When building a distributed system one principal goal is often to build in fault-tolerance. That is, if one particular node in a network goes down, or if there is a network partition, the entire cluster does not fall over. The cluster of nodes taking part in a distributed consensus protocol must come to agreement regarding values, and once that decision is reached, that choice is final. Distributed Consensus Algorithms often take the form of a replicated state machine and log. Each state machine accepts inputs from its log, and represents the value(s) to be replicated, for example, a hash table. They allow a collection of machines to work as a coherent group that can survive the failures of some of its members.