That's a good summary by Aphyr he said it better than me of course.

Now I know it is Eric Brewer himself who wrote that announcement. So I make no claim disproving him or knowing better than, I am just struggling to understand the implications. That CA terms has caused a lot of confusion (at least to me) and so far from what I have read talking about CA systems doesn't make sense.

Never heard of harvest & yield that's an interesting perspective. Thanks for the link, I'll need to go and ponder that for a while. It seems to take a probabilistic approach to these constraints.

But even in that article the description of CA systems is confusing. They describe it it means system can work only in the absence of a partitions. Ok, but then what does it do in the case of partition? The system will presumably do something accept requests, refuse to reply, ... I don't see how it can be both C and A though. That is why I equate that choice with a statement of "I believe partitions will never happen", which I personally think is not realistic.

A useful perspective for me has been that C, A, and P are spectra rather than all-or-nothing. A system may bend a bit on availability when some of its replicas are partitioned, because there are fewer servers that can respond at all, smaller aggregate queue depth etc... It has been said that consistency was specified rather poorly in Brewer's original paper, and we've since seen work that dives into the consistency spectrum. Peter Balis's "HAT not CAP" paper is an often-cited example of such work. Aphyr again comes through with a summary of some of these ideas in https://aphyr.com/posts/313-strong-consistency-models .

We know that we can't have 100% harvest and 100% yield in the presence of partitions. We can play with different things though to shape the curve of these things as conditions worsen, however