This article explains distributed transactions, the reasons they arise, the CAP and BASE theories that guide consistency trade‑offs, and outlines strong, eventual, and weak consistency solutions along with popular frameworks for implementing them in modern distributed systems.
This article explains the CAP theorem, details how Redis implements master‑slave replication—including its asynchronous nature, configuration methods, three‑phase workflow, heartbeat mechanism, and common operational issues—providing practical guidance for building highly available Redis deployments.
This article explains the fundamentals of Redis master‑slave replication, covering CAP theory, the replication workflow, configuration methods, heartbeat mechanisms, and typical problems with practical solutions to ensure high availability and data consistency.
This article explains the evolution of backend service architectures, introduces the CAP and BASE theories, and provides detailed walkthroughs of the Paxos and Raft consensus algorithms, covering their roles, constraints, protocol steps, and practical considerations for building reliable distributed systems.
