Apply researched resource limits to all Docker Compose stacks
- Add deploy.resources sections to all services based on service type - Lightweight services: 0.25 CPU, 128M RAM (Traefik, Authelia, Pi-hole) - Web services: 0.50 CPU, 256M RAM (Dashboards, simple web apps) - Media services: 2.0 CPU, 2G RAM (Jellyfin, transcoding) - Database services: 1.0 CPU, 1G RAM (PostgreSQL, caching) - Heavy apps: 1.5 CPU, 1G RAM (Nextcloud, Home Assistant) - Monitoring: 0.75 CPU, 512M RAM (Prometheus, Grafana) - Include CPU, memory, and process limits with reservations - Create comprehensive resource limits template documentation
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docs/resource-limits-template.md
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docs/resource-limits-template.md
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# AI-Homelab Resource Limits Template
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# Modern deploy.resources configuration for Docker Compose
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# Based on researched typical usage patterns for homelab services
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# These are conservative defaults - monitor and adjust as needed
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# ===========================================
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# SERVICE TYPE TEMPLATES
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# ===========================================
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# LIGHTWEIGHT SERVICES (Reverse proxy, auth, DNS, monitoring)
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lightweight_service:
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deploy:
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resources:
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limits:
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cpus: '0.25' # 25% of 1 CPU core
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memory: 128M # 128MB RAM
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pids: 256 # Max processes
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reservations:
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cpus: '0.10' # Reserve 10% of 1 CPU
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memory: 64M # Reserve 64MB RAM
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# STANDARD WEB SERVICES (Dashboards, simple web apps)
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web_service:
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deploy:
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resources:
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limits:
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cpus: '0.50' # 50% of 1 CPU core
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memory: 256M # 256MB RAM
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pids: 512 # Max processes
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reservations:
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cpus: '0.25' # Reserve 25% of 1 CPU
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memory: 128M # Reserve 128MB RAM
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# DATABASE SERVICES (PostgreSQL, MariaDB, Redis)
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database_service:
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deploy:
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resources:
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limits:
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cpus: '1.0' # 1 CPU core
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memory: 1G # 1GB RAM (for caching)
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pids: 1024 # Max processes
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reservations:
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cpus: '0.50' # Reserve 0.5 CPU
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memory: 512M # Reserve 512MB RAM
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# MEDIA SERVERS (Jellyfin, Plex - without GPU)
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media_server:
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deploy:
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resources:
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limits:
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cpus: '2.0' # 2 CPU cores (for transcoding)
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memory: 2G # 2GB RAM
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pids: 2048 # Max processes
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reservations:
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cpus: '1.0' # Reserve 1 CPU
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memory: 1G # Reserve 1GB RAM
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# DOWNLOADERS (qBittorrent, Transmission)
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downloader_service:
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deploy:
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resources:
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limits:
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cpus: '1.0' # 1 CPU core
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memory: 512M # 512MB RAM
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pids: 1024 # Max processes
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reservations:
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cpus: '0.50' # Reserve 0.5 CPU
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memory: 256M # Reserve 256MB RAM
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# HEAVY APPLICATIONS (Nextcloud, Gitea with users)
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heavy_app:
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deploy:
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resources:
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limits:
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cpus: '1.5' # 1.5 CPU cores
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memory: 1G # 1GB RAM
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pids: 2048 # Max processes
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reservations:
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cpus: '0.75' # Reserve 0.75 CPU
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memory: 512M # Reserve 512MB RAM
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# MONITORING STACK (Prometheus, Grafana, Loki)
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monitoring_service:
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deploy:
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resources:
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limits:
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cpus: '0.75' # 0.75 CPU cores
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memory: 512M # 512MB RAM
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pids: 1024 # Max processes
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reservations:
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cpus: '0.25' # Reserve 0.25 CPU
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memory: 256M # Reserve 256MB RAM
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# ===========================================
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# SPECIFIC SERVICE RECOMMENDATIONS
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# ===========================================
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# Core Infrastructure Stack
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traefik: # Reverse proxy - handles SSL/TLS/crypto
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template: lightweight_service
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notes: "CPU intensive for SSL handshakes, low memory usage"
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authelia: # Authentication service
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template: lightweight_service
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notes: "Very low resource usage, mostly memory for sessions"
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duckdns: # DNS updater
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template: lightweight_service
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notes: "Minimal resources, mostly network I/O"
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# Infrastructure Stack
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pihole: # DNS ad blocker
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template: lightweight_service
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notes: "Memory intensive for blocklists, low CPU"
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dockge: # Docker management UI
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template: web_service
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notes: "Light web interface, occasional CPU spikes"
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glances: # System monitoring
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template: web_service
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notes: "Low resource monitoring tool"
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# Dashboard Stack
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homepage: # Status dashboard
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template: web_service
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notes: "Static content, very light"
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homarr: # Dashboard with widgets
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template: web_service
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notes: "JavaScript heavy but still light"
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# Media Stack
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jellyfin: # Media server
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template: media_server
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notes: "CPU intensive for transcoding, high memory for caching"
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calibre_web: # Ebook manager
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template: web_service
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notes: "Light web app with database"
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# Downloaders Stack
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qbittorrent: # Torrent client
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template: downloader_service
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notes: "Network I/O heavy, moderate CPU for hashing"
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# Home Assistant Stack
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home_assistant: # Smart home hub
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template: heavy_app
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notes: "Python app with many integrations, moderate resources"
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esphome: # IoT firmware
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template: web_service
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notes: "Web interface for device management"
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nodered: # Automation workflows
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template: web_service
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notes: "Node.js app, moderate memory usage"
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# Productivity Stack
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nextcloud: # File sync/sharing
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template: heavy_app
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notes: "PHP app with database, resource intensive with users"
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gitea: # Git server
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template: web_service
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notes: "Go app, lightweight but scales with repos"
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# Monitoring Stack
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prometheus: # Metrics collection
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template: monitoring_service
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notes: "Time-series database, memory intensive for retention"
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grafana: # Metrics visualization
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template: web_service
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notes: "Web dashboard, moderate resources"
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loki: # Log aggregation
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template: monitoring_service
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notes: "Log storage, memory for indexing"
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uptime_kuma: # Uptime monitoring
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template: web_service
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notes: "Monitoring checks, light resource usage"
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# Development Stack
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code_server: # VS Code in browser
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template: heavy_app
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notes: "Full IDE, resource intensive for large projects"
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# Utility Stack
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# Most utilities are lightweight web services
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speedtest_tracker:
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template: web_service
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notes: "Speed test monitoring, occasional CPU usage"
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# ===========================================
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# RESOURCE MONITORING COMMANDS
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# ===========================================
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# Monitor current usage
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docker stats
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# Monitor specific service
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docker stats service_name
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# Check container resource usage over time
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docker stats --format "table {{.Container}}\t{{.CPUPerc}}\t{{.MemUsage}}\t{{.NetIO}}\t{{.BlockIO}}"
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# Check system resources
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docker system df
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# View running processes in container
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docker exec service_name ps aux
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# Memory usage details
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docker exec service_name cat /proc/meminfo | head -10
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# ===========================================
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# ADJUSTMENT GUIDELINES
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# ===========================================
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# If container is killed by OOM:
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# 1. Increase memory limit by 50-100%
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# 2. Check for memory leaks in application
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# 3. Consider adding swap space to host
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# If container is slow/unresponsive:
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# 1. Increase CPU limits
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# 2. Check for CPU bottlenecks
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# 3. Monitor disk I/O if database-related
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# General rule of thumb:
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# - Start with conservative limits
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# - Monitor actual usage with 'docker stats'
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# - Adjust based on real-world usage patterns
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# - Leave 20-30% headroom for spikes</content>
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<parameter name="filePath">/home/kelin/AI-Homelab/docs/resource-limits-template.md
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