Implementing Raft: Part 0 - Introduction - Eli Bendersky's website
This is the first post in a multi-part series describing the Raft distributed consensus algorithm and its complete implementation in Go. Here is a complete list: Part 0: Introduction (this post) Part 1: Elections Part 2: Commands and log replication Part 3: Persistence and optimizations Raft is a relatively new algorithm (2014), but it's already being used quite a bit in industry. The best known e
Fuzzing Raft for Fun and Publication - Rest for the Wicked
Research on distributed systems is often motivated by some variation of the following: Developers of distributed systems face notoriously difficult challenges, such as concurrency, asynchrony, and partial failure. That statement seems convincing enough, but it’s rather abstract. In this post we’ll gain a concrete understanding of what makes distribution so challenging, by describing correctness bu
Scaling Raft
In CockroachDB, we use the Raft consensus algorithm to ensure that your data remains consistent even when machines fail. In most systems that use Raft, such as etcd and Consul, the entire system is one Raft consensus group. In CockroachDB, however, the data is divided into ranges, each with its own consensus group. This means that each node may be participating in hundreds of thousands of consensu
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Implementing Raft: Part 1 - Elections - Eli Bendersky's website
GitHub - adjoint-io/raft: Raft Consensus Algorithm
RAFT Explained – Part 1/3: Introduction to the Consensus Problem - Container Solutions
https://raftconsensus.github.io/
