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    Raft lecture (Raft user study)

    Diego Ongaro

    4 HN recommenders · recommended in 7 months, 2013–2025

    YouTube

    58:17 · 87K views · Aug 15, 2013

    John Ousterhout lectures on the Raft consensus algorithm, made for the Raft user study comparing how students learn Raft and Paxos. It covers leader election and log repair.

    HN commenters recommend it as a clearer introduction to Raft than the paper and as part of a well-designed understandability study.

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    9 comments from Hacker News

    1. @krat0sprakharOct 2014· in “The Raft Consensus Algorithm”

      One of the most lucid explanations of the Raft Consensus Algorithm that I've ever seen is the one in John Ousterhout and Diego Ongaro's Raft User Study[0]. The 2 videos do an excellent job of explaining both the Paxos and Raft algorithms and the key differences between them. John's narration is extremely clear and the slides are very informative. Definitely recommended! Raft is a consensus algorithm designed to be easier to understand than Paxos. To measure Raft's understandability, we conducted an experimental study using CS students at two universities. We recorded a video lecture of Raft and another of Paxos, and created corresponding quizzes. This page makes our materials available for anyone interested. We think these are valuable resources for anyone learning consensus (whether Raft or Paxos or both). [0] - [LINK] Raft Video - this video Paxos Video - [LINK]

      Strongly recommendsView on HN
    2. @tomjohnson3Sep 2013· in “ZooKeeper vs. Doozer vs. Etcd”

      one other thing to keep in mind is that the underlying algorithms (zab and raft) provide different guarantees. for example, zookeeper/zab allows reading directly from followers with a guarantee to get at least a past value that won't be rolled back. this was one reason zookeer didn't use paxos: [LINK] in my understanding, raft doesn't allow reading directly from followers, because the follower logs may get repaired/rolled-back when a new leader is elected. (though i'm sure an implementation can tweak the protocol to provide this support.) that said, raft has a lot of interesting applications, and, in my opinion, is definitely more understandable than the many versions of paxos. (implementing zab yourself, at this point, would be a futile exercise.) i found the videos from the raft user study to be very well done (and easier to understand than even their paper): raft: [LINK] paxos: this video ...however, i think they did paxos a disadvantage by not just focusing on multi-paxos (which is probably the most common implementation). but, it's certainly fair to say that info about paxos is spread out far and wide...with perhaps too many knobs to turn and implementation-related details to fill in yourself. as a side note: i've just started implementing raft in a set of libraries (multiple languages) that will be open source - along with other protocols.

      RecommendsView on HN
    3. @pkjNov 2013· in “The Writings of Leslie Lamport”

      A really good intro to Raft --> this video Very useful if you are into distributed systems and would like to see a practical implementation with clear examples.

      RecommendsView on HN
    4. @sathish316Aug 2025· in “The Raft Consensus Algorithm (2015)”

      This YouTube video by the Raft creators (linked at the bottom of the page) gives a solid explanation of Raft internals - this video

      RecommendsView on HN
    5. @deathanatosSep 2014· in “Raft: Understandable Distributed Consensus”

      > and does not address the situation of two nodes having conflicting sets of data (for instance from network partition). I believe it does address this. Each log entry is either committed or not; an entry can only be committed if it has been replicated to a majority of nodes. Any node that lacks a committed entry cannot be elected master because of the election rules: a node will not vote for another node less complete than itself. Since a committed entry has been replicated to a majority, a node lacking that entry cannot receive a majority of the votes. (Thus the committed log entries will always be the same on all nodes (though some may be behind, and may only have a subset), which is the purpose of the protocol.) > Considering it basically relies on random chance (I.E. who receives the message first) to elect a master, has basically no real way of resolving a conflict in election This is mostly true. The PDF slides I link to below recommend that the election timeout be much greater than the broadcast time, the idea being that things should work out in the long run. Highly recommend the PDF slides here, as they explain it better than I can: [LINK] — there's also a YouTube talk here: this video > Considering all that, this protocol doesn't seem very interesting (from a use-case point of view). I'd love to hear of alternatives.

      CitesView on HN