๐ฅ๏ธ Understanding the Raft Consensus Algorithm: A Comprehensive Guide ๐
Ensuring consistency across distributed systems, even amidst failures, is vital. The Raft Consensus Algorithm, introduced by Diego Ongaro and John Ousterhout in 2013, simplifies this process with its clear and understandable approach. ๐
Key Points:
๐ธConsensus Protocols: Ensures agreement on a single value or state among servers.
๐ธRaft Structure: Involves Leaders, Followers, and Candidates.
๐ธTerms and Logs: Uses terms to coordinate actions and maintain consistency.
๐ธRPCs: Communication through RequestVotes and AppendEntries RPCs.
๐ธLeader Election: A defined process to maintain system consistency.
๐ธLog Replication: Ensures all nodes have identical logs for consistency.
๐ธAdvantages of Raft:
Easy to understand and implement.
Fault-tolerant and ensures strong consistency.
Modular approach.
๐ธLimitations:
Potential leader bottleneck.
No Byzantine Fault Tolerance.
Complexity in managing membership changes.
Check out my related blog on Apache Kafka to see how Raft is utilized in Kafka's new KRaft architecture! ๐
Understanding the Raft Consensus Algorithm: A Comprehensive Guide
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