CQRS & Event Sourcing
Separate write models from read models and rebuild state from append-only domain events when auditability and scale diverge.
Concept Breakdown
💡 Why It Matters
It enables independent scaling of reads/writes and time-travel debugging, at the cost of operational complexity.
🌐 Real-World Production Usages & Examples
Order history dashboard
Scenario: Writes go to an order aggregate; reads come from denormalized search indexes.
Outcome: Read replicas scale without locking the write path.
✓ When to Use
- •High read/write asymmetry
- •Rich audit requirements
- •Multiple read projections from one write model
✕ When NOT to Use
- •Simple CRUD domains
- •Teams without projection replay tooling
🔑 Core Architecture & Rules
- 1Commands enforce invariants on write model
- 2Projections are rebuildable
- 3Event schema evolution is a first-class problem
⚖️ Architectural Trade-Off Analysis
Complexity
PROFlexible read models
CONEvent versioning and replay pipelines required
⚠️ Failure Modes & Mitigations
Stale projections
Consumers lag behind writers.
Mitigation: Lag metrics, replay jobs, and idempotent projectors.
🛠️ Example Usages
Reviewed practical implementations and concrete code walkthroughs for CQRS & Event Sourcing.
No reviewed practical examples currently published for this concept. Queued for technical review.
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