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Homelab n8n Monitoring Workflows

This directory contains intelligent n8n workflows for monitoring and integrating your homelab infrastructure using AI-powered analysis.

📋 Workflows

1. Homelab Health Monitor (`homelab-health-monitor.json`)

Purpose: Comprehensive health monitoring of all homelab services
Schedule: Every 15 minutes (or manual via webhook)
Features:

Network connectivity checks (internet + internal DNS)
Docker Swarm service status monitoring
Service endpoint validation (Komodo, OpenWebUI, Paperless, Prometheus, LM Studio)
AI-powered health analysis using LM Studio
Health scoring (0-100) and automated alerting

Webhook: POST https://n8n.sj98.duckdns.org/webhook/health-check

2. Homelab Log Analyzer (`homelab-log-analyzer.json`)

Purpose: Automated AI analysis of Docker service logs
Schedule: Every 6 hours
Features:

Collects logs from critical services (Traefik, n8n, OpenWebUI, Komodo, Prometheus)
Parses ERROR, WARN, CRITICAL patterns
AI analysis of log patterns and issues
Generates actionable recommendations
Alerts on high error counts

💡 For Manual Log Viewing: Use Dozzle at your configured URL for real-time, interactive log viewing with a beautiful web interface. This workflow is for automated AI-powered analysis and alerting.

3. Homelab Integration Advisor (`homelab-integration-advisor.json`)

Purpose: AI-powered service integration recommendations
Schedule: Daily at 9 AM (or manual via webhook)
Features:

Discovers all running services and capabilities
Identifies integration opportunities
AI generates specific n8n workflow patterns
Prioritizes by complexity and value
Provides step-by-step implementation guidance

Webhook: POST https://n8n.sj98.duckdns.org/webhook/integration-advisor

🚀 Installation

1. Import Workflows

# Option A: Via n8n UI
1. Open n8n at https://n8n.sj98.duckdns.org
2. Click "Workflows" → "Import from File"
3. Select each JSON file from this directory

# Option B: Via API (if API enabled)
cd /workspace/homelab/services/n8n/workflows
curl -X POST https://n8n.sj98.duckdns.org/api/v1/workflows \
  -H "Content-Type: application/json" \
  -H "X-N8N-API-KEY: your-api-key" \
  -d @homelab-health-monitor.json

2. Configure AI Model

Edit each workflow and set your preferred LM Studio model:

Health Monitor: Uses deepseek-r1-distill-llama-8b (reasoning)
Log Analyzer: Uses qwen2.5-coder-7b-instruct (technical analysis)
Integration Advisor: Uses deepseek-r1-distill-llama-8b (planning)

Available models on your LM Studio instance (.81:1234):

deepseek-r1-distill-llama-8b
qwen2.5-coder-7b-instruct
qwen/qwen3-coder-30b
mistralai/codestral-22b-v0.1
google/gemma-3-12b

3. Activate Workflows

Open each workflow
Toggle "Active" switch in top right
Verify schedule trigger is enabled

🔧 Configuration

LM Studio Connection

The workflows connect to LM Studio via the lm-studio hostname (mapped to 192.168.1.81:1234 via extra_hosts in n8n-stack.yml).

Test connection:

docker exec <n8n-container-id> curl http://lm-studio:1234/v1/models

Notifications (Optional)

To enable alerts, add these nodes to each workflow:

Email: Use n8n's Email node with SMTP credentials
Discord: Use Webhook node with Discord webhook URL
Slack: Use Slack node with OAuth credentials
Home Assistant: Send to http://homeassistant.local:8123/api/webhook/n8n-alert

📊 Recommended Integration Patterns

Based on your homelab services, here are high-value integrations to implement:

1. AI-Powered Document Processing

Services: n8n → Paperless → OpenWebUI
Pattern: Auto-tag and summarize uploaded documents using AI

Trigger: Paperless webhook (new document)
→ Get document content
→ Send to LM Studio for tagging/summary
→ Update Paperless tags and notes

2. Metric-Based Automation

Services: Prometheus → n8n → Docker/Komodo
Pattern: Auto-restart services on high resource usage

Trigger: Prometheus AlertManager webhook
→ Parse alert (high CPU/memory)
→ Execute docker service update --force <service>
→ Send notification

3. Smart Search Integration

Services: SearXNG → OpenWebUI
Pattern: Enhanced AI chat with web search capability

Trigger: OpenWebUI webhook or manual
→ Query SearXNG for context
→ Send results + query to LM Studio
→ Return AI response with citations

4. Backup Automation

Services: n8n → All Services → Storage
Pattern: Automated backup verification and reporting

Schedule: Daily at 2 AM
→ Trigger OMV backup scripts
→ Verify backup completion
→ Calculate backup sizes
→ AI analysis of backup health
→ Send report

5. Development Pipeline

Services: Gitea → Komodo → n8n
Pattern: GitOps deployment automation

Trigger: Gitea webhook (push to main)
→ Parse commit info
→ Trigger Komodo deployment
→ Monitor deployment status
→ Run health checks
→ Send notification

🐛 Troubleshooting

Connection to LM Studio Fails

# Check if extra_hosts is configured
docker service inspect n8n_n8n | grep -A 5 ExtraHosts

# Test from n8n container
docker exec $(docker ps -q -f name=n8n) curl http://lm-studio:1234/v1/models

# Verify LM Studio is running on .81
curl http://192.168.1.81:1234/v1/models

Docker Commands Fail

# Verify Docker socket is mounted
docker service inspect n8n_n8n | grep -A 2 docker.sock

# Test from n8n container
docker exec $(docker ps -q -f name=n8n) docker ps

Workflows Don't Execute

Check n8n logs: docker service logs n8n_n8n --tail 100
Verify workflow is activated (toggle in UI)
Check schedule trigger settings
Ensure n8n has sufficient resources (increase memory/CPU limits)

<EFBFBD> Log Viewing

Interactive Log Viewing with Dozzle

For manual, real-time log viewing, use Dozzle - it's already part of your homelab:

Access: Check your Traefik/Portainer configuration for the Dozzle URL

Features:

Real-time log streaming with color coding
Multi-container view
Search and filter logs
No configuration needed - automatically discovers containers
Beautiful, responsive web UI

Use Dozzle when you need to:

Investigate specific issues in real-time
Follow logs during deployments
Debug container startup problems
Search for specific error messages

Automated Log Analysis (This Workflow)

The Homelab Log Analyzer workflow complements Dozzle by:

Running periodically (every 6 hours) to catch issues you might miss
Using AI to identify patterns across multiple services
Sending proactive alerts before issues escalate
Providing trend analysis over time

Both tools serve different purposes and work great together!

<EFBFBD>📈 Next Steps

Import and test each workflow manually
Configure notifications (email/Discord/Slack)
Review AI recommendations from Integration Advisor
Implement priority integrations suggested by AI
Monitor health scores and adjust thresholds
Create custom workflows based on your specific needs

🔗 Useful Links

n8n Documentation: https://docs.n8n.io
LM Studio API: http://lm-studio:1234 (OpenAI-compatible)
Prometheus API: http://prometheus.sj98.duckdns.org/api/v1
Dozzle Logs: Your Dozzle URL (real-time log viewer)
Docker API: Unix socket at /var/run/docker.sock

💡 Tips

Use Dozzle for interactive debugging, workflows for automated monitoring
Start with manual triggers before enabling schedules
Use AI model with appropriate context window for your data
Monitor n8n resource usage - increase limits if needed
Keep workflows modular - easier to debug and maintain
Save successful execution results for reference

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