CAGE — Cloud Architecture Gap Evaluation

CAGE is a complete testing framework designed to evaluate latency, throughput, and payload processing performance in distributed Cloud–Edge architectures.

The goal of CAGE is to identify architectural gaps, performance bottlenecks, and network limitations across different connectivity environments such as 4G/5G, Starlink, WiFi, fiber, or satellite links.

This repository includes two main components:

• Client Module → generates telemetry and image payloads and sends them at controlled rates
• Server Module → receives payloads, logs ingestion metrics, and supports end-to-end KPI analysis

Together, they form a reproducible measurement suite useful for research, benchmarking, and Cloud–Edge system evaluation.

---

📦 Repository Structure

CAGE/
│── client/         # Payload generator and KPI test executor
│── server/         # FastAPI ingestion service and CSV logger
│── README.md       # (this file)

---

🎯 Project Purpose

CAGE helps evaluate:

• Cloud–Edge architectural gaps
• real network performance under different conditions
• effects of payload size on network behavior
• ingestion speed and throughput of backend services
• end-to-end telemetry delays
• suitability of Cloud, Edge, or Hybrid processing

You can use CAGE for:

• research experiments
• infrastructure benchmarking
• performance comparisons between ISPs
• KPI validation (e.g., OA4.1, cloud/edge split)
• system capacity planning

---

🚀 System Overview

✔ Client Module

Simulates IoT/Edge devices by sending:

• weather telemetry JSON payloads
• image payloads encoded in Base64
• configurable batch sizes
• latency patterns (batch + frequency)
• throughput stress bursts

All sent metadata is logged into CSV files.

📄 Documentation:
➡️ client/README.md

---

✔ Server Module

A FastAPI service that:

• receives all client payloads
• timestamps arrival time
• measures payload size
• sanitizes image fields
• appends full records to CSV for later analysis
• exposes a /ping health endpoint

📄 Documentation:
➡️ server/README.md

---

🛠 Technologies Used

• Python 3.8+
• FastAPI
• Uvicorn
• Requests
• python-dotenv
• CSV logging for reproducibility

---

🔧 Setup and Usage

1. Configure environment variables

Each module has its own .env.example.
Copy and rename to .env:

cp client/.env.example client/.env
cp server/.env.example server/.env

2. Install dependencies

pip install -r client/requirements.txt
pip install -r server/requirements.txt

3. Start the KPI ingestion server

cd server
uvicorn app:app --reload

4. Run the KPI client

cd client
python3 client.py

---

📊 Output & Analysis

CAGE produces:

Client-side logs

• timestamps of sending
• JSON payload sizes
• test parameters (batch, frequency, throughput type)

Server-side logs

• timestamps of reception
• payload size
• sanitized payload fields

Use these logs for:

• latency curves
• throughput charts
• jitter estimation
• network performance comparison
• Cloud–Edge gap analysis

---