nw-sd-patterns-advanced

# Advanced Distributed Patterns ## Event Sourcing **Problem**: need audit trail, state reconstruction, temporal queries. **Core idea**: store every state change as immutable event, not current state. ``` Events: [WalletCreated: balance=0] [Deposited: +100] [Transferred: -30] [Deposited: +50] Current state: 0 + 100 - 30 + 50 = 120 ``` **Benefits**: complete audit trail | temporal queries ("balance on Jan 15?") | rebuild state from scratch | debug by replay | event-driven architecture **Challenges**: computing state requires replaying all events -- use snapshots | schema evolution (events immutable) | store grows indefinitely -- compaction/archiving | eventual consistency for read models **Snapshots**: periodically save computed state | current state = latest snapshot + events after it | trade-off: recovery speed vs storage **Used in**: payment systems, banking, trading platforms, audit-critical systems ## CQRS (Command Query Responsibility Segregation) **Problem**: read and write models have different optimization needs. **Architecture**: Commands -> Write Model (normalized, consistency) -> events/CDC -> Read Model (denormalized, query-optimized) <- Queries **When**: very different read/write patterns | read model needs heavy denormalization | different scaling for reads vs writes | paired with Event Sourcing **Trade-offs**: eventual consistency between models | increased complexity (two models) | sync lag ## Saga Pattern **Problem**: distributed transactions ac...