This article explains how transactions, consistency, and consensus interrelate in distributed systems, reviews replication models, details ACID properties, internal consistency models, consensus algorithms, and Kafka’s configuration and transaction support, and highlights verification tools like TLA+ and Jepsen for ensuring correctness.
The article revisits the CAP theorem, explains linearizable consistency and strict availability, demonstrates with concrete data‑center examples why the CP/AP split is often misleading, and argues that latency concerns and broader failure modes make the binary classification of distributed systems impractical.
This article explains the fundamentals of Jepsen testing, compares it with TLA+, describes its architecture and workflow, illustrates how to apply Jepsen for linearizability verification of distributed systems such as locks, and offers practical guidance on integrating Jepsen or building custom testing frameworks.
This article explains linearizability in distributed systems, compares Raft read strategies, and describes how CB‑SQL uses range leases and node leases to achieve strong consistency while reducing overhead, illustrating the trade‑offs and evolutionary design choices behind its consensus mechanisms.
This article explains the fundamental reasons for building distributed systems, examines the inevitable side‑effects—especially data consistency challenges—analyzes the root causes of inconsistency, and walks through various consistency models from eventual to linearizability with clear examples and illustrations.
The article explains how distributed systems achieve linearizability by using logical clocks, TrueTime, Hybrid Logical Clocks, and Timestamp Oracle mechanisms to establish a global ordering of events despite clock skew and network delays.
This article explains the concept of linearizability, contrasts it with serializability, and describes how Google Spanner uses the TrueTime API and commit‑wait mechanisms to provide external consistency and reliable snapshot reads in a globally distributed database system.
