THE VIDEO SHELF · paxos consensus
Paxos lecture (Raft user study)
John Ousterhout's slides-and-voiceover lecture on Paxos, made for the Raft user study comparing how students learn Raft and Paxos. It is a full introduction to the Paxos consensus algorithm.
Why HN readers recommended it
Recommended as a clear, lucid way to learn Paxos and Multi-Paxos, ideally alongside the companion Raft video.
This is a summary from the source dataset, not an endorsement by Hacker News or the video creator.
Video & recommendation details
- Creator / channel
- Diego Ongaro
- Topic
- paxos consensus
- Format
- lecture
- Level
- intermediate
- HN recommenders in dataset
- 6
- HN mentions in dataset
- 7
- Recommendation years in dataset
- 2013–2024
These counts and years describe the included Hacker News records; they are not YouTube views or the video’s publication date.
From the original HN conversations
Excerpts from the recorded comments. Follow each source for the full comment and surrounding discussion.
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 …
krat0sprakhar on Hacker News · 2014-10
In The Raft Consensus AlgorithmI recently took a Distributed Systems course, and I also thought it was very interesting and unexpected how in the most basic form of Paxos, there is no concept of node roles or hierarchy like leader/follower, master/replica, etc. The base case is that all nodes …
cljacoby on Hacker News · 2024-02
In The leadership myth in replicated databases (2023)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 …
tomjohnson3 on Hacker News · 2013-09
In ZooKeeper vs. Doozer vs. Etcd
Summaries, classifications and recommendation records are from the HackerTube source dataset. Read about this library and its limitations.