raft
coyote
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raft | coyote | |
---|---|---|
7 | 13 | |
7,787 | 1,409 | |
1.5% | 0.7% | |
6.1 | 6.0 | |
3 days ago | 13 days ago | |
Go | C# | |
Mozilla Public License 2.0 | GNU General Public License v3.0 or later |
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raft
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Leader election library
Depending on your exact needs, you could try HashiCorp's Raft implementation: https://github.com/hashicorp/raft
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Implementing a distributed key-value store on top of implementing Raft in Go
I have found the performance tests very tricky to get to pass without having any input from others. The assignment is really very unforgiving, I would wager the test suite is comparable to how commercial Raft implementations are tested (e.g. https://github.com/hashicorp/raft)
- Raft Is So Fetch: The Raft Consensus Algorithm Explained Through Mean Girls
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Concurrency in Go is hard
While searching on GitHub, I found a pull request in the Raft implementation by Hashicorp (a distributed consensus algorithm), which we can use to demonstrate the following problem. Let’s start by showing the code (at api.go):
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rqlite, the light distributed database built with Go and SQLite, v7.2 now with autoclustering via DNS and DNS SRV
Production-grade distributed consensus system.
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Raft Consensus Protocol
In general Hashicorp's repos are high quality:
https://github.com/hashicorp/raft
Example application: https://github.com/Jille/raft-grpc-example
coyote
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Does Your Test Suite Account for Weak Transaction Isolation?
Or something like https://github.com/microsoft/coyote
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Implementing a distributed key-value store on top of implementing Raft in Go
Microsoft has a library/tool called Coyote* that helps with testing distributed systems; you can write tests/specifications, Coyote will systematically explore nondeterminism in your system and check if your tests still pass. If there's a failure, it'll show the sequence of events that led to the failing test.
I started a project to implement Raft with a KV-store on top, similar to the article, meaning to use Coyote to test it; I didn't get that far before losing interest, though. It's reassuring to read that it took Phil several months to write the code in the post, it's good to know that this is a decidedly nontrivial problem.
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What's the best way to test parallel jobs?
Something like coyote by MS?
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Using Java's Project Loom to build more reliable distributed systems
If you're looking for similar concurrency testing in the dotnet world, checkout Coyote:
https://microsoft.github.io/coyote/
https://innovation.microsoft.com/en-us/exploring-project-coy...
- Coyote: .NET library tool help ensure that your code is free of concurrency bugs
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TLA+ Graph Explorer
Visualizations do help a lot when model checkers and concurrency schedule exploration tools like Coyote find bugs. Coyote include the ability to visualize the traces if you express your concurrency using actors (see https://microsoft.github.io/coyote/#concepts/actors/state-ma...)
It also allows you to implement your own "logger" through which you can emit enough information to construct some cool visualizations. I had a lot of fun working on visualizing an implementation of Paxos using Coyote (then P#) (screenshot at https://ibb.co/TTk2hYb)
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Finding threading issues in code quickly
The closest I can think of is https://github.com/microsoft/coyote
What are some alternatives?
serf - Service orchestration and management tool.
tendermint - ⟁ Tendermint Core (BFT Consensus) in Go
torrent - Full-featured BitTorrent client package and utilities
etcd - Distributed reliable key-value store for the most critical data of a distributed system [Moved to: https://github.com/etcd-io/etcd]
dragonboat - A feature complete and high performance multi-group Raft library in Go.
DHT - BitTorrent DHT Protocol && DHT Spider.
ringpop-go - Scalable, fault-tolerant application-layer sharding for Go applications
grpc-go - The Go language implementation of gRPC. HTTP/2 based RPC
raft-grpc-example - Example code for how to get hashicorp/raft running with gRPC
Olric - Distributed in-memory object store. It can be used as an embedded Go library and a language-independent service.
go-health - Library for enabling asynchronous health checks in your service
redis-lock - Simplified distributed locking implementation using Redis