DATA OPS
Snowflake Freshness SLA Watchdog: Page Owner and Pause Downstream dbt
Checks a Snowflake table's last-loaded timestamp on a schedule and, if it exceeds its freshness window, pages the on-call owner, pauses the downstream dbt job, and logs the breach.
How it runs
The automated pipeline, trigger to output.
- TriggerEvery 15 minutes
- ActionQuery table max load timestamp + row countSnowflake
- LogicStaleness exceeds SLA window?
- ActionPage data on-callPagerDuty
- ActionPause downstream dbt Cloud jobHTTP webhook
- OutputLog breach to audit tableSnowflake
What it does
Watches a critical Snowflake table's load recency against a defined SLA window. When the table goes stale, it escalates to the data on-call via PagerDuty, halts the dependent dbt transformation so bad or missing data never propagates, and records the breach for the SLA report.
When to use it
Use it on tables that feed dashboards or reverse-ETL where serving stale rows is worse than serving none — a revenue rollup, a daily active users mart, or any source other models depend on.
How it works
- 1A schedule fires every 15 minutes.
- 2Query Snowflake for the table's MAX load timestamp and row count for the latest partition.
- 3Logic compares the gap against the SLA window (e.g., 90 minutes); if within window, the run ends quietly.
- 4On breach, trigger a PagerDuty incident routed to the data on-call with the table name and staleness age.
- 5Pause the downstream dbt Cloud job via its HTTP API so no model builds on stale input.
- 6Append a breach record (table, expected vs actual, age) to a Snowflake audit table for the monthly SLA review.
Set it up
What you configure once, before turning it on.
- 1Connect SnowflakeWarehouses, queries, shares.
- 2Connect PagerDutyIncidents, on-call, escalations.
- 3Connect HTTP webhookTrigger any URL on agent actions.
- 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.
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.
