Design a Key-Value Store: Scaling Bottlenecks
How a distributed key-value store breaks under scale: hot keys, rebalancing pain, cross-region replication latency, and compaction storms, with concrete mitigations interviewers expect.
How a distributed key-value store breaks under scale: hot keys, rebalancing pain, cross-region replication latency, and compaction storms, with concrete mitigations interviewers expect.
A complete interview framework for designing a distributed key-value store: LSM tree vs. B-tree trade-offs, compaction strategy, bloom filters, and consistent hashing for partitioning.
A component-level architecture breakdown for the news feed system design question: publisher-subscriber pattern, timeline service, cache warming, and post fanout, updated for July 2026 interviews.
Back-of-envelope capacity estimation for the news feed system design interview: DAU assumptions, storage per post, cache sizing for hot users, and QPS peaks, updated July 2026.
Schema and API design for the news feed system design interview: feed table, friendship graph, REST vs GraphQL, and cursor pagination vs offset, updated July 2026.
Deep-dive on scaling bottlenecks for the news feed system design interview: the celebrity problem, hot partitions, cache stampede, and cross-region replication, updated July 2026.