1. Scaling Strategies & Load Balancing
Scaling is the practice of increasing a system's capacity to handle growing demand. The two fundamental approaches are vertical scaling, which adds more power (CPU, RAM, disk) to a...
Read full chapter →The essential System Design cheat sheet: 7 concise chapters you can read in minutes, distilled from the full deck. When you're ready, drill the flashcards or test yourself under exam conditions.
Scaling is the practice of increasing a system's capacity to handle growing demand. The two fundamental approaches are vertical scaling, which adds more power (CPU, RAM, disk) to a...
Read full chapter →Caching accelerates data access by storing frequently used information closer to where it is needed. Redis (Remote Dictionary Server) is a popular open-source, in-memory key-value...
Read full chapter →As data volumes grow, distributing them across multiple database nodes becomes necessary. Sharding is a horizontal partitioning strategy that splits data across multiple database i...
Read full chapter →Monolithic architectures package all application functionality into a single deployable unit, which is simpler to develop and deploy initially but harder to scale individual compon...
Read full chapter →Rate limiting controls the number of requests a client can make to a service within a given time window, protecting against abuse and ensuring fair resource usage. When limits are...
Read full chapter →Asynchronous messaging decouples services and enables reliable communication at scale. Apache Kafka is a distributed event streaming platform used for building real-time data pipel...
Read full chapter →Distributed systems face inherent trade-offs that shape every design decision. The CAP theorem states that a distributed data store can guarantee at most two of three properties si...
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