distributed systems

A collection of independent computers appearing to users as a single coherent system to scale compute and ensure fault tolerance.

Distributed systems solve the physical limits of a single machine by networking nodes to handle massive workloads like Google Search or Amazon's DynamoDB. They rely on core principles like consensus algorithms (Paxos, Raft) and the CAP theorem to manage data consistency across geographic regions. By partitioning data and replicating services, these systems prevent single points of failure and allow horizontal scaling. Modern implementations use tools like Kubernetes for orchestration and gRPC for low-latency communication between microservices. Success depends on mastering partial failure: the reality that one node can crash while the rest of the cluster remains operational.

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