
  • LogicCompute per-author baseline and flag statistical outliers
  • ActionOpen Linear triage issue per anomalyLinearLinear
  • 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

  1. 1A scheduled trigger runs once daily.
  2. 2A Snowflake action returns 15 days of cost per author from `QUERY_HISTORY`.
  3. 3A logic step computes each author's 14-day baseline and flags days exceeding mean plus a configurable number of standard deviations.
  4. 4For each flagged author, a Linear action opens a triage issue with the spend delta and that day's top queries.
  5. 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.

  1. 1
    Connect SnowflakeWarehouses, queries, shares.
  2. 2
    Connect LinearIssues, projects, cycles, triage.
  3. 3
    Connect SlackChannels, DMs, threads, mentions.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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