[mjb]

This is a very good list. Adrian's blog is, particularly, a treasure.

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]

More gentle introduction to timeless concepts that stood the test of times.

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]

I couldn't agree more about curiosity mode (I'm going to use that phrase liberally). Despite reading papers for many years, I rarely go in cold. I browse blog posts and twitter, ask myself a series of questions, then try to find/read papers to answer them. Of course this only leads to more questions, and so the journey continues.

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]

> Another great resource there is Twitter: following distributed systems practitioners and researchers, and seeing what they tweet about.

What's your twitter handle?