The Distance Problem: Why Centralized Data Paths Cost You Latency, Uptime, and Money
Blog post from Harper
Geographic distance imposes unavoidable latency, availability, and egress costs on distributed applications, particularly when dependent requests repeatedly cross regions, so architecture choices must balance consistency, speed, operational complexity, and data residency. Leader-based, multi-leader, leaderless, and consensus systems offer different trade-offs: replicas can reduce read latency but may be stale, multi-writer systems require conflict handling, quorum systems add operational burden, and globally serializable consensus requires cross-region coordination on writes. Harper is presented as an eventually consistent, peer-to-peer alternative that colocates application logic, storage, caching, and messaging in one process, removing internal network hops while selectively replicating data among regions. Its local operations are ACID and serializable, but cross-node replication is asynchronous and uses last-writer-wins conflict resolution with optional CRDT support, making it unsuitable for workloads requiring strict global serializability or lossless concurrent writes. The text recommends benchmarking centralized versus colocated reads across distant regions with open-loop load generation and percentile measurements, predicting that colocated reads can remain near local latency while centralized reads reflect intercontinental round-trip times.
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