Middleware

Introduction Modern cloud‑native applications rely heavily on low‑latency data access. Distributed caches—such as Redis clusters, Memcached farms, or custom in‑memory stores—are the workhorses that keep hot data close to the compute layer. However, as the number of cache nodes grows, consistency becomes a first‑class challenge. Traditional approaches (eventual consistency, read‑through/write‑through proxies, or simple master‑slave replication) either sacrifice freshness or incur high latency during failover. Raft, a well‑understood consensus algorithm, offers a middle ground: strong consistency with predictable leader election and log replication semantics. ...