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hugofirth | 5 years ago
## Blogs:
- http://muratbuffalo.blogspot.com/
- https://bartoszsypytkowski.com/
- https://decentralizedthoughts.github.io/
- https://www.the-paper-trail.org/
- https://pathelland.substack.com/
## Other web resources
- https://aws.amazon.com/builders-library/ - set of resources from Amazon about building distributed systems
- https://www.youtube.com/playlist?list=PLeKd45zvjcDFUEv_ohr_H... - lecture series from Cambridge
## Books
- https://www.cl.cam.ac.uk/teaching/1213/PrincComm/mfcn.pdf - A great book on the maths of networking (probability, queuing theory etc...)
mjb|5 years ago
I wrote this post a while ago, aiming to answer a similar question about finding paper: http://brooker.co.za/blog/2020/05/25/reading.html One key point there is that there are, in my mind, multiple 'modes' of reading, and I like to use different approaches to finding material for different modes. Those blogs you list are great for curiosity mode. Another great resource there is Twitter: following distributed systems practitioners and researchers, and seeing what they tweet about. When I read a (recent) paper I really like, I often see if the authors are active on Twitter and follow them there if they are.
It's also important not to weight too much on recency. A lot of the canon is actually more approachable than newer papers. For example, Lamport's classic "Time, Clocks" (https://www.microsoft.com/en-us/research/publication/time-cl...) and distributed snapshot (https://www.microsoft.com/en-us/research/publication/distrib...) papers, and Gilbert and Lynch's CAP paper (http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.67....) are approachable without deep background or systems knowledge. Similarly, John Little's " A Proof for the Queuing Formula: L = λW" (https://pubsonline.informs.org/doi/abs/10.1287/opre.9.3.383) is quite approachable if you have a math background but no systems knowledge, and is one of the foundational results behind the practice of building stable systems.
I've got some longer-form dives into researcher's work here: http://brooker.co.za/blog/2014/03/30/lamport-pub.html http://brooker.co.za/blog/2014/09/21/liskov-pub.html http://brooker.co.za/blog/2014/05/10/lynch-pub.html
Finally, books. There are a couple recommendations for Martin Kleppman's Designing Data-Intensive Applications book, which I like a whole lot. Alex Petrov's "Database Internals" is also a very approachable introduction. I wish every practitioner in the field would read Harchol-Balter's Performance Modeling and Design of Computer Systems.
synctext|5 years ago
Material from a university master course on distributed systems engineering. We developed our own university material in .ipynb format at Github. Should give you the basics in 5 days. Applies distributed systems theory in 5 steps. Most improvements in past decade are not due to hardware improvement, but algorithm and tooling advances I believe.
- Distributed systems. Overlays and communication network. Introduction to simulation framework https://github.com/grimadas/BlockchainEngineering/blob/maste...
- Gossip. Convergence of the transactions, information https://github.com/grimadas/BlockchainEngineering/blob/maste...
- Faults in distributed systems: crashes and disruptions https://github.com/grimadas/BlockchainEngineering/blob/maste...
- Malicious nodes, adversary model https://github.com/grimadas/BlockchainEngineering/blob/maste...
- Consensus and agreement despite malicious nodes https://github.com/grimadas/BlockchainEngineering/blob/maste...
hugofirth|5 years ago
I also agree with the recommendations for "Designing Data-Intensive Applications" and "Database Internals". Though, having read the latter for a book club at $employer, I felt it served better as a sort of "index for the space" for people who already had some DB experience, rather a true introduction.
mandeepj|5 years ago
What's your twitter handle?
Vervious|5 years ago
mjb|5 years ago
See https://lamport.azurewebsites.net/pubs/pubs.html#paxos-simpl... Ok, might not be fair to call it an error, but it is super confusing, and a great example of Lamport's larger point that writing prose about these things is really hard, and we need better tools (like TLA+).