I just wrote and published an essay on Multi-Paxos and how it helps distributed databases achieve consensus.
This week, I dug deeper into Paxos (something I have always wanted to do) and explored how distributed databases use it to reach agreement when nodes fail, messages are delayed, or networks are partitioned.
The write-up covers how Paxos works, its intuition, optimizations with Multi-Paxos for distributed databases, common issues, further optimizations, and real-world limitations. As always, it is no-fluff, highly practical, and packed with code snippets and edge cases.
If you want to understand how distributed databases maintain consistency across data centers, why quorums matter, or how systems recover from leader failures without losing data, this essay will give you a solid mental model.
Give it a read.