DATA OPS
On dbt source.json Result: Block Downstream Run When Sources Are Late
Triggered by a webhook from a dbt source freshness job, it inspects which sources came back stale and, if any feeding the next transform job are late, cancels that job…
How it runs
The automated pipeline, trigger to output.
- TriggerWebhook: dbt source freshness resultsHTTP webhook
- LogicExtract sources with stale/error status
- LogicBranch: do late sources feed the pending job?
- ActionCancel queued transform run via dbt Cloud APIHTTP webhook
- OutputNotify owning team in Slack with detailsSlack
What it does
When your scheduled `dbt source freshness` job finishes, it fires this workflow with the results. The workflow parses which sources returned a `stale` status, checks whether any of them feed the next transform job, and if so cancels that job before it starts so it never builds on late inputs. The relevant owner gets a Slack DM with the specifics.
When to use it
Use it when dbt's own freshness check already runs and you want its result to act as a gate on the downstream build job, rather than running freshness and the transforms blindly back to back.
How it works
- 1A webhook receives the dbt source freshness run results.
- 2A logic step extracts every source with a stale or error status.
- 3A logic branch checks whether any stale source is an upstream dependency of the pending transform job.
- 4If blocked, call the dbt Cloud API to cancel/skip the queued transform run.
- 5Send a Slack message to the data team channel with the late sources and the cancelled job link.
Set it up
What you configure once, before turning it on.
- 1Connect HTTP webhookTrigger any URL on agent actions.
- 2Connect SlackChannels, DMs, threads, mentions.
- 3Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 4Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 5Test, 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.