Consensus: Bridging Theory and Practice a Dissertation Submitted to the Department of Computer Science and the Committee on Graduate Studies of Stanford University in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy

Distributed consensus is fundamental to building fault-tolerant systems. It allows a collection of machines to work as a coherent group that can survive the failures of some of its members. Unfortunately, the most common consensus algorithm, Paxos, is widely regarded as difficult to understand and implement correctly. This dissertation presents a new consensus algorithm called Raft, which was designed for understandability. Raft first elects a server as leader, then concentrates all decision-making onto the leader. These two basic steps are relatively independent and form a better structure than Paxos, whose components are hard to separate. Raft elects a leader using voting and randomized timeouts. The election guarantees that the leader already stores all the information it needs, so data only flows outwards from the leader to other servers. Compared to other leader-based algorithms, this reduces mechanism and simplifies the behavior. Once a leader is elected, it manages a replicated log. Raft leverages a simple invariant on how logs grow to reduce the algorithm’s state space and accomplish this task with minimal mechanism. Raft is also more suitable than previous algorithms for real-world implementations. It performs well enough for practical deployments, and it addresses all aspects of building a complete system, including how to manage client interactions, how to change the cluster membership, and how to compact the log when it grows too large. To change the cluster membership, Raft allows adding or removing one server at a time (complex changes can be composed from these basic steps), and the cluster continues servicing requests throughout the change. We believe that Raft is superior to Paxos and other consensus algorithms, both for educational purposes and as a foundation for implementation. Results from a user study demonstrate that Raft is easier for students to learn than Paxos. The algorithm has been formally specified and proven, its leader election algorithm works well in a variety of environments, and its performance is equivalent to Multi-Paxos. Many implementations of Raft are now available, and several companies are deploying Raft.