| I have many recommendations of different kinds: ## Blogs: - http://muratbuffalo.blogspot.com/ - https://bartoszsypytkowski.com/ - https://decentralizedthoughts.github.io/ - https://www.the-paper-trail.org/ - https://blog.acolyer.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...) |
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.