Lecture 6: Fault Tolerance: Raft (1)

The podcast features a lecture on the Raft consensus algorithm, a method for achieving fault tolerance in distributed systems. The speaker introduces the problem of split-brain scenarios in replicated systems and explains how Raft uses majority voting to avoid this issue. The lecture covers the architecture of a Raft replica, the flow of client requests, and the role of logs in ordering operations, ensuring data consistency, and enabling recovery after crashes. The discussion also includes leader election, the importance of randomized election timers, and how Raft handles log divergence after failures.