Raft
Raft is a distributed consensus algorithm that uses leader election and replicated logs to coordinate nodes and maintain consistent replicated state despite failures.
ScyllaDB in Action
Raft is a distributed consensus algorithm designed to make replicated-state coordination understandable through leader election, log replication, and safety rules.
- How it is used
- Provides strongly ordered internal metadata changes, including schema and topology updates.
- How deep it goes
- Explains leader election, replicated-log commits, majority acknowledgment, and failure trade-offs without detailing implementation mechanics.
- Examples
- Uses concurrent schema updates and a leader-to-follower log-append diagram to illustrate agreement.
- What you can do after
- Evaluate/understand why internal cluster changes favor Raft consistency despite leader-election downtime.
Kafka for Architects
Raft is a consensus algorithm that coordinates replicated state among nodes and commits updates after acknowledgment by a quorum.
- How it is used
- Coordinates Kafka controller state and metadata updates through quorum-based replication.
- How deep it goes
- Explains leader commitment, follower acknowledgment, election safety, quorum loss, and metadata-log boundaries.
- Examples
- Uses metadata-log replication, controller quorum, data-center placement, snapshots, and broker metadata requests as concrete examples.
- What you can do after
- Evaluate controller placement and metadata-consistency consequences using quorum and leader-election behavior.
Apache Kafka in Action
Raft is a distributed consensus algorithm and protocol for coordinating replicated state machines so cluster nodes agree on replicated state.
- How it is used
- Coordinates Kafka brokers, metadata, partition assignments, leader elections, and failover through an integrated controller cluster.
- How deep it goes
- Explains KRaft roles, controller quorum sizing, metadata storage, and migration steps without detailing Raft internals.
- Examples
- Uses one-, three-, and five-controller configurations plus ZooKeeper-to-KRaft metadata migration as operational examples.
- What you can do after
- Operate/configure Kafka KRaft clusters with appropriate controller counts and understand the path from ZooKeeper coordination to KRaft.
Related concepts
- consensuskind of · Consensus is sufficient agreement among participants or processes on a shared decision, value, state, assessment, or outcome.
- KRaftimplemented by · KRaft is Apache Kafka’s Raft-based metadata-management mode, using an internal controller quorum instead of ZooKeeper.
- replicated state machineimplements · A replicated state machine is a set of replicas that apply the same ordered operations to maintain equivalent state across nodes.
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