Review of "Making Geo-Replicated Systems Fast as Possible, Consistent when Necessary"

This paper aims to present a solution to the issue of maintaining consistency across multiple datacenters. As services become increasingly global, this becomes important to decrease latency to users across the globe, which also ensuring consistency.

The main idea is to separate operations into two categories: Blue (commutative, eventual consistency) and Red (strong consistency). They provide guidelines for how to determine what operations fall into each category, plus a system for forcing more operations to fit into the blue category: decomposing operations into generator and shadow operations, which can turn some non-commuting operators into commuting ones.

This work comes about most likely because the scale of geo-replication that exists now is significantly larger than in the past, and being able to maintain low latency (small consistency overheads) is very important - higher latency has a significant correlation to decreased per-user profits.

There are a number of trade-offs here. Using blue operations only guarantees eventual consistency, which still may come with issues ("eventual consistency is no consistency"), though it provides much higher speed. Breaking down operations into generator/shadow operations may grant much lower latency, but also makes things more difficult to reason about.

I can see this being influential in the future - services are becoming increasingly more global and people expect increasingly lower latencies, but application programmers also want consistency. This seems to provide a good framework for maintaining both of these things simultaneously.