Cloud Incident Postmortem Scaffold
On cloud incident: auto-generate postmortem structure (timeline, root cause, lessons learned, action items); save to doc store and notify team.
Overview
**What it does**: Webhook (incident report: incident_id, start_time, end_time, affected_services) → extract incident metadata → query cloud logs for event timeline (when did service degrade, first alert, detection, recovery) → LLM generates postmortem structure (summary, timeline, root cause hypothesis, lessons learned, 3-5 action items) → save to Google Drive/Notion → Slack to #incident-postmortems with link. **Setup (4 steps)**: 1. Configure incident webhook: POST incident details (timestamp, affected services, severity) 2. Connect doc storage: Google Drive, Notion, or Confluence (credentials) 3. Configure Slack channel: #incident-postmortems 4. Test: trigger with sample incident; verify document generated **Apps/nodes**: Webhook, code node (metadata extraction), HTTP request (cloud logs API), Claude/OpenAI (postmortem), HTTP request (doc upload), Slack. **Credentials required**: Cloud API, doc storage credentials, OpenAI account, Slack workspace. **Difficulty**: High | **Setup time**: 12 minutes. **Business outcome**: Incident learning captured immediately → postmortems ↑ thorough, blameless culture ↑, repeated incidents ↓ prevented.
What's included
Inside this workflow
Quickstart
- 01
Download the JSON
With an active Library Pass, download the workflow file right from this page or your dashboard.
- 02
Import into n8n
Choose Import from File and select the downloaded JSON. The full agent graph appears, ready to configure.
- 03
Plug in credentials
Each integration node prompts for credentials on first run. The setup guide lists every credential the agent expects.
- 04
Activate and test
Run once with sample input, confirm the expected output, then flip the activate toggle.
Frequently Asked Questions
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