Distributed Systems Series — Part 5.5: Scalability & Performance The Most Powerful and Most Dangerous Scalability Technique Caching is the highest-leverage performance technique available in distributed systems. A cache hit costs microseconds. A database query costs milliseconds. A cache that absorbs 90% of read traffic reduces database load by 90%, reduces read latency by an … Read more
Distributed Systems Series — Part 5.3: Scalability & Performance The Write Scalability Problem Post 5.1 established that data scalability — the ability to handle growing data volume — is a distinct problem from load scalability. Post 3.8 established that write throughput in leader-based replication is bounded by the leader’s capacity — reads scale with replicas, … Read more
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
Distributed Systems Series — Part 5.4: Scalability & Performance Load Balancing Is Not One Algorithm Post 5.3 established that partitioning creates multiple independent nodes, each owning a subset of the data and serving reads and writes for that subset. Load balancing is the mechanism that distributes incoming traffic across those nodes — and across the … Read more
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
Distributed Systems Series — Part 4.9: Fault Tolerance & High Availability The Gap Between Designed Resilience and Actual Resilience Parts 4.1 through 4.8 have established the complete fault tolerance and high availability engineering stack. Post 4.1 defined the failure taxonomy. Posts 4.2 and 4.3 established the fault tolerance and redundancy foundations. Post 4.4 covered failure … Read more