Latency and Tail Latency at Scale in Distributed Systems

Distributed Systems Series — Part 5.2: Scalability & Performance Why Latency at Scale Is a Different Problem Post 5.1 established what scalability means and identified Amdahl’s Law as the mathematical ceiling on parallelism. This post addresses the latency dimension of scalability — specifically why latency behaviour at scale is fundamentally different from latency at low … Read more

What Scalability Really Means in Distributed Systems

Distributed Systems Series — Part 5.1: Scalability & Performance What Scalability Actually Means Parts 1 through 4 of this series established how distributed systems work correctly and survive failures. Part 5 addresses the final dimension: how do systems handle growth? Scalability is one of the most overused and least precisely defined terms in software engineering. … Read more

Performance Trade-offs in Distributed Systems: Replication vs Consensus

Performance trade-offs in distributed replication and consensus — write latency, tail latency, write vs read scalability, consensus throughput limits, batching and pipelining, geographic distribution costs, and backpressure design.