BussDCC System Health

bussdcc-system-health is a reference application demonstrating how to build a real system using bussdcc — a deterministic cybernetic runtime for Python.

It monitors host system health and exposes:

• live metrics via a web dashboard
• structured event streams
• historical JSONL logging
• real-time UI updates through WebSockets

The project is intentionally small but complete. It shows how services, processes, interfaces, and sinks work together inside a bussdcc runtime.

Overview

This application collects and visualizes system telemetry:

• CPU usage
• Memory usage
• Disk usage
• System load averages
• CPU temperature
• Network throughput
• Hardware throttling / undervoltage status (Raspberry Pi compatible)
• Host identity information

The runtime emits events continuously, which are:

1. processed into state
2. streamed to a web interface
3. logged to disk

This demonstrates bussdcc’s core pattern:

Service → Events → Process → State → Interface → UI
             ↓
           Sinks

Architecture

The project intentionally mirrors bussdcc’s runtime model.

Services

SystemService

Runs periodically and emits system telemetry events:

system.memory.usage.updated
system.cpu.usage.updated
system.disk.usage.updated
system.temperature.updated
system.network.usage.updated
system.throttling.updated

Services are responsible only for observing the world and emitting events.

Processes

SystemProcess

Consumes events and updates runtime state:

ctx.state.set("system.cpu.usage", evt.data)

Processes transform event streams into structured shared state.

Interface

SystemWebInterface

• Runs a Flask + Socket.IO server
• Streams runtime events to the browser
• Renders state snapshots on page load

Interfaces expose the system externally without coupling to services.

Event Sinks

Two sinks demonstrate observability patterns:

ConsoleSink

Prints structured JSON events to stdout.

JsonlSink

Writes rotating JSONL event logs:

data/history/YYYY-MM-DD/HH-MM-SS.jsonl

Each line is a single immutable event record.

Dashboard

The web UI provides live system visibility:

• ✅ Health status indicator
• CPU usage breakdown
• Memory & disk utilization
• Load averages
• Network throughput per interface
• Thermal & power throttling detection

Updates occur in real time using Socket.IO events emitted directly from the runtime.

Installation

Requires Python 3.11+.

Standard Install (Recommended)

Install from PyPI:

pip install bussdcc-system-health

Or install locally for development:

pip install -e .

Linux / Raspberry Pi Setup

On Debian-based systems (including Raspberry Pi OS), install required system packages:

sudo apt-get update
sudo apt-get install -y \
    python3-pip \
    python3-flask \
    python3-psutil \
    python3-flask-socketio \
    python3-flask-bootstrap

Then install the application:

pip install bussdcc-system-health --break-system-packages

--break-system-packages may be required on newer Debian and Raspberry Pi OS releases due to externally-managed Python environments (PEP 668).

Optional: Virtual Environment (Alternative)

If you prefer not to use --break-system-packages:

python3 -m venv .venv
source .venv/bin/activate
pip install bussdcc-system-health

Running

Start the runtime:

bussdcc-system-health

Then open:

http://localhost:8086

Example Event Output

Console sink output:

{"time":"2026-01-01T12:00:00Z","name":"system.cpu.usage.updated","data":{"user":12.4,"system":3.1,"idle":84.5}}

This illustrates bussdcc’s core idea:

the system is an event stream first, UI second.

Project Structure

bussdcc_system_health/
├── cli.py            # runtime entrypoint
├── runtime/          # custom runtime lifecycle
├── services/         # telemetry collection
├── processes/        # state projection
├── interfaces/       # web UI
└── sinks/            # event logging

What This Example Demonstrates

This project is designed as a learning reference for bussdcc concepts:

Why bussdcc?

Traditional applications couple:

logic ↔ UI ↔ IO ↔ background work

bussdcc separates responsibilities through events:

observe → emit → transform → expose

This leads to systems that are:

• easier to reason about
• deterministic
• observable by default
• naturally extensible

Hardware Notes

Some features depend on Linux system interfaces:

The application still runs on non-Pi systems, but certain fields may be unavailable.

Development

Install dependencies:

pip install -e .[dev]

Run directly:

python -m bussdcc_system_health.cli

License

MIT License

Related

• bussdcc runtime: https://github.com/jbussdieker/bussdcc