This project involved developing a distributed application that required extensive knowledge of sockets programming, Remote Procedure Calls (RPCs), scale-out techniques, networked storage, load balancing, fault tolerance, and cloud computing. The goal was to design a system that could effectively handle scalability and reliability challenges in a distributed environment.
A crucial component of this project was understanding and implementing the Raft protocol. The Raft protocol is a consensus algorithm designed to manage a distributed system’s state and ensure consistency across multiple nodes. It achieves this by electing a leader node that manages the log replication process, ensuring that all nodes in the cluster agree on the same state and can recover from failures.
The Raft protocol is closely related to the CAP theorem, which states that a distributed system can only achieve at most two of the following three guarantees: Consistency, Availability, and Partition Tolerance. Raft primarily addresses the Consistency aspect of the CAP theorem by ensuring that all nodes in the system have the same data, even in the presence of failures. By leveraging Raft, the application was able to maintain high consistency while also addressing the challenges of fault tolerance and scalability.
Useful links:
Raft Visualization
Best Raft Tutorial