"Immutable Values in the Big Wide World" by Tim Ewald and Paul deGrandis

Value-based architectures with immutable data enable reliable, scalable distributed systems by separating reads from writes and allowing independent scaling of components

Using S3 as the backing store for immutable values and deltas provides effectively infinite scalability while keeping operational costs low compared to managing database clusters

Hybrid logical clocks enable coordination-free transactions and causal consistency across distributed systems without complex consensus protocols

In-memory computation on large machines with deterministic functions is often more efficient and simpler than distributed microservices architectures

Checkpointing with versioned immutable values enables reliable disaster recovery and debugging by allowing system state replay

Separating data producers (processors) from consumers (observers) allows flexible scaling and partial data replication based on specific needs

Moving complexity to build/design time rather than runtime reduces operational costs and improves reliability

Using deltas instead of full value updates enables efficient data transfer and storage while maintaining consistency

Value-based architectures support multi-region deployment and cloud/prem hybrid models by leveraging cloud storage replication

Critical to consider economics and costs when designing distributed systems - focus on linear rather than non-linear cost growth as system scales