Walk the stages in order for Module Boundaries Should Follow Change: start from the contract, trace the representation through the operation, then confirm the boundary. Worked case: If billing and email share a database table but change for different reasons, each may be better represented by its own module even when both run in one process. For a worked explanation, continue to the topic article and execution trace.
Stage-by-stage execution walkthrough
This request flow decomposes Module Boundaries Should Follow Change into 5 sequential stages so you can trace where latency accumulates, which state transitions are irreversible, and where production failure modes occur.
Stage 1: Contract
A module groups decisions that are likely to change together and hides details other modules do not need. A useful boundary reduces the number of places that must change for one product decision. The public interface should express stable intent rather than expose internal storage or control flow. During this transition, the runtime enforces strict state invariants before handing control to the next stage: inputs are validated at the boundary, state mutations are ordered deterministically, and latency/resource costs are bounded so downstream consumers never observe a torn or partially initialized state.
Stage 2: Representation
If billing and email share a database table but change for different reasons, each may be better represented by its own module even when both run in one process. A narrow interface can let the implementation change from a local adapter to a remote service without rewriting every caller. During this transition, the runtime enforces strict state invariants before handing control to the next stage: inputs are validated at the boundary, state mutations are ordered deterministically, and latency/resource costs are bounded so downstream consumers never observe a torn or partially initialized state.
Stage 3: Operation
Choose a boundary for a feature that sends a receipt after a purchase. Decide which module owns payment state, receipt formatting, and delivery retries, and explain how dependencies flow. During this transition, the runtime enforces strict state invariants before handing control to the next stage: inputs are validated at the boundary, state mutations are ordered deterministically, and latency/resource costs are bounded so downstream consumers never observe a torn or partially initialized state.
Stage 4: Boundary
More modules do not automatically mean less complexity: excessive fragmentation adds indirection and coordination cost. A boundary drawn around technical layers may still couple unrelated product rules. Strong boundaries usually emerge from repeated change patterns and explicit ownership. During this transition, the runtime enforces strict state invariants before handing control to the next stage: inputs are validated at the boundary, state mutations are ordered deterministically, and latency/resource costs are bounded so downstream consumers never observe a torn or partially initialized state.
Stage 5: Result
Choose a boundary for a feature that sends a receipt after a purchase. Decide which module owns payment state, receipt formatting, and delivery retries, and explain how dependencies flow. During this transition, the runtime enforces strict state invariants before handing control to the next stage: inputs are validated at the boundary, state mutations are ordered deterministically, and latency/resource costs are bounded so downstream consumers never observe a torn or partially initialized state.
Production invariants and failure modes
Done when the worked check holds: Choose a boundary for a feature that sends a receipt after a purchase. When debugging or capacity-planning this flow in production, instrument each stage boundary separately (measuring both p50 median and p99.9 tail latency), verify what happens when an intermediate stage times out or drops packets, and ensure retry or fallback paths preserve end-to-end idempotency.