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Scalability is a multifaceted concept that entails the system's capacity to handle rising load, traffic, or data volumes while maintaining performance, reliability, and functionality. Achieving scalability involves design considerations across architecture, data management, and deployment. Common scaling approaches include horizontal scaling (adding more nodes), vertical scaling (upgrading capabilities of existing nodes), and distributed scaling (organizing load across multiple distinct systems). Geographical scalability adds regional distribution to bring services closer to users. Linear scalability would imply proportional performance gains with added resources, but many real-world systems exhibit diminishing returns due to bottlenecks and coherence costs. Elastic scalability enables rapid up/down adjustment in response to demand. Other important techniques include load balancing, caching, sharding, partitioning, and data replication. Each approach introduces trade-offs in cost, complexity, consistency, and operational risk. Performance metrics such as throughput, latency, saturation, and resource utilization should guide scaling decisions.