StormScale is an advanced AI-powered performance testing tool designed to test, analyze, and predict system performance under various conditions. It integrates machine learning, deep learning models, and real-time anomaly detection to optimize system load testing.
✅ AI-Driven Load Testing using Locust
✅ Automated Login & Authentication for web applications
✅ Dataverse & Dataset Creation Testing
✅ Deep Learning-Based Performance Prediction (LSTM Model)
✅ AI Anomaly Detection in Response Times & System Metrics
✅ Real-Time System Monitoring (CPU, Memory, Disk, Network)
✅ Auto-Scaling Performance Testing (Adjusts Load Dynamically)
✅ REST API for Performance Predictions & Anomaly Detection
✅ Advanced Visualizations with Seaborn & Plotly
✅ CI/CD Integration for Continuous Testing
git clone https://github.com/yourusername/StormScale.git
cd StormScale
python3 -m pip install --upgrade pip
python3 -m pip install -r requirements.txt
python3 stormscale.py
Endpoint | Method | Description |
---|---|---|
/status |
GET | Returns system CPU, memory, and disk usage |
/predict |
POST | Predicts system performance based on AI model |
/detect-anomalies |
GET | Detects anomalies in performance data |
/api/login |
POST | Logs in a user with credentials |
/api/dataverse |
POST | Creates a new Dataverse |
/api/dataset |
POST | Creates a new Dataset |
StormScale leverages TensorFlow & Scikit-Learn for:
✔ LSTM-based Performance Predictions
✔ Random Forest-Based Bottleneck Detection
✔ Real-Time Data Visualization & Insights
Monitor system usage dynamically:
http://127.0.0.1:5000/status
- Fork the repository
- Create a new feature branch
- Commit your changes
- Submit a pull request
This project is licensed under the MIT License.
💡 StormScale – AI-Powered Performance Testing at Lightning Speed! 🚀