DATA OPS
Freshness Recovery Auto-Resolver for Open Lag Incidents
Periodically rechecks tables that have open freshness incidents in PagerDuty, and once Snowflake confirms a table has caught up to its SLA.
How it runs
The automated pipeline, trigger to output.
- TriggerScheduled recovery sweep
- ActionList open freshness incidents in PagerDutyPagerDuty
- ActionRe-check table freshness in SnowflakeSnowflake
- LogicKeep tables now within SLA
- ActionResolve recovered incidentsPagerDuty
- OutputPost recovery and downtime to SlackSlack
What it does
This closes the loop on freshness alerts. It looks at currently open PagerDuty freshness incidents, re-measures those specific tables in Snowflake, and when a table has fully recovered to within its SLA, it resolves the incident automatically and reports how long the table was stale to the team channel in Slack.
When to use it
Use it alongside any freshness alerting workflow so on-call engineers are not stuck manually resolving incidents that the pipeline already fixed itself on the next run. It also gives you accurate, automatic staleness-duration metrics per incident.
How it works
- 1A schedule triggers the recovery sweep.
- 2It lists open freshness-related incidents from PagerDuty.
- 3It re-queries Snowflake for the current freshness of each affected table.
- 4A logic step keeps only the tables now back within SLA.
- 5It resolves those PagerDuty incidents.
- 6It posts a recovery note with total downtime to Slack.
Set it up
What you configure once, before turning it on.
- 1Connect PagerDutyIncidents, on-call, escalations.
- 2Connect SnowflakeWarehouses, queries, shares.
- 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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