Consistency models in distributed systems define the guarantees provided for data reads and writes across multiple nodes, directly influencing system behavior under normal operation and during failures. Two prominent models are eventual consistency and strong consistency. Eventual consistency allows temporary…

Introduction Multi-region deployments involve distributing system components—such as databases, caches, and services—across geographically diverse data centers to enhance availability, reduce latency, and comply with regulatory requirements. This approach is essential for global applications that must deliver consistent performance to users…

Introduction Quorum consensus is a fundamental technique in distributed systems for achieving data consistency and fault tolerance by requiring a majority (or quorum) of nodes to agree on read and write operations. It ensures that operations succeed only when a…

Introduction Leader election is a fundamental problem in distributed systems, where nodes must select a single leader to coordinate tasks, ensure consistency, and manage resources, while the remaining nodes act as followers. This process is essential for maintaining system reliability…

Core system design patterns provide foundational blueprints for constructing distributed systems that can handle increasing loads, maintain high availability, and ensure efficient resource utilization. These patterns address common challenges in scalability, such as data distribution, fault tolerance, and performance optimization,…

Change Data Capture (CDC): A Comprehensive Analysis for Tracking and Propagating Database Changes in Real Time Change Data Capture (CDC) is a critical technique in distributed systems for identifying, capturing, and propagating changes (inserts, updates, deletes) in a database to…

Rate limiting is a critical technique in distributed systems to control the rate of incoming requests, ensuring system stability, preventing abuse, and maintaining fair resource allocation. It is essential for high-traffic applications like APIs (e.g., Twitter, PayPal), web services (e.g.,…

Load balancing is a fundamental technique in distributed systems design, aimed at distributing incoming network traffic across multiple backend servers or nodes to optimize resource utilization, minimize response time, maximize throughput, and ensure high availability. In high-traffic applications, such as…