DATA OPS

Fivetran schema-change webhook triage to ClickUp or auto-approve

Receives Fivetran schema-change webhook events, auto-approves additive changes, and routes destructive changes to a ClickUp ticket with a Slack heads-up for human review.

CategoryData Ops
Enginesim
Difficultybeginner
Triggerwebhook
Steps5
Setup~5 min

How it runs

The automated pipeline, trigger to output.

  • TriggerFivetran schema-change webhook receivedHTTP webhook
  • LogicParse payload for change type and columns
  • LogicBranch additive auto-approve vs destructive review
  • ActionOpen ClickUp ticket for destructive changeClickUpClickUp
  • OutputPost Slack alert linking the ticketSlack

What it does

Reacts to schema-change events the moment a connector reports them, rather than polling on a timer. When Fivetran (or any loader) posts a schema-change webhook, this inspects the payload, lets harmless additive changes flow through automatically, and quarantines destructive ones into a ClickUp ticket for a human to approve before they propagate.

When to use it

Use it when your loader emits schema-change webhooks and you want near-real-time triage — fast-tracking the safe 90% while pausing the risky 10% for review, instead of treating every change the same.

How it works

  1. 1An incoming HTTP webhook trigger receives the schema-change event.
  2. 2Parse the payload to extract the table, change type, and affected columns.
  3. 3Branch on change type: additive (new column or table) vs destructive (drop, type narrow).
  4. 4For additive changes, log the event and exit — auto-approved.
  5. 5For destructive changes, open a ClickUp ticket capturing the full payload and proposed action.
  6. 6Post a Slack alert linking the ticket so a reviewer can approve or block.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect HTTP webhookTrigger any URL on agent actions.
  2. 2
    Connect ClickUpDocs + tasks + chats in one workspace.
  3. 3
    Connect SlackChannels, DMs, threads, mentions.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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