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PROJECT / HOME-SERVER

홈 서버 플랫폼

Build and operate a practical information platform using only home computing resources, without depending on external cloud providers. Design, implementation, and operational monitoring are all handled solo.

인프라
홈 서버 플랫폼

시스템 구성

SYSTEM
System architecture: 6-layer flow from access control to hardware At home — everything runs on a single physical machine External Network Home Network Access Control — encrypted dedicated path only Reverse Proxy Container Platform Media / Photos Home Automation AI / Dev Env Auth / Security Virtualization Layer One PC at Home

Figure 1 — Requests pass only through the encrypted path and reach services isolated at the container level.

구현한 기능

5 capabilities
✓

Photos, files, and passwords can now be managed securely on a single personal PC, with no monthly subscription fees.

✓

Can now securely reach the home PC from outside through an encrypted path, even while away.

✓

Home appliances can now be controlled by voice.

✓

Server anomalies (low disk space, a stopped service, etc.) are now detected automatically, with notifications sent out.

✓

New services can now be added quickly without breaking the existing setup.

기술과 도구

Runtime

WSL2DockerDocker Compose

Reverse Proxy / Remote Access

CaddyTailscale

Photos / File Management

ImmichNextcloud

Auth / Password Management

Vaultwarden

Media Streaming

Jellyfin

Home Automation

Home AssistantMosquitto (MQTT)

Local AI

OllamaOpen WebUI

Monitoring / Operations

NetdatantfyWatchtower

Equipment

3 items

Equipment actually used in this project, with its role and constraints. Each entry is based on a research-log record. Prices and availability are not listed.

Intel Core i7-12700

Used in this build

Intel

Role
CPU for every service. It is an everyday desktop PC whose resources are shared, not a dedicated server.
Limitations & notes
With everything on one machine, stopping this PC stops every service (single point of failure).

Record: compute-foundation Manufacturer page

NVIDIA GeForce RTX 3060 Ti

Used in this build

NVIDIA

Role
GPU shared by Jellyfin hardware transcoding, Immich machine-learning inference, Ollama local LLMs and ComfyUI image generation.
Limitations & notes
Because GPU memory is shared, ComfyUI is started only when needed. The card's board partner is not recorded.

Record: compute-foundation Manufacturer page

16 GB system memory

Used in this build
Role
Memory shared by all containers on WSL2 and a robot-development workspace.
Limitations & notes
The practical bottleneck. A swap-usage alert above 98% led to memory limits on every container. An upgrade to 32 GB has not been done. Module part numbers are not recorded.

Record: compute-foundation

학습 로드맵

01

Phase 1

Foundation

Set up the virtualization layer and container platform, and established a secure remote access path. Laid the groundwork every later service runs on.

02

Phase 2

Data Migration

Gradually moved photos, files, and credentials that had been scattered across external cloud services onto the self-hosted platform, verifying integrity at each step.

03

Phase 3

Security Hardening

Audited the entire exposed surface, identified unnecessary exposure, and redesigned around the principle of least privilege, building in an ongoing audit process.

04

Phase 4

Extensibility

Introduced a reverse proxy and a monitoring platform, restructuring the setup so new services can be added quickly and with low risk.

05

Ongoing

Ongoing Operations

Continuing to expand into smart-home territory alongside day-to-day monitoring and maintenance, growing the platform through repeated cycles of planning and implementation.