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Systems Behaviour Dashboard

An integrated dashboard for exploring and comparing experiments across a systems engineering portfolio focused on load, stability, failure dynamics, concurrency, and performance.

This dashboard provides a unified workbench for visualising how burst-sensitive systems behave under stress and how different engineering strategies affect system outcomes.


Overview

This project brings together multiple experimental environments into a single interactive interface.

Each underlying project studies a different aspect of system behaviour:

  • Load and queue dynamics
  • Backpressure and overload protection
  • Retry amplification and cascading failure
  • Control loops and system stability
  • Concurrent worker runtimes
  • Computational cost and performance optimisation

The dashboard provides a coherent way to view, compare, and understand these behaviours.


Portfolio Projects Covered

1. Systems Load Simulator (Python)

Models queue growth, latency, throughput, and scheduling tradeoffs under varying load and worker capacity.

2. Load Backpressure Service (Python / FastAPI)

Demonstrates bounded queues, worker pools, and overload rejection under increasing request pressure.

3. Retry Storm Simulator (Python)

Explores retry amplification, permanent failures, and resilience limits under rising failure rates.

4. Control Loop Stability Simulator (Python)

Compares fixed, aggressive, and damped feedback strategies to study backlog regulation and oscillation tradeoffs.

5. Concurrent Worker Queue (Go)

Shows bounded concurrent processing using goroutines and channels with load-dependent acceptance behaviour.

6. High-Performance Task Processing Engine (C++)

Benchmarks naive vs optimised task pipelines to demonstrate the performance impact of memory layout and allocation strategy.


What This Dashboard Provides

  • Unified view across multiple systems experiments
  • Visual comparison of system behaviours
  • Observability-focused engineering perspective
  • Reproducible exploration environment
  • Integration layer across a multi-language portfolio

Project Structure

systems-behaviour-dashboard/
├── app.py
├── data/
│ ├── systems-load-simulator/
│ ├── load-backpressure-service/
│ ├── retry-storm-simulator/
│ ├── control-loop-stability-simulator/
│ ├── concurrent-worker-queue/
│ └── cpp-task-processing-engine/
├── assets/
├── requirements.txt
└── README.md

Installation

Create a virtual environment and install dependencies:

python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt

Run the Dashboard

streamlit run app.py

A browser window will open with the interactive dashboard.


Why This Matters

Modern infrastructure systems must remain stable under bursty, failure-prone and resource-constrained conditions.

This dashboard supports:

  • Experimental systems research
  • Engineering tradeoff analysis
  • Observability-driven design
  • Portfolio demonstration of systems thinking

Future Extensions

Possible improvements:

  • Live ingestion from experiment repositories
  • Interactive parameter controls
  • Cross-project comparative analytics
  • Real-time metrics streaming
  • Private plugin integration for proprietary stability layers

License

MIT

About

Streamlit dashboard for exploring and comparing load, backpressure, retry, control, concurrency and performance experiments across a systems engineering portfolio.

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