Automated Databricks Table Freshness Checks
Every morning, WebRun opens Databricks, checks the last updated time on every table your dashboards read from, compares it against the refresh each table is meant to keep, cards the stale ones in Trello with the job behind them, and pings you on WhatsApp before standup.
How do I know if my Databricks tables actually refreshed?
Every morning, WebRun opens Databricks and checks the last updated time on every table your dashboards depend on, catching the ones that are stale even when no job reported a failure. It cards each stale table in Trello and pings you on WhatsApp before standup, with the table to fix first.
- Stale dashboards are caught before standup, not by an executive
- Tables behind their cadence surface even when every job reports green
- Each stale table arrives with its job and the dashboards it feeds
Built for analytics engineers · data platform teams · BI developers · data leads
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
databricks.comin a real browser with your saved login - no setup, no API keys. -
1
Databricks - check table freshness
databricks.com
WebRun opens Databricks to check table freshness. - Open Databricks and list the tables your reporting dashboards read from, catalog by catalog
- Read the last updated time on each one
- Compare that time against the refresh cadence the table is supposed to keep
- Flag any table whose data is older than its cadence allows, even where no job reported a failure
- Trace each stale table back to the job or pipeline that writes it, and note its last run status
- Note which dashboards read from each stale table so the blast radius is clear
Done when Every dashboard table has a freshness verdict and, where stale, the job behind it.
-
2
Trello - card the stale tables
trello.com
WebRun opens Trello to card the stale tables. - Open a Trello card for each stale table
- Put the table name, how far behind it is, and the job that writes it in the card
- List the dashboards affected so the impact is visible without opening anything else
- Order the board by how many dashboards each table feeds
- Leave the rerun to an engineer. WebRun never starts a job or edits a pipeline
Done when Every stale table has a card naming its job and the dashboards it feeds.
-
3
WhatsApp - ping you before standup
whatsapp.com
WebRun opens WhatsApp to ping you before standup. - Send yourself a few lines before standup: how many tables are stale and which dashboard is worst affected
- Name the single table to fix first
- Say plainly when everything refreshed on time, so a quiet morning is confirmed rather than assumed
Done when You know before standup whether any dashboard is showing yesterday's numbers.
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 rerun a job to fix a stale table?
No. WebRun reads the table metadata and reports. Starting a job, editing a pipeline, or changing a warehouse is always done by an engineer who can see the wider impact.
How is this different from watching for failed jobs?
A job can succeed and still write nothing. This checks the data itself, so a table that is quietly behind its cadence is caught even when every job reports green.
Does it run queries against my data?
It reads table metadata such as the last updated time and the owning job. It does not copy rows out, and the contents of your tables never leave Databricks.
Related templates
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