What are the common patterns/trade-offs in large-scale system design that:

  1) Give you a clear picture of the design space
  2) Help you evaluate & categorise existing solutions better?

We have all have come across fundamental trade-offs in system design, such as:

  1. CAP Theorem (or variations thereof)[1]
  2. RUM (Read-Update-Memory) Conjecture[2]
  3. Latency vs. Throughput (& Queuing Theory)[3]

Are there any research papers/book/blogs/videos where all such fundamental trade-offs for large-scale system design have been documented? If not, what other fundamental trade-offs do you swear by when designing or evaluating large-scale systems?

  [1] https://dbmsmusings.blogspot.com/2010/04/problems-with-cap-and-yahoos-little.html
  [2] http://daslab.seas.harvard.edu/rum-conjecture/
  [3] https://blog.danslimmon.com/2019/02/26/the-latency-throughput-tradeoff-why-fast-services-are-slow-and-vice-versa/