Explore key system design principles from computer architecture to message queues for building robust and scalable software applications.

Message queues enable asynchronous event processing, scalability, and reliability in system design by decoupling event producers from consumers and offering durable message storage.

Object storage simplifies data storage with a flat architecture and immutable objects, ideal for storing large media files and long-term data.

The CAP theorem describes trade-offs in distributed databases: Consistency (C), Availability (A), and Partition Tolerance (P), emphasizing the inevitable compromise between them.

Understanding replication and sharding is crucial for scaling databases. Replication copies data for better availability, while sharding splits data across multiple machines to manage large volumes efficiently.

NoSQL databases, defined by "Not Only SQL," offer diverse data models, scalability, and flexibility, often adhering to the BaSE principle: Basically Available, Soft state, Eventually consistent.

Explore the intricacies of relational database management systems (RDBMS) and SQL, delving into data structures, indexing, constraints, and system design trade-offs for efficient data management.

Consistent hashing optimizes load balancing by ensuring stable request distribution, efficient caching, and scalability in dynamic server environments.

Content Delivery Networks (CDNs) cache data closer to users, reducing load times and enhancing web performance globally.

Understanding proxies and load balancers is essential for efficient networking. Proxies act as intermediaries, hiding clients or servers, while load balancers distribute traffic across multiple servers for scalability and reliability.

Caching enhances software performance by storing frequently accessed data in faster-accessible storage, reducing latency and optimizing throughput across systems.

API design is crucial for defining clear, user-friendly interfaces, focusing on CRUD operations, entities, versioning, and backward compatibility to ensure effective communication between applications.

Understanding API paradigms like REST, GraphQL, and gRPC is crucial for effective application development and data communication.

WebSockets offer bidirectional, real-time communication, addressing HTTP's limitations in latency and efficiency for applications like chat and live feeds.

Understanding application layer protocols like HTTP and RPCs is vital for developers. The client-server model, HTTP's request-response nature, and secure communication via HTTPS are foundational to building robust, interconnected systems.

The Domain Name System (DNS) translates user-friendly domain names into IP addresses, acting as the internet's phone book. It involves multiple steps, from local caching to querying authoritative servers, ensuring seamless web connectivity and user experience.

This comprehensive guide covers networking fundamentals, including IP addresses, TCP, and application layer protocols like HTTP, essential for system design interviews and understanding modern computing.

TCP offers reliability by ensuring data arrives in order and intact, while UDP prioritizes speed, lacking guaranteed delivery and order. Both protocols have distinct trade-offs crucial for different application needs.

Understanding system design involves analyzing data movement, storage, and transformation. Key metrics like availability, throughput, and latency shape the efficiency and reliability of large-scale systems.

Understanding high-level application architecture is crucial for developers. From servers and storage to scaling and monitoring, this guide demystifies key components and considerations for building robust production apps.

Understanding computer architecture is crucial for designing large-scale systems. Components like disk storage, RAM, CPU, and cache interact to execute code, with each having its unique role and speed.