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Ravi Mourya
Ravi Mourya

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๐Ÿ–ฅ๏ธ Understanding the Raft Consensus Algorithm: A Comprehensive Guide ๐Ÿ“š

๐Ÿ–ฅ๏ธ Understanding the Raft Consensus Algorithm: A Comprehensive Guide ๐Ÿ“š

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. ๐ŸŒ

Key Points:

๐Ÿ”ธConsensus Protocols: Ensures agreement on a single value or state among servers.

๐Ÿ”ธRaft Structure: Involves Leaders, Followers, and Candidates.

๐Ÿ”ธTerms and Logs: Uses terms to coordinate actions and maintain consistency.

๐Ÿ”ธRPCs: Communication through RequestVotes and AppendEntries RPCs.

๐Ÿ”ธLeader Election: A defined process to maintain system consistency.

๐Ÿ”ธLog Replication: Ensures all nodes have identical logs for consistency.

๐Ÿ”ธAdvantages of Raft:
Easy to understand and implement.
Fault-tolerant and ensures strong consistency.
Modular approach.

๐Ÿ”ธLimitations:
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! ๐Ÿ”—

Understanding the Raft Consensus Algorithm: A Comprehensive Guide

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