Edge Computing Infrastructure: AI-Optimized Technical Reference

Configuration Requirements

Hardware Specifications (Production Reality)

• CPU: 4-8 cores minimum (whatever has stock availability)
• Memory: 16GB minimum (K3s claims 512MB but actually needs 2GB+)
• Storage: 256GB SSD minimum (fills with logs during failures)
• Network: Dual internet connections required (one will fail during demos)
• Power: UPS rated for 2x calculated load
• Procurement Reality: Order 30% extra hardware - 30% will be DOA/stolen/repurposed

Network Reality Thresholds

• Bandwidth Planning: Plan for 1/10th advertised ISP speed during business hours
• Latency Expectations: Lab latency × 30 = production latency
• Redundancy Costs: $500/month per cellular backup connection
• Actual Availability: "99.99% uptime" becomes "99.99% fighting network issues"

Deployment Platform Comparison

Platform	Marketing Promise	Reality	Hidden Costs	Cost Range/Node/Month
K3s	Production ready in minutes	3 days debugging systemd conflicts	Support engineer: $2K/month	$500-1500
Docker Swarm	Simple orchestration	Simple until networking breaks	Networking consultant fees	$300-800
Bare Metal	Maximum performance	Maximum troubleshooting	On-site visits: $500/trip	$800-2000
AWS Wavelength	Managed edge computing	3x cost estimates	Data transfer charges	$1200-3000
Hybrid Cluster	Best of both worlds	Worst of both worlds	Therapy costs	$1000-2500

Critical Implementation Warnings

Hardware Failures

• Intel NUCs: 50% arrive with dead NICs or corrupted WiFi drivers
• Dell OptiPlex Micro: Most reliable option for vendor support
• Industrial Grade Hardware: Costs 3x more, breaks in air-conditioned environments
• Compatibility Matrices: Fantasy documents - real compatibility = "boots and doesn't crash"

Network Failure Modes

• Comcast Throttling: Docker pulls trigger "suspicious activity" throttling
• Routing Issues: Local WiFi routing through foreign servers (200ms+ latency)
• Bandwidth Reality: 100 Mbps advertised becomes 5 Mbps during business hours
• Maintenance Windows: Redundant connections fail during each other's maintenance

Security Breaking Points

• Zero-Trust Reality: 47 certificates expire at different times
• Clock Sync Critical: 5-minute clock drift breaks TLS certificate validation
• Physical Security: Servers unplugged for phone charging, rebooted for power outlets, stolen as "expensive equipment"
• Identity Management: OIDC becomes "zero-access" during network partitions

Resource Requirements (Real Costs)

Time Investment

• Planning Phase: 6 months (realistic) vs 2 years (following vendor marketing)
• Deployment Phase: 2-4 months in reality vs 2-4 weeks in documentation
• Operations Phase: Full-time fire fighting

Expertise Requirements

• Support Engineer: $2K/month for K3s issues
• Networking Consultant: Required for troubleshooting
• On-site Technicians: $1500/trip for remote locations
• Premium Support Contracts: $5K/month minimum

Hidden Operational Costs

• Site Visits: $1500/trip (infrastructure always in remote locations)
• Backup Internet: $800/month per location
• Premium Support: $5K/month (regular support can't help)
• Emergency Response: 24/7 availability required

Failure Modes and Solutions

Common Breaking Points

• Memory Leaks: K3s memory usage grows unpredictably beyond documented requirements
• Storage Corruption: Persistent volumes corrupt when cables unplugged
• Certificate Expiration: cert-manager failures at 2am on Sundays
• GitOps Sync Failures: 49 nodes sync perfectly, 50th becomes "special snowflake"

Monitoring False Positives

• Prometheus Resource Consumption: Monitoring uses more resources than applications
• Health Check Lies: Reports "UP" while users can't access anything
• Alert Noise: 500 alerts about legitimate Docker operations, miss actual breaches
• Network Policy Chaos: Zero-trust becomes "open everything" during troubleshooting

Application Deployment Issues

• Container Bloat: 50MB applications become 2GB containers
• Multi-stage Build Failures: Final images larger than originals
• Gradual Rollout Problems: Location 1 works, location 2 fails, location 3 works differently
• Cache Corruption: Local caches fill with stale unusable data

Decision Criteria

When to Choose Edge Computing

• Never: Centralized infrastructure costs 4x less and works better
• If Forced: Start with 2-3 locations to understand failure modes before scaling
• Minimum Budget: 4x initial estimates plus therapy costs

Technology Selection Guidelines

• K3s: Least terrible Kubernetes option (still systemd hell)
• Docker Swarm: Acceptable if you enjoy networking disasters
• Bare Metal: Maximum control, maximum suffering
• Avoid: Fancy edge appliances from Advantech (8-week replacement parts)

Scaling Decision Points

• Location 5: Templates start breaking mysteriously
• Location 10: Infrastructure-as-code becomes infrastructure-as-chaos
• Location 50: Automated deployments break everything simultaneously

Operational Intelligence

Real Success Metrics

• 80% Fix Rate: "Turn it off and on again" solves most edge problems
• Cost Reality: Multiply budget by 4, add 50% for therapy
• Availability Target: Design for 90% uptime, celebrate 95%
• Response Time: Drive to site is faster than remote debugging

Critical Dependencies

• NTP Everywhere: Time sync failures break everything
• Local Admin Accounts: Zero-trust becomes zero-access during outages
• Physical Access Plans: Assume someone needs to visit every site monthly
• Backup Procedures: Everything will need manual restoration

Learning Curve Reality

• Month 1: Optimistic planning and vendor demos
• Month 6: First reality check when nothing works as documented
• Month 12: Acceptance that distributed systems are hard
• Month 18: Expertise in creative problem-solving and vendor negotiation

Resource Links (Verified Functional)

Core Technologies

• K3s Documentation: https://docs.k3s.io/ (lightweight Kubernetes)
• KubeEdge: https://kubeedge.io/ (cloud-native edge framework)
• cert-manager: https://cert-manager.io/ (certificate lifecycle management)
• Prometheus: https://prometheus.io/ (monitoring that consumes all resources)

Hardware Vendors

• Intel NUCs: https://www.intel.com/content/www/us/en/products/details/nuc.html
• Dell OptiPlex: https://www.dell.com/en-us/work/shop/desktops-all-in-one-pcs/optiplex-micro-form-factor/

Community Resources

• CNCF Edge Computing: https://www.cncf.io/blog/2022/08/18/kubernetes-on-the-edge-getting-started-with-kubeedge-and-kubernetes-for-edge-computing/
• Real-World Tutorial: https://www.youtube.com/watch?v=_HTIEcOm3SA (includes debugging failures)

Breaking Point Thresholds

Technical Limits

• Container Images: >2GB causes deployment timeouts
• Monitoring Data: Prometheus data exceeds application resource usage at 50+ nodes
• Certificate Rotation: >47 certificates cause management complexity
• Network Latency: >150ms makes distributed systems unusable

Economic Limits

• Site Visit Frequency: >1 visit/month/location makes edge uneconomical
• Support Costs: >$5K/month indicates platform choice failure
• Hardware Replacement: >30% annual replacement rate unsustainable
• Bandwidth Costs: >$800/month/location for backup connections

Operational Limits

• Team Size: <3 full-time engineers cannot maintain 50+ locations
• Response Time: >4 hours to site visit creates unacceptable downtime
• Automation Failure: >50% manual interventions indicate deployment failure
• Knowledge Transfer: Single points of failure in human expertise create risk

This technical reference preserves all operational intelligence while structuring it for AI consumption and automated decision-making.