Monitor scheduled cloud batch jobs; on failure, LLM summarizes what failed, when it last ran, and recovery steps — escalate to #batch-ops.
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.
Instrument batch jobs: add POST to n8n webhook on success/failure (wrapper script or scheduler notification)
Configure Slack channel: #batch-ops
Set job tiers: which failures escalate vs. warn
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 ↓.
With an active subscription, download the workflow file right from this page or your dashboard.
Choose Import from File and select the downloaded JSON. The full agent graph appears, ready to configure.
Each integration node prompts for credentials on first run. The setup guide lists every credential the agent expects.
Run once with sample input, confirm the expected output, then flip the activate toggle.
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This agent — and every other in the collection — comes with your subscription. One plan, the whole catalog.
Subscribe to downloadMonitor cloud job execution (K8s, Lambda, Cloud Run); on failure, fetch logs, LLM diagnoses root cause (timeout, permission, resource) — alert instantly.