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DATA OPS

dbt exposure watcher for BI dashboards on deleted models

Detects dbt exposures (dashboards, reports) whose upstream models were deleted or renamed.

CategoryData Ops
Enginesim
Difficultyintermediate
Triggerschedule
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerDaily schedule
  • ActionFetch manifest from GitLabGitLabGitLab
  • LogicResolve each exposure's upstream refs, flag missing models
  • ActionCreate Linear ticket per broken exposureLinearLinear
  • OutputDM the dashboard owner in SlackSlack

What it does

Scans every dbt `exposure` — the declared link between a model and a downstream BI dashboard or report — and verifies each referenced upstream model still exists in the manifest. When a model an exposure depends on has been deleted or renamed, the dashboard is about to break. It files a Linear ticket scoped to the dashboard and notifies the named owner directly so they can repoint or fix it.

When to use it

Run daily if your dbt project documents exposures and your team frequently refactors model names. It closes the gap between a model rename in a merge and a confused stakeholder staring at a broken Looker tile.

How it works

  1. 1A daily schedule triggers the watcher.
  2. 2Fetch the current manifest from the dbt repo in GitLab.
  3. 3For each exposure, resolve its `depends_on` model refs against existing nodes.
  4. 4Branch: flag exposures with any missing upstream model.
  5. 5Create a Linear ticket per broken exposure naming the dashboard and missing model.
  6. 6DM the exposure's declared owner in Slack with the fix needed.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect GitLabRepos, MRs, pipelines, registry.
  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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