RAFT protocol is a well-known protocol for consensus in Distributed Systems. Want to learn how consensus is achieved in a system with a large amount of data such as Axon Server’s Event Store? Join this talk to hear about all specifics regarding data replication in highly available Event Store! Axon is a free and open source Java framework for writing Java applications following DDD, event sourcing, and CQRS principles. While especially useful in a microservices context, Axon provides great value in building structured monoliths that can be broken down into microservices when needed. Axon Server is a messaging platform specifically built to support distributed Axon applications. One of its key benefits is storing events published by Axon applications. In not so rare cases, the number of these events is over millions, even billions. Availability of Axon Server plays a significant role in the product portfolio. To keep event replication reliable we chose RAFT protocol for consensus implementation of our clustering features. In short, consensus involves multiple servers agreeing on values. Once they reach a decision on a value, that decision is final. Typical consensus algorithms make progress when any majority of their servers is available; for example, a cluster of 5 servers can continue to operate even if 2 servers fail. If more servers fail, they stop making progress (but will never return an incorrect result). Join this talk to learn why we chose RAFT; what were our findings during the design, the implementation, and testing phase; and what does it mean to replicate an event store holding billions of events!

1. Axon Server went RAFTing
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2. Milan Savić
Software Engineer @ AxonIQ
milan@axoniq.io
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m1l4n54v1c
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3. Axon
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4. @MilanSavic14

5. RAFT
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6. RAFT States
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7. Terms
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8. Leader Election
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• RequestVote RPC

9. Log Replication
• AppendEntries RPC
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10. Log Compaction
• InstallSnapshot RPC
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11. Cluster membership changes
• Add Node
• Remove Node
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12. Multi RAFT
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13. Testing
• Development environment
• Build environment
• Cloud environment
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• Unit Tests
• Integration Tests
• Automated Tests
• Chaos experiments
Test Types Environments

14. Lessons Learned
• Start as simple as possible
• Don’t deviate from the RAFT paper
• Timing is important
• Large state makes Install Snapshot more difficult
• gRPC can be tricky
• Test, test, test
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15. Resources
• https://raft.github.io/
• https://axoniq.io/
• In Search of an Understandable Consensus Algorithm
(Extended Version) - Diego Ongaro and John Ousterhout,
Stanford University
• CONSENSUS: BRIDGING THEORY AND PRACTICE – Diego
Ongaro
• http://gousios.org/courses/bigdata/book/introduction-to-
distributed-systems.html
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16. Gracias!
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Thank you!
Hvala!