Domain-Driven Design in Practice: From Theory to Code

When DDD Makes Sense

Domain-Driven Design is not for every project. It is for complex domains where the business logic is the hard part, not the technical implementation.

Signs DDD will help:

Domain experts and developers talk past each other

Business rules are scattered across the codebase

The same concept means different things in different parts of the system

Changes to business logic require touching many files

Signs DDD is overkill:

Simple CRUD applications

Technical complexity exceeds domain complexity

No access to domain experts

Ubiquitous Language

The foundation of DDD is shared language. Domain experts and developers use the same terms, and those terms appear directly in the code.

Not OrderProcessor.execute(orderData) - that is technical language. Instead: Order.place(), Order.ship(), Order.cancel(). The code reads like the business speaks.

Building ubiquitous language requires ongoing collaboration. Event storming workshops, domain expert pairing, glossary maintenance. The language evolves as understanding deepens.

Bounded Contexts

A bounded context is a boundary within which a domain model is consistent. The same word can mean different things in different contexts - and that is okay.

"Customer" in Sales is a lead to nurture. "Customer" in Billing is an account to charge. "Customer" in Support is a person with problems. Each context has its own Customer model, optimized for its needs.

Context mapping defines relationships between contexts: shared kernel (shared model), customer-supplier (one depends on another), conformist (one adopts another's model), anti-corruption layer (translation between models).

Aggregates: Consistency Boundaries

An aggregate is a cluster of objects treated as a unit for data changes. The aggregate root is the only entry point - external code cannot directly modify internal objects.

Aggregates enforce business invariants. An Order aggregate ensures line items do not exceed limits, totals are calculated correctly, and state transitions are valid.

Design aggregates small. Large aggregates create contention and complicate transactions. Reference other aggregates by ID, not by object reference.

Domain Events

Domain events capture things that happened that domain experts care about. OrderPlaced, PaymentReceived, ShipmentDispatched.

Events enable loose coupling. The Order context publishes OrderPlaced. The Shipping context subscribes and creates a shipment. Neither knows about the other's internal model.

Events also provide an audit trail and enable event sourcing if you choose that path.

Tactical Patterns

Entities: Objects with identity that persists over time. An Order remains the same Order even as its state changes.

Value Objects: Immutable objects defined by their attributes. Money, Address, DateRange. Two Money objects with the same amount and currency are equal.

Repositories: Abstractions for aggregate persistence. The domain layer does not know about databases.

Domain Services: Operations that do not belong to any single entity. TransferMoney spans two accounts.

Best Practices

Start with ubiquitous language: Words matter, align them early

Find bounded contexts: Do not force one model everywhere

Keep aggregates small: Consistency boundaries, not convenience boundaries

Use domain events: Decouple contexts through events

Collaborate continuously: DDD is not a one-time design phase

Refactor toward deeper insight: Models improve as understanding grows