Philosophy of Everything

A trilogy about Data Consistency and how to workaround the CAP and PACELC theorems: 1. First issues with multi-region and multi-cloud software scalability 2. Solutions to have enough Consistency without sacrificing Availability and Latency 3. Theoretical arguments on the nature of CAP/PACELC problem and why you cannot find a better solution than the above one Dear reader, please leave a message if you exist! ;)  Also, please share this article if you find it interesting. Thank you.

moved to  https://software.mihvoi.ro/2026/04/3-data-consistency-and-theory-of.html "If a tree falls in a forest and no one is around to hear it, does it make a sound?" If a system has an inconsistency but no one is able to observe it, is it still an inconsistency? Introduction We need to scale data processing systems geographically to achieve lower Latency and (at least partial) Availability in case of network Partitioning. But CAP / PACELC tells us that we cannot achieve strong Consistency in this case. When we increase the Consistency requirements, we have to accept lower Availability and higher Latency. What is the minimum consistency level that we need? If eventual consistency is enough for your system, things are pretty clear and relatively simple. Most probably you want to achieve Strong Eventual Consistency that is relatively cheap and provides nice guaranties. For this you will have to you something like CRDT . Some theoretical results assure us that you cannot fin...

We love "cutting edge" technology. We need to have the latest gadget, we need to use this new trendy framework, we need to use the latest update of our favorite software. Newer should be better, right? Actually, each new technology brings a promise of improvement and an additional hidden small risk. You are trying the new innovative painkiller drug that promises to solve your low intensity, but still disturbing, migraines . You can get a real improvement on your condition, you could get no significant improvement or, with a small probability, you could die, like in the recent drug trial in France . Indeed, that was an experimental drug, and many others that took the drug were not affected. Well, this is exactly the danger: if the really bad effects only happens with low probability, it might not even be caught in the trial period...

Human intuition behaves similar to a neural network software algorithm: it produces an estimation of a certain probability, based on prior experience. The same with an artificial neural network, human intuition needs to have sufficient training experiences on that field so it can extract regularities. The training experiences should be able to provide adequate and rapid feedback that can be used to adjust the internal model, for both biological and software neurons.