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eli.thegreenplace.net | ||
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reubenbond.github.io
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| | | | | reublog | |
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chelseatroy.com
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| | | | | In December, I took a course in which we attempted to implement the Raft distributed consensus algorithm fromthis paper. Parts 1-5 of this series share insights from the course. From then on, I'm guiding you through my continued work implementing Raft "for fun" (I know. I don't understand me, either). Here's where you can see... | |
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tomaugspurger.net
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| | | | | Last week, I was fortunate to attend Dave Beazley's Rafting Trip course. The pretext of the course is to implement the Raft Consensus Algorithm. I'll post more about Raft, and the journey of implementing, it later. But in brief, Raft is an algorithm that lets a cluster of machines work together to reliably do something. If you had a service that needed to stay up (and stay consistent), even if some of the machines in the cluster went down, then you might want to use Raft. | |
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briankung.dev
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| | | I survived David Beazley's weeklong course on the Raft consensus algorithm that powers technologies like Kubernetes, MongoDB, and Neo4j. Image from https://raft.github.io/ The Raft Consensus Algorithm is a way for a gaggle of computers to agree on a sequence of events, or a "log" of events. Raft is useful for things like databases - once... | ||
