DATA OPS

On-Demand Freshness Check from SLA Definitions in Notion

Triggered by a webhook, reads the table-to-SLA registry maintained in Notion, checks each table's current freshness in Snowflake.

CategoryData Ops
Enginesim
Difficultyintermediate
Triggerwebhook
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerIncoming webhook requestHTTP webhook
  • ActionRead SLA registry from NotionNotionNotion
  • ActionMeasure freshness in SnowflakeSnowflakeSnowflake
  • LogicCompute pass/fail per table
  • ActionOpen PagerDuty incidents for breachesPagerDutyPagerDuty
  • OutputReturn pass/fail report to callerHTTP webhook

What it does

This turns your Notion SLA registry into a runnable check. A webhook call kicks off an evaluation that loads every table's owner and expected freshness window from a Notion database, measures actual freshness in Snowflake, and returns a structured pass/fail result. Any breach also opens a PagerDuty incident so nothing relies on a human reading the report.

When to use it

Use it when teams declare their freshness SLAs in Notion and you want a single source of truth that is both human-editable and machine-enforceable. Great for ad-hoc "is everything fresh right now?" checks before a board demo or release.

How it works

  1. 1An incoming HTTP webhook starts the run.
  2. 2It reads the SLA registry rows (table, owner, max staleness) from the Notion database.
  3. 3It queries Snowflake for each table's actual last-load timestamp.
  4. 4A logic step computes pass/fail per table against its registry SLA.
  5. 5For each failure it opens a PagerDuty incident routed to the listed owner.
  6. 6It returns the full pass/fail report to the webhook caller.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect HTTP webhookTrigger any URL on agent actions.
  2. 2
    Connect NotionPages, databases, comments.
  3. 3
    Connect SnowflakeWarehouses, queries, shares.
  4. 4
    Connect PagerDutyIncidents, on-call, escalations.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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