NetMind is an AI-powered network health and observability platform that helps engineers monitor network performance, detect anomalies, analyze root causes, and search operational knowledge — all from a single, unified interface.
⚙️ Built by a Systems Development Engineer to sharpen software, AI, and infrastructure skills — and proudly showcase them in interviews.
- ✅ Live monitoring of latency, jitter, and bandwidth across multiple network endpoints
- ✅ Time-series database storage for historical performance trends
- ✅ ML-based anomaly detection (e.g., latency spikes, connectivity drops)
- ✅ Root cause analysis engine using LLMs and log summarization
- ✅ AI-searchable Knowledge Base for troubleshooting and known issues
- ✅ Clean, interactive dashboard (Streamlit or Dash UI)
- ✅ Modular and cloud-ready (Docker + optional AWS deploy)
| Layer | Tools & Frameworks |
|---|---|
| Language | Python 3.11+ |
| Backend API | FastAPI |
| Monitoring Core | ping, iperf3, subprocess, custom scripts |
| DB (time series) | InfluxDB |
| Dashboard | Streamlit or Dash |
| ML/AI | scikit-learn, Prophet, sentence-transformers |
| Vector Search | FAISS or Qdrant |
| LLM Integration | OpenAI API or local model (Mistral, LLaMA) |
| Deployment | Docker + docker-compose (optional: AWS ECS) |
netmind/
├── backend/
│ ├── main.py # FastAPI server & API routes
│ ├── collector.py # Pings/iperf tests + ingestion
│ ├── db.py # InfluxDB wrapper functions
│ ├── ml/
│ │ └── anomaly_detector.py # Anomaly detection logic
├── dashboard/
│ ├── app.py # Streamlit UI
│ └── components/ # UI widgets (charts, filters)
├── kb/
│ ├── docs/ # Markdown knowledge base entries
│ ├── embed.py # Convert docs to embeddings
│ └── search.py # Semantic query handler
├── scripts/
│ └── simulate_latency.py # Fake data generator
├── logs/ # Collector and API logs
├── Dockerfile
├── docker-compose.yml
└── README.md