Batch Job Failure Watchdog
Monitor scheduled cloud batch jobs; on failure, LLM summarizes what failed, when it last ran, and recovery steps — escalate to #batch-ops.
Overview
**What it does**: Webhook (batch job completion) or schedule-based heartbeat check → track execution state → IF status=failed → LLM diagnoses (timeout, permission denied, resource exhausted, dependency missing) + last success timestamp + recovery action → Slack to #batch-ops. **Setup (4 steps)**: 1. Instrument batch jobs: add POST to n8n webhook on success/failure (wrapper script or scheduler notification) 2. Configure Slack channel: #batch-ops 3. Set job tiers: which failures escalate vs. warn 4. Test: force job failure; verify diagnosis in Slack **Apps/nodes**: Webhook, code node (state tracking), IF condition, Claude/OpenAI (diagnosis), Slack. **Credentials required**: Slack workspace, OpenAI account. **Difficulty**: Medium | **Setup time**: 8 minutes. **Business outcome**: Silent batch failures caught within minutes → data completeness ↑, downstream services unbroken, SLA violations ↓.
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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