Build your own Mini Edge Data Center Lab to run smart home automation, local AI processing, and secure network services. all using compact hardware and open-source tools.
To simulate or deploy a miniature edge data center for:
- Testing Edge AI applications
- Hosting lightweight services (DNS, NVR, MQTT, InfluxDB, Grafana)
- Running containerized microservices (Docker/K8s)
- Real-time data processing for Smart Home/IoT/CCTV
A. Core Hardware Requirements
| Component | Suggested Model | Role |
|---|---|---|
| Compute Node | Intel NUC / Raspberry Pi 5 / Jetson Nano / Mini PC | Main Edge AI engine |
| Storage | SSD 500GB+ or USB 3.0 HDD | For logging, databases, CCTV |
| Network Switch | TP-Link TL-SG108E / Unifi Switch | VLAN support |
| Router | TP-Link ER605 / MikroTik hEX | Load balancing, failover |
| Wi-Fi AP / Mesh | TP-Link Deco X50 / Unifi FlexHD | Reliable wireless |
| UPS | APC BX600 / Luminous Mini | Power protection |
| Admin Interface | Your PC / Laptop | To manage containers & automations |
Pro tip: Use TP-Link Omada Controller or Unifi Controller for centralized management.
Network Design Layout
B. Logical Segmentation (VLANs)
| VLAN | Subnet | Use Case |
|---|---|---|
| 10 | 192.168.10.0/24 | Admin & PC |
| 20 | 192.168.20.0/24 | IoT Devices |
| 30 | 192.168.30.0/24 | CCTV |
| 50 | 192.168.50.0/24 | Edge Apps & Services |
C. Software Stack
Containerized Services (Docker Compose)
D. Edge AI Tools
- ONNX Runtime / TensorRT for local inference
- Coral Edge TPU for faster processing (optional)
- Ollama / Llama.cpp for on-device LLMs
- Home Assistant for integration with sensors, triggers, dashboards
E. Security Recommendations
- VLAN isolation via router ACLs
- Enable firewall on Edge node
- Use DoH or DoT DNS encryption
- Add failover DNS / NTP
- Use VPN (WireGuard / Tailscale) to remotely access the lab securely
F. Implementation Steps
Step 1: Setup VLAN on Router & Switch
- Use ER605 or MikroTik to define VLANs (10, 20, 30, 50)
- Tag trunks to managed switch, untag end device ports
Step 2: Install OS & Docker
- Use Ubuntu Server / Raspberry Pi OS
- Install Docker + Docker Compose
Step 3: Deploy Containers
- Start InfluxDB, Grafana, Node-RED, MQTT
- Connect IoT devices and stream data via MQTT to InfluxDB
Step 4: Setup Monitoring Dashboards
- Use Grafana to visualize:
- Bandwidth per VLAN
- Device uptime
- Packet loss / ping failures
- Storage capacity
Step 5: Automate with Home Assistant
- Integrate switches, power plugs, sensors
- Create alerts:
- If camera disconnects
- If temperature of Edge node > threshold
- If ISP downtime occurs
G. Budget Summary (Indicative for 2025)
| Component | Cost (INR) |
|---|---|
| Mini PC / RPi 5 | ₹6,500 – ₹14,000 |
| Router | ₹4,000 |
| Managed Switch | ₹2,700 |
| SSD or HDD | ₹2,500 – ₹5,000 |
| UPS | ₹3,000 |
| Total (Baseline Lab) | ₹20,000 – ₹30,000 |
Use Cases
- Testing LLMs & AI inference on edge
- Real-time network health monitoring
- Local CCTV NVR-like function
- IoT automations without the cloud
- Simulated SD-WAN or dual-WAN deployments
A Mini Edge Data Center Lab is not just a geeky experiment — it’s a stepping stone to mastering the edge computing revolution. Whether you’re preparing for Edge AI deployments, smart surveillance, or resilient home networks, this setup gives you the power to test, break, and innovate safely.