Homelab Operations | Jimmy Perron

HOMELAB / ARCHITECTURE

Follow the signal.

Choose a component to see its role and connections.

Dashed: planned data pathsSolid: existing links · documented, not live telemetry

01 / Field

NAS Synology DS220+ · Docker
All containers managed by Portainer

03 / Insight

IoT dashboards planned

NAS / MANAGEMENT

AI SERVER / COMPUTE

AI / INTERPRETATION

Portainer manages all Docker containers on both NAS and AI Server. Grafana already monitors its GPU. Ollama will summarize collected IoT data.

Select a component to inspect its purpose and connections.

Enable JavaScript to inspect components. Proposed flow: field nodes → Mosquitto → Node-RED → InfluxDB and MariaDB; InfluxDB → Grafana and Ollama. Existing links: Portainer → all NAS containers and AI Server containers; AI Server GPU → Grafana; AI Server hosts Ollama.

System path

Sensor to decision

The lab mirrors an industrial stack at a smaller scale.

Field

ESP32 · Arduino · LoRa

Transport

Wi-Fi · MQTT

Logic

Node-RED flows

Storage

InfluxDB · MariaDB

Use

Grafana · Ollama summaries (planned)

FIRST USE CASE / GREENHOUSE

Remote moisture monitoring

Distributed nodes measure soil conditions, move readings through LoRa and MQTT, preserve history, and support irrigation decisions from one dashboard.

Design for intermittent field connectivity
Keep raw measurements separate from derived status
Build alerting after baseline behavior is understood

Platform layers

One concern per layer

Every technology needs a defined job. This is a learning platform, not a container-collection contest.

Connectivity

Tailscale for authenticated access; Cloudflare for deliberate web ingress.

Tailscale · Cloudflare Tunnel

Container operations

Portainer manages all Docker containers locally on NAS and remotely on AI Server through the Portainer Agent.

Docker Compose · Portainer

Observability

Grafana already monitors AI Server GPU performance. IoT dashboards will extend that visibility to collected measurements.

Node Exporter · Grafana

Local AI

Ollama runs on AI Server. The planned AI layer will summarize collected IoT data alongside existing coding experiments.

Ollama · Qwen Coder

Development

Application experiments and repeatable infrastructure.

Git · .NET · Blazor · Python

Knowledge system

Architecture, procedures and lessons stay understandable.

Obsidian · Markdown · Git

Operating principles

The rules of the lab

The same rules that matter in a plant matter at home—just with fewer meetings and less vendor theatre.

Document the actual state

Capture live ports, mounts, networks, restart policies and dependencies before calling infrastructure reproducible.

Separate data by purpose

Time-series storage for measurements; relational storage for context and records.

Prefer observable failure

A visible broken service is safer than a silent pipeline producing believable but incorrect data.

Build one complete path

Finish the sensor-to-decision loop before multiplying devices, protocols and dashboards.

Security follows exposure

Keep databases trusted, expose deliberate entry points, and never bury credentials in scripts.