claude-home/monitoring/CONTEXT.md

title	description	type	domain	tags
Monitoring and Alerting Overview	Architecture overview of the homelab monitoring system including Uptime Kuma, Claude Runner (CT 302) two-tier health checks, Tdarr monitoring, Windows desktop monitoring, and n8n master/sub-workflow orchestration.	context	monitoring	uptime-kuma claude-runner n8n discord healthcheck tdarr windows infrastructure

System Monitoring and Alerting - Technology Context

Overview

Comprehensive monitoring and alerting system for home lab infrastructure with focus on automated health checks, Discord notifications, and proactive system maintenance.

Architecture Patterns

Distributed Monitoring Strategy

Pattern: Service-specific monitoring with centralized alerting

• Uptime Kuma: Centralized service uptime and health monitoring (status page)
• Claude Runner (CT 302): SSH-based server diagnostics with two-tier auto-remediation
• Tdarr Monitoring: API-based transcoding health checks
• Windows Desktop Monitoring: Reboot detection and system events
• Network Monitoring: Connectivity and service availability
• Container Monitoring: Docker/Podman health and resource usage

AI Infrastructure LXCs (301–302)

Claude Discord Coordinator — CT 301 (10.10.0.147)

Purpose: Discord bot coordination with read-only cognitive memory MCP access SSH alias: claude-discord-coordinator

Claude Runner — CT 302 (10.10.0.148)

Purpose: Automated server health monitoring with AI-escalated remediation Repo: cal/claude-runner-monitoring on Gitea (cloned to /root/.claude on CT 302) Docs: monitoring/server-diagnostics/CONTEXT.md

Two-tier system:

• Tier 1 (health_check.py): Pure Python, runs every 5 min via n8n. Checks containers, systemd services, disk/memory/load. Auto-restarts containers when allowed. Exit 0=healthy, 1=auto-fixed, 2=needs Claude.
• Tier 2 (client.py): Full diagnostic toolkit used by Claude during escalation sessions.

Monitored servers (dynamic from config.yaml):

Server Key	IP	SSH User	Services	Critical
arr-stack	10.10.0.221	root	sonarr, radarr, readarr, lidarr, jellyseerr, sabnzbd	Yes
gitea	10.10.0.225	root	gitea (systemd), gitea-runner (docker)	Yes
uptime-kuma	10.10.0.227	root	uptime-kuma	Yes
n8n	10.10.0.210	root	n8n (no restart), n8n-postgres, omni-tools, termix	Yes
ubuntu-manticore	10.10.0.226	cal	jellyfin, tdarr-server, tdarr-node, pihole, watchstate, orbital-sync	Yes
strat-database	10.10.0.42	cal	sba_postgres, sba_redis, sba_db_api, dev_pd_database, sba_adminer	No (dev)
pihole1	10.10.0.16	cal	pihole (primary DNS), nginx-proxy-manager, portainer	Yes
sba-bots	10.10.0.88	cal	paper-dynasty bot, paper-dynasty DB (prod), PD adminer, sba-website, ghost	Yes
foundry	10.10.0.223	root	foundry-foundry-1 (Foundry VTT)	No

Per-server SSH user: health_check.py supports per-server ssh_user override in config.yaml (default: root). Used by ubuntu-manticore, strat-database, pihole1, and sba-bots which require cal user. SSH keys: n8n uses n8n_runner_key → CT 302, CT 302 uses homelab_rsa → target servers Helper script: /root/.claude/skills/server-diagnostics/list_servers.sh — extracts server keys from config.yaml as JSON array

n8n Workflow Architecture (Master + Sub-workflow)

The monitoring uses a master/sub-workflow pattern in n8n. Adding or removing servers only requires editing config.yaml on CT 302 — no n8n changes needed.

Master: "Server Health Monitor - Claude Code" (p7XmW23SgCs3hEkY, active)

Schedule (every 5 min)
  → SSH to CT 302: list_servers.sh → ["arr-stack", "gitea", "uptime-kuma", "n8n", "ubuntu-manticore", "strat-database"]
  → Code: split JSON array into one item per server_key
  → Execute Sub-workflow (mode: "each") → "Server Health Check"
  → Code: aggregate results (healthy/remediated/escalated counts)
  → If any escalations → Discord summary embed

Sub-workflow: "Server Health Check" (BhzYmWr6NcIDoioy, active)

Execute Workflow Trigger (receives { server_key: "arr-stack" })
  → SSH to CT 302: health_check.py --server {server_key}
  → Code: parse JSON output (status, exit_code, issues, escalations)
  → If exit_code == 2 → SSH: remediate.sh (escalation JSON)
  → Return results to parent (server_key, status, issues, remediation_output)

Exit code behavior:

• 0 (healthy): No action, aggregated in summary
• 1 (auto-remediated): Script already handled it + sent Discord via notifier.py — n8n takes no action
• 2 (needs escalation): Sub-workflow runs remediate.sh, master sends Discord summary

Pre-escalation notification: remediate.sh sends a Discord warning embed ("Claude API Escalation Triggered") via notifier.py before invoking the Claude CLI, so Cal gets a heads-up that API charges are about to be incurred.

SSH credential: SSH Private Key account (id: QkbHQ8JmYimUoTcM) Discord webhook: Homelab Alerts channel

Alert Management

Pattern: Structured notifications with actionable information

# Discord webhook integration
curl -X POST "$DISCORD_WEBHOOK" \
  -H "Content-Type: application/json" \
  -d '{
    "content": "**System Alert**\n```\nService: Tdarr\nIssue: Staging timeout\nAction: Automatic cleanup performed\n```\n<@user_id>"
  }'

Core Monitoring Components

Tdarr System Monitoring

Purpose: Monitor transcoding pipeline health and performance Location: scripts/tdarr_monitor.py

Key Features:

• API-based status monitoring with dataclass structures
• Staging section timeout detection and cleanup
• Discord notifications with professional formatting
• Log rotation and retention management

Windows Desktop Monitoring

Purpose: Track Windows system reboots and power events Location: scripts/windows-desktop/

Components:

• PowerShell monitoring script
• Scheduled task automation
• Discord notification integration
• System event correlation

Uptime Kuma (Centralized Uptime Monitoring)

Purpose: Centralized service uptime, health checks, and status page for all homelab services Location: LXC 227 (10.10.0.227), Docker container URL: https://status.manticorum.com (internal: http://10.10.0.227:3001)

Key Features:

• HTTP/HTTPS, TCP, DNS, Docker, and ping monitoring
• Discord notification integration (default alert channel for all monitors)
• Public status page at https://status.manticorum.com
• Multi-protocol health checks at 60-second intervals with 3 retries
• Certificate expiration monitoring

Infrastructure:

• Proxmox LXC 227, Ubuntu 22.04, 2 cores, 2GB RAM, 8GB disk
• Docker with AppArmor unconfined (required for Docker-in-LXC)
• Data persisted via Docker named volume (uptime-kuma-data)
• Compose config: server-configs/uptime-kuma/docker-compose/uptime-kuma/
• SSH alias: uptime-kuma
• Admin credentials: username cal, password in ~/.claude/secrets/kuma_web_password

Active Monitors (20):

Tag	Monitor	Type	Target
Infrastructure	Proxmox VE	HTTP	https://10.10.0.11:8006
Infrastructure	Home Assistant	HTTP	http://10.0.0.28:8123
DNS	Pi-hole Primary DNS	DNS	10.10.0.16:53
DNS	Pi-hole Secondary DNS	DNS	10.10.0.226:53
Media	Jellyfin	HTTP	http://10.10.0.226:8096
Media	Tdarr	HTTP	http://10.10.0.226:8265
Media	Sonarr	HTTP	http://10.10.0.221:8989
Media	Radarr	HTTP	http://10.10.0.221:7878
Media	Jellyseerr	HTTP	http://10.10.0.221:5055
DevOps	Gitea	HTTP	http://10.10.0.225:3000
DevOps	n8n	HTTP	http://10.10.0.210:5678
Networking	NPM Local (Admin)	HTTP	http://10.10.0.16:81
Networking	Pi-hole Primary Web	HTTP	http://10.10.0.16:81/admin
Networking	Pi-hole Secondary Web	HTTP	http://10.10.0.226:8053/admin
Gaming	Foundry VTT	HTTP	http://10.10.0.223:30000
AI	OpenClaw Gateway	HTTP	http://10.10.0.224:18789
Bots	discord-bots VM	Ping	10.10.0.33
Bots	sba-bots VM	Ping	10.10.0.88
Database	PostgreSQL (strat-database)	TCP	10.10.0.42:5432
External	Akamai NPM	HTTP	http://172.237.147.99

Notifications:

• Discord webhook: "Discord - Homelab Alerts" (default, applied to all monitors)
• Alerts on service down (after 3 retries at 30s intervals) and on recovery

API Access:

• Python library: uptime-kuma-api (pip installed)
• Connection: UptimeKumaApi("http://10.10.0.227:3001")
• Used for programmatic monitor/notification management

Network and Service Monitoring

Purpose: Monitor critical infrastructure availability Implementation:

# Service health check pattern
SERVICES="https://homelab.local http://nas.homelab.local"
for service in $SERVICES; do
    if curl -sSf --max-time 10 "$service" >/dev/null 2>&1; then
        echo "✅ $service: Available"
    else
        echo "❌ $service: Failed" | send_alert
    fi
done

Automation Patterns

Cron-Based Scheduling

Pattern: Regular health checks with intelligent alerting

# Monitoring schedule examples
*/20 * * * * /path/to/tdarr-timeout-monitor.sh    # Every 20 minutes
0 */6 * * * /path/to/cleanup-temp-dirs.sh         # Every 6 hours
0 2 * * * /path/to/backup-monitor.sh              # Daily at 2 AM

Event-Driven Monitoring

Pattern: Reactive monitoring for critical events

• System Startup: Windows boot detection
• Service Failures: Container restart alerts
• Resource Exhaustion: Disk space warnings
• Security Events: Failed login attempts

Data Collection and Analysis

Log Management

Pattern: Centralized logging with rotation

# Log rotation configuration
LOG_FILE="/var/log/homelab-monitor.log"
MAX_SIZE="10M"
RETENTION_DAYS=30

# Rotate logs when size exceeded
if [ $(stat -c%s "$LOG_FILE") -gt $((10*1024*1024)) ]; then
    mv "$LOG_FILE" "$LOG_FILE.$(date +%Y%m%d)"
    touch "$LOG_FILE"
fi

Metrics Collection

Pattern: Time-series data for trend analysis

• System Metrics: CPU, memory, disk usage
• Service Metrics: Response times, error rates
• Application Metrics: Transcoding progress, queue sizes
• Network Metrics: Bandwidth usage, latency

Alert Integration

Discord Notification System

Pattern: Rich, actionable notifications

# Professional alert format
**🔧 System Maintenance**
Service: Tdarr Transcoding
Issue: 3 files timed out in staging
Resolution: Automatic cleanup completed
Status: System operational

Manual review recommended <@user_id>

Alert Escalation

Pattern: Tiered alerting based on severity

1. Info: Routine maintenance completed
2. Warning: Service degradation detected
3. Critical: Service failure requiring immediate attention
4. Emergency: System-wide failure requiring manual intervention

Best Practices Implementation

Monitoring Strategy

1. Proactive: Monitor trends to predict issues
2. Reactive: Alert on current failures
3. Preventive: Automated cleanup and maintenance
4. Comprehensive: Cover all critical services
5. Actionable: Provide clear resolution paths

Performance Optimization

1. Efficient Polling: Balance monitoring frequency with resource usage
2. Smart Alerting: Avoid alert fatigue with intelligent filtering
3. Resource Management: Monitor the monitoring system itself
4. Scalable Architecture: Design for growth and additional services

This technology context provides the foundation for implementing comprehensive monitoring and alerting in home lab environments.