The goal of this project is to demonstrate core distributed systems principles -
replication, fault tolerance, eventual consistency, and observability - using a minimal but realistic setup.
Rather than relying on large cloud infrastructure, this system uses two Raspberry Pis, a real sensor, and a production-grade distributed database to show how real-world distributed systems behave under normal operation and failure conditions.
- Horizontal scaling using multiple nodes
- Data replication with Apache Cassandra
- Fault tolerance and node failure simulation
- Heartbeat-based node liveness detection
- Eventual consistency
- Separation of data plane (Cassandra) and control plane (heartbeats)
- Observability through a real-time dashboard
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Seed Node (Raspberry Pi 1)
- Connected to a temperature sensor
- Acts as the initial Cassandra seed node
- Publishes sensor data to the backend REST API
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Peer Node (Raspberry Pi 2)
- Participates in Cassandra replication
- Maintains a replica of the dataset
- Demonstrates resilience under node failures
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Apache Cassandra
- Distributed, peer-to-peer NoSQL database
- Handles data replication and fault tolerance
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Spring Boot Backend (Java)
- Exposes REST APIs
- Writes sensor data to Cassandra
- Reads replicated data for visualization
-
React + TypeScript Dashboard
- Real-time data visualization
- Polls backend APIs
- Shows system behavior during failures
- Temperature sensor reads data on Seed Node
- Spring Boot backend receives sensor data via REST
- Data is written to Apache Cassandra
- Cassandra replicates data to the Peer Node
- Dashboard fetches and visualizes data in real time
- When a node goes down, replication and recovery behavior can be observed
- Shutting down one Cassandra node
- Observing continued read/write availability
- Watching replicas converge after node recovery
- Monitoring latency and data consistency during failures
This project was presented as a live lightning talk/demo at:
- Community Over Code 2025, Minneapolis, Minnesota.
- PyData Boston 2025
The demo showcased how distributed systems behave under node failures, using real hardware, real data, and real infrastructure components.
Most distributed systems tutorials stop at “it works.”
This project goes further:
- It expects failure
- It embraces imperfect networks
- It shows how production systems are designed to survive, not avoid failure
- Apache Cassandra (distributed database)
- Java + Spring Boot (REST APIs)
- React + TypeScript (frontend dashboard)
- Recharts (data visualization)
- Raspberry Pi 4 (2 nodes)
- DS18B20 temperature sensor
- Docker & Docker Compose
- Python (sensor reader & heartbeat scripts)
- Switch & Ethernet cables
Distributed systems are not about avoiding failure;
they are about continuing to function when failure is inevitable.