Quorum-free replicated state machine built atop S3
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Hi HN,I’m sharing the alpha release of S2C, a state machine replication system built atop S3.The goal is to enable a distributed application to maintain consistent state without needing a quorum of nodes for availability or consistency.The idea came from a side project that was using S3 and where I needed strongly consistent distributed state but wanted to avoid adding a separate consensus dependency. I initially tried to use S3 directly for coordination, but it became messy. Eventually, I realized I need a replicated state machine with a deterministic log, and then it ended up as a standalone project.To mitigate S3's latency and API costs, it uses time- and size-based batching by default.S2C supports: - Linearizable reads and writes (with single node) - Exactly-once command semantics (for nodes with stable identities) - Dynamic node joins and cold-start recovery from zero nodes - Split-brain safety without clocks or leases - Snapshotting, log truncation, etc.Of course, it trades latency and S3 operation costs for operational simplicity - not meant to replace high-throughput Raft rings. And clearly, only usable in architectures that already use S3 (or compatible with similar guarantees).It has passed chaos/fault-injection tests so far (crashes, partitions, leader kills); formal verification planned.It’s still alpha, but I’d love for people to try it, experiment, and provide feedback.If you’re curious, the code, and an extensive deep dive guide are here: [https://github.com/io-s2c/s2c]
HN · launched Jan 31, 2026 · 6 upvotes (top 75%) · 0 views
Niche: distributed systems frameworks · 62 launches, 2 in the last 7 days ▼ -78% · Explore this niche →
Category and tags
- Horizontal
- Data infrastructure
- Developer
- Not AI
- Hobby / open-source project
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More like this: all 62 launches in distributed systems frameworks →
Could you build this?
No Designing and verifying a quorum-free state machine replication protocol on top of object storage requires formal methods and deep distributed systems consensus expertise.
What it would actually take: Building S2C involves implementing distributed consensus or conditional writes (using S3 conditional PUTs / object locking) to simulate linearizable logs. It requires formal verification via TLA+, handling network partitions, split-brain scenarios, and rigorous chaos testing (Jepsen-style), which demands senior distributed systems engineering skills.
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