DeepStream-dGPU-Installation VS maelstrom

Maelstrom [1], a workbench for learning distributed systems from the creator of Jepsen, includes a simple (model-checked) implementation of Raft and an excellent tutorial on implementing it.

Raft is a simple algorithm, but as others have noted, the original paper includes many correctness details often brushed over in toy implementations. Furthermore, the fallibility of real-world hardware (handling memory/disk corruption and grey failures), the requirements of real-world systems with tight latency SLAs, and a need for things like flexible quorum/dynamic cluster membership make implementing it for production a long and daunting task. The commit history of etcd and hashicorp/raft, likely the two most battle-tested open source implementations of raft that still surface correctness bugs on the regular tell you all you need to know.

The tigerbeetle team talks in detail about the real-world aspects of distributed systems on imperfect hardware/non-abstracted system models, and why they chose viewstamp replication, which predates Paxos but looks more like Raft.

[1]: https://github.com/jepsen-io/maelstrom/

[2]: https://github.com/tigerbeetle/tigerbeetle/blob/main/docs/DE...

I've tried to run the echo example and I'me getting some problems. I assume it works as the same example in the maelstrom's getting started ready (https://github.com/jepsen-io/maelstrom/blob/main/doc/01-getting-ready/index.md).

Love it. Thanks for putting this together! The actual challenges here [0].

Though I'm curious: are these different from the chapters in the Maelstrom documentation [1]? There seems to be a bit of overlap anyway.

[0] https://fly.io/dist-sys/

[1] https://github.com/jepsen-io/maelstrom#documentation