Aurora Monitor

Real-Time Data Pipeline & Dashboard in Rust

Proof of Concept: Real-Time Analytics Platform

A complete end-to-end real-time data system: high-performance ingestion, reliable storage (Delta Lake), and responsive web dashboard. Demonstrates how modern systems-level programming can build production-grade data platforms efficiently.

Uses space weather data as the example domain. Architecture applies directly to operational monitoring, IoT analytics, financial data streaming, or any real-time analytics use case.

Key insight: building fast, reliable systems doesn't require complex infrastructure. This project shows how thoughtful architectural choices reduce both operational overhead and total cost of ownership.

Technical Highlights

  • Efficient Ingestion: Async I/O and parallelization for high-throughput data collection
  • Reliable Storage: Delta Lake provides ACID guarantees and time-travel queries for audit compliance
  • Responsive Dashboard: HTMX + Plotly for interactive visualization without SPA complexity
  • Simple Architecture: End-to-end flow with minimal moving parts, reducing operational overhead
  • Flexible Analysis: User-selectable time ranges (2 hours to 7 days) for different analysis needs
  • Production-Ready Patterns: Scales from POC to enterprise deployment

Technical Approach

Decoupled architecture allows independent optimization of each component. Real-time ingestion runs separately from storage and API layers, improving reliability and maintainability.

Modern lakehouse architecture provides both real-time responsiveness for business users and historical reliability for compliance and audit. Demonstrates how thoughtful system design reduces both operational complexity and total cost of ownership.

Core Technologies

  • Backend: Rust with Actix-web
  • Frontend: HTML, CSS (Bootstrap), JavaScript (Plotly.js)
  • Data Handling: Delta Lake, Apache Arrow
  • Interactivity: HTMX for seamless updates