Scalable systems are designed to handle an increasing amount of work by adding resources to the system. Below is a collection of key concepts and methodologies essential for designing and understanding scalable systems.
Load balancing distributes network or application traffic across multiple servers, ensuring that no single server bears too much demand.
Distributed databases spread data across multiple physical locations. They are designed to improve performance, availability, and fault tolerance.
Replication and Sharding :Replication ensures that data is duplicated across multiple nodes, while sharding partitions data to spread it across servers.
Distributed messaging systems facilitate communication between different parts of a scalable system, ensuring high throughput and fault tolerance.
Caching improves system performance by storing instances of data in high-speed storage areas.
Fault tolerance ensures that a system continues to operate even if some components fail.
Effective monitoring and logging provide insights into system performance, security, and user behavior.
Note: This guide is meant as an overview and starting point. Further reading and hands-on practice are encouraged for a deeper understanding of these concepts.