Understanding Consistency in Distributed Systems

Building reliable software today means working with networks of computers that must agree on the state of your data. This course demystifies how data consistency works across distributed nodes, helping you make smart architectural decisions. You will learn to navigate the classic trade-offs between speed, availability, and correctness. What you'll learn: - Understand foundational consistency models, including strong, eventual, sequential, and causal consistency. - Analyze the CAP and PACELC theorems to make informed architectural decisions under network partition scenarios. - Explore how modern consensus protocols like Raft ensure agreement across distributed nodes. - Discover Conflict-Free Replicated Data Types (CRDTs) and their role in offline-first and collaborative application design. - Evaluate replication strategies and how modern databases manage write conflicts. This course begins with essential terminology, defining nodes, networks, and the core challenge of distributed state. You will then progress through structured text lessons and conceptual scenarios that illustrate how these theories apply to modern cloud databases and microservices. This course is designed for software developers, system architects, and tech enthusiasts who want a solid conceptual foundation in distributed systems. No prior experience with distributed databases is required. Start reading today to build more resilient and scalable systems.