Cloud systems are undergoing an architectural shift. Traditional shared-nothing designs struggle to deliver the elasticity, availability, and operational simplicity that the cloud demands. The new generation of cloud systems (Amazon Aurora, Microsoft Socrates, Google AlloyDB, Snowflake, S3 Athena, Neon) embrace disaggregation, and decouple compute, storage, and increasingly, logs. This separation allows independent scaling, faster failover, and shared durable storage across tenants, but it also brings new performance tradeoffs and system design challenges.

In this talk, I will survey why disaggregation matters, what we have learned from the past decade of industrial systems, and where research and practice are headed next. I will explain the economic and operational motivations (elastic scaling, fault isolation, pooling) and discuss how disaggregation reshapes core database components like logging, recovery, and concurrency control. I'll discuss how design choices like "log-as-database", shared-storage replication, and caching tiers affect throughput, latency, and cost.

Finally, I’ll connect these modern architectures back to the timeless ideas in distributed systems, using Lamport's proposers, acceptors, and learners as a way to reason about how we disaggregate coordination, availability, durability, and computation. Viewed through this lens, disaggregation is our new Paxos: an architecture for separating roles so systems can scale, fail, and recover gracefully.