A deep dive into distributed cache internals: consistent hashing, virtual nodes, replication, client-side sharding, and proxy layers, with a full request-flow walkthrough.
A practical interview walkthrough for designing a distributed cache: Redis cluster vs Memcached, eviction policies, cache-aside vs write-through, and consistency trade-offs.
Tracing a single write and read through a distributed key-value store: write-ahead log, memtable, SSTable flush, and how the read/write paths differ, plus replication data flow.
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.