designing-distributed-systems

SKILL.md

Design scalable, reliable, and fault-tolerant distributed systems using proven patterns and consistency models.

Distributed systems are the foundation of modern cloud-native applications. Understanding fundamental trade-offs (CAP theorem, PACELC), consistency models, replication patterns, and resilience strategies is essential for building systems that scale globally while maintaining correctness and availability.

CAP Theorem: In a distributed system experiencing a network partition, choose between Consistency (C) or Availability (A). Partition tolerance (P) is mandatory.

When designing distributed systems for scalability, reliability, and consistency. Covers CAP/PACELC theorems, consistency models (strong, eventual, causal), replication patterns (leader-follower, multi-leader, leaderless), partitioning strategies (hash, range, geographic), transaction patterns (saga, event sourcing, CQRS), resilience patterns (circuit breaker, bulkhead), service discovery, and caching strategies for building fault-tolerant distributed architectures. Source: ancoleman/ai-design-components.

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