0-1-1-understand-distributed-consensus-and-replication-protocols-fault-tolerance[0.1.1] The ability of a distributed system to continue correct operation despite component failures including node cr
0.1.2-understand-agreement[0.1.2] The property that a set of distributed processes reach the same decision outcome on a given value. Uniform agr
0.1.3-understand-consistency[0.1.3] The property that all nodes in a distributed system observe the same data state at the same time, or that oper
0.1.4-understand-distributed_transaction[0.1.4] A transaction that spans multiple independent nodes or services, requiring coordination across participants to
0.1-understand-core[0.1] the core subdomain of distributed consensus and replication protocols (4 concepts)
0.2.1-understand-failure_detector[0.2.1] Mechanism to distinguish crashed nodes from slow ones based on timeouts, heartbeats, or phi_accrual.
0.2.2-understand-replica_synchronization[0.2.2] Propagation of updates to ensure all replicas converge toward identical state.
0.2.3-understand-agreement_decide[0.2.3] A value reaches agreement when a quorum of nodes have accepted it; once decided, the value is stable and no co
0.2.4-understand-failure_mode[0.2.4] Classification of ways components can fail: crash_stop, crash_recovery, omission, timing, response, arbitrary_
0.2.5-understand-byzantine_failure[0.2.5] Component exhibits arbitrary behavior including lies, omissions, or timing violations.
0.2.6-understand-network_partition[0.2.6] Connectivity loss between node subgroups preventing inter-group communication.
0.2-understand-deep_consensus[0.2] the deep_consensus subdomain of distributed consensus and replication protocols (41 concepts)
0.3.1-understand-a005[0.3.1] Uniform agreement: all processes including those that later fail must decide on the same value, stricter than
0.3.2-understand-a002[0.3.2] Validity in agreement: the decided value must have been proposed by some process in the system, guaranteeing a
0.3.3-understand-a007[0.3.3] Quorum in agreement: a subset of processes sufficient to guarantee agreement can be reached, typically interse
0.3.4-understand-a008[0.3.4] Threshold in agreement: the minimum number of correct processes required to guarantee safety and liveness unde
0.3.5-understand-a009[0.3.5] Asymmetric agreement: one class of processes (e.g., primary) must agree while another class (e.g., backups) ma
0.3.6-understand-a004[0.3.6] Termination in agreement: every correct process eventually decides some value, ensuring the protocol makes pro
0.3-understand-deep_raft[0.3] the deep_raft subdomain of distributed consensus and replication protocols (28 concepts)
0.4.1-understand-consensus[0.4.1] Agreement on a single value among a set of distributed processes; the core problem consensus protocols solve.
0.4.2-understand-replicated_log[0.4.2] Ordered log of commands maintained across replicas; foundation of state machine replication.
0.4.3-understand-quorum[0.4.3] Subset of nodes sufficient for reads or writes; typically majority (n/2+1) for strong consistency.
0.4.4-understand-raft[0.4.4] Consensus algorithm designed for understandability, using leader election, log replication, and safety viaterm
0.4.5-understand-eventual_consistency[0.4.5] Given no new updates, all replicas will eventually converge to the same value.
0.4.6-understand-split_brain[0.4.6] Scenario where network partition causes multiple nodes to believe they are leader; resolved by quorum.
0-4-understand-distributed-consensus-and-replication-protocols[0.4] the distributed_consensus_and_replication_protocols subdomain of distributed consensus and replication protocols (123 concepts)
0-understand-distributed-consensus-and-replication-protocols[0] the distributed consensus and replication protocols library — every skill a certified region of the KB; call number = home : facets
using-distributed-consensus-and-replication-prUse the distributed consensus and replication protocols neurosymbolic module: RAG library, agent brain, growable KB — proof-checked