Distributed Systems Classics (2017)

Some other classics (applied dist systems):

- DDB: https://www.allthingsdistributed.com/files/amazon-dynamo-sos...

- MapReduce: https://www.cs.princeton.edu/courses/archive/fall13/cos518/p...

- Spark/RDDs: https://www.usenix.org/system/files/conference/nsdi12/nsdi12...

- BigTable: https://static.googleusercontent.com/media/research.google.c...

This is not a bad list for sure. Here are some deeper cuts for those looking for something a bit less mainstream:

"The Maintenance of Duplicate Databases" https://datatracker.ietf.org/doc/html/rfc677 (AFAIK the genesis of the use of logical clocks in distributed systems).

"Chain Replication for Supporting High Throughput and Availability" https://www.usenix.org/legacy/event/osdi04/tech/full_papers/... (Chain replication is how a huge percentage of real-world cloud-scale data replication is done).

"Brewer’s Conjecture and the Feasibility of Consistent, Available, Partition-Tolerant Web Services" (The formalization of CAP, which caused a ton of very poor trade-off thinking in the decade that followed by defining Availability in a very goofy way. Still a classic.)

"Paxos Made Live" https://research.google/pubs/paxos-made-live-an-engineering-... (Brought a much-needed engineering perspective to a conversation that was largely theoretical up until this time.)

"Practical Byzantine fault tolerance" (Moved the conversation on Byzantine faults forward significantly).

This is just a short selection. There's so much good stuff going back in the 70s and 80s distributed database literature, for example (and in the modern systems and DB literature too).

I am a Lamport admirer.

I gradually realized that Lamport is more of the godfather of distributed system than Hinton is to deep learning. Lamport is less prominent than Shannon is to information theory. Shannon is the closest to any title of "gold-like" figure to a scientific discipline of universal relevance in modern society.

Lamport specifically revealed a philosophical connections between computer systems and physics, in the parallel of distributed consensus to relativity theory. To me, the enlightenment is that, the relations between events happening in a distributed system, is more fundamental than their absolute ordering, thus the central role of an "observer". I haven't really analyzed if this realization is from Lamport's papers, or my general reading and thinking, but I am moderately confident that general readings are heavily influenced by Lamport's papers, or can be traced back to be compatible with Lamport's thinking. I have not seriously study if this connection is valid in depth, which might be another pure amateur speculation of mine.

One thing I think Lamport falls short is that his writing is not easy to read and understand. I unconciously feel that Lamport (and Dario from Anthropic) probably share a hidden sense of intellectual supriority grew from their own experience throughout their career. So their writing (and Dario's gospel) all share a unchangable sense of narration from their own delicate and graceful ideas, much less of faciliating the understanding to their audience. In this cateogry, Shannon is abosolutely superior in any measure, in his writing, ideas are so naturally presented, although the implications of the ideas remain elusive due to the inherent depth.

Also, among the 3 prominent figures of modern AI: Hinton/Bengio are more like Shannon, Lecun is closer to Lamport.

Enough random rambling. Lamport, as indicated by the outweight presence in this list, is no doubt the single most important scientist in distributed systems.

As always, lists like these don’t include Joe Armstrong's PhD thesis “Making reliable distributed systems in the presence of software errors” - http://erlang.org/download/armstrong_thesis_2003.pdf

Lamport is the author of more than half of these, it's crazy how influential he is in this space

In addition to making LaTex which has almost nothing to do with it

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