Distributed

Distributed refers to systems or processes that are spread across multiple locations or components, communicating to achieve a common objective. In computing, a distributed system consists of multiple independent computers that appear to users as a single coherent system. The primary goals are scalability, fault tolerance, high availability, and the ability to share resources or data efficiently.

Key concepts in distributed systems include concurrency and coordination across components, lack of a global clock, and the presence of partial failures. Components communicate via message passing, and system state may be replicated or partitioned across nodes. Data distribution often relies on replication for redundancy and partitioning (sharding) to scale storage and processing. Consensus protocols are used to agree on shared state in the presence of failures. The CAP theorem articulates trade-offs among consistency, availability, and partition tolerance, influencing design choices in distributed data stores and services.

Architectural styles frequently encountered in distributed contexts include client-server, peer-to-peer, and microservices architectures. Distributed data stores may be implemented as distributed databases or file systems, while processing frameworks enable parallel computation across nodes. Modern environments commonly employ orchestration and containerization tools to manage distributed services, and may also leverage edge computing to bring computation closer to data sources.

Common challenges include maintaining safety and liveness in the face of network delays and node failures, choosing appropriate consistency guarantees, achieving reliable coordination, and addressing security concerns. Practical systems balance these considerations to deliver scalable, resilient, and maintainable services across dispersed infrastructure.