DATA OPS
BigQuery dbt-Model Freshness Sentinel to Linear
Hourly scan of dbt-managed BigQuery tables for stale partitions; when a model misses its freshness SLA, files a Linear ticket to the owning team with lineage context so the right…
How it runs
The automated pipeline, trigger to output.
- TriggerHourly freshness scan
- ActionQuery partition recency + dbt SLABigQuery
- LogicKeep models past freshness SLA
- ActionResolve owner + upstream lineageBigQuery
- ActionFile Linear ticket to owning teamLinear
- OutputPost new-ticket digest to SlackSlack
What it does
Watches every dbt model registered in your BigQuery warehouse and checks whether its latest partition landed inside the model's declared freshness window. When a table goes stale past its SLA, it opens a Linear issue assigned to the team that owns the model, pre-filled with the table name, last-loaded timestamp, hours overdue, and upstream lineage so the on-call analyst can start triaging immediately.
When to use it
Use it when your team relies on dbt freshness checks but nobody watches the `dbt source freshness` output, or when stale dashboards keep surprising stakeholders. Best for warehouses where each model has a clear owning team in the dbt `meta` block.
How it works
- 1An hourly schedule fires the sentinel.
- 2It queries BigQuery `INFORMATION_SCHEMA.PARTITIONS` plus the dbt manifest to find each model's newest partition and its SLA.
- 3A filter keeps only models whose latest data is older than their allowed window.
- 4For each stale model it reads the dbt `meta.owner` and upstream `depends_on` lineage.
- 5It files a Linear issue to the owning team with the overdue hours and lineage chain.
- 6It posts a digest of all new tickets to the data-ops Slack channel.
Set it up
What you configure once, before turning it on.
- 1Connect BigQueryDatasets, queries, schemas.
- 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.
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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.
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