Automated dbt Source Freshness Checks
Every morning, WebRun signs in to dbt Cloud, reads the source freshness results for each environment, compares how old every source is against its warn and error thresholds even when the jobs all passed, posts the stale ones to Slack with their last loaded time, and drafts a Gmail note to the team that owns the pipeline.
How do I catch a stale data source before standup?
WebRun opens dbt Cloud every morning and checks how old each source is against its warn and error thresholds, even when every job passed. It posts the stale sources to Slack with their last loaded time and drafts a Gmail note to the owning team, left for you to send.
- Stale sources are known before standup, not after a dashboard is presented
- A green job over old data is called out instead of trusted
- The note to the upstream team is written and waiting on one click
Built for analytics engineers · data teams · BI leads · data platform owners
What does WebRun do on every run?
The exact actions WebRun takes, in order - in plain language, so you can adjust anything.
-
WebRun signs in and gets to work
Opens
cloud.getdbt.comin a real browser with your saved login - no setup, no API keys. -
1
dbt Labs - check source freshness
getdbt.com
WebRun opens dbt Labs to check source freshness. - Sign in to dbt Cloud and open the source freshness results for each environment you track
- Read the last loaded time for every source and how it compares with its warn and error thresholds
- List the sources in a warn or error state, and note how far past the threshold each one is
- Check whether the jobs themselves passed, so a green run over stale data is called out explicitly
- Compare against yesterday so a source that has been stale for several days is marked as ongoing
Done when Every source has a freshness verdict and the stale ones are listed with their age.
-
2
Slack - post the stale sources
slack.com
WebRun opens Slack to post the stale sources. - Post the analytics channel this morning's stale sources before standup
- Give each line the source, the environment, the last loaded time, and how far past the threshold it is
- Separate the sources in error from the ones only in warn, so attention goes to the right place
- Say nothing when every source is inside its threshold
Done when The team knows before standup which sources are stale.
-
3
Gmail - draft the note to the data owner
gmail.com
WebRun opens Gmail to draft the note to the data owner. - Compose a Gmail note to the team that owns the upstream system for each source in error
- State the source, the last successful load, and how long it has been stale
- Leave every message as a draft. WebRun does not send it, so you check the detail and send it yourself
Done when A Gmail note to each upstream owner is drafted and waiting.
How is each run configured?
Secure by default
Connect once, stays signed in
WebRun signs in once and keeps each session in a persistent environment, so every run picks up right where it left off.
Every action is checked against this policy before it runs.
Questions, answered
Will it email the upstream team without me?
No. Every note is left as a Gmail draft for you to review and send. WebRun never emails another team, a vendor, or a stakeholder on its own, so nothing goes out in your name unchecked.
Can it trigger or rerun a dbt job?
No. WebRun reads the freshness results and reports them. It never runs a job, changes a threshold, or edits a source definition, so nothing in your project is touched by the check.
Why check freshness when all my jobs passed?
Because a job can succeed on stale input. Source freshness compares each table's last loaded time against your warn and error thresholds, so a source that quietly stopped loading is caught even on a green run.
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