Managing Shared Libraries in Hexagonal Architecture and Domain-Driven
Published: 2024-02-26 08:10:15

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Designing a microservices architecture with both hexagonal architecture and Domain-Driven Design (DDD) brings a wealth of benefits: modularity, testability, and a strong focus on the core business domain. However, as your system grows, the need for shared code across microservices presents a challenge. How do you effectively manage shared libraries while upholding the principles of encapsulation and independent evolution?

**Types of Shared Code**

Before delving into strategies, let's categorize the types of code that might be shared:

1. **Core Domain Entities:** Fundamental business concepts (e.g., Customer, Order). Sharing these risks tight coupling.
2. **Value Objects:** Immutable data structures representing concepts like addresses, currency, etc. Less risky to share.
3. **Technical Utilities:** General-purpose libraries for logging, serialization, date manipulation, etc. Ideal for sharing.

**The Encapsulation Conundrum**

The core tenet of DDD is modeling bounded contexts, each with its own ubiquitous language and understanding of domain entities. Hexagonal architecture emphasizes isolating this domain logic behind ports, reducing dependencies. Sharing domain models directly undermines these principles.

Consider two microservices, "Order Management" and "Customer Relationship Management," both needing a `Customer` concept. If they share a `Customer.java` class, changes in one service could break the other without careful coordination.

**Best Practices**

1. **Minimize Shared Domain Concepts:** The most effective approach is to strive for minimal sharing when it comes to the domain model. Duplication might feel inefficient, but it preserves encapsulation and autonomy.
2. **Semantic Versioning:** Rigorously apply semantic versioning (Major.Minor.Patch) to any shared libraries. Breaking changes have system-wide consequences.
3. **Classification of Shared Code:** Differentiate domain-specific shared code from generic utilities, applying differing levels of change management.
4. **Explicit Contracts:** Treat shared libraries like external APIs. Establish clear contracts defining their interfaces and behaviors.

**Strategies**

* **Shared Kernel (DDD):** In strict DDD, a bounded context can share a limited portion of its domain model as a "Shared Kernel." Requires strong coordination and should only be used for incredibly stable concepts.
* **Published Language (DDD):** Emphasize a shared vocabulary for key concepts, even if the internal modeling differs slightly between microservices.
* **Canonical Model:** Define a shared representation of core concepts for communication. Microservices translate their internal models to/from this canonical format.

**Technical Considerations**

* **Packaging:** Separate modules or dedicated libraries help manage different types of shared code.
* **Dependency Injection:** Use Spring's capabilities to inject the correct shared dependencies at runtime.

**Tradeoffs**

* **Encapsulation vs. Efficiency:** The best solution depends on your project's complexity, team structure, and the nature of shared concepts.

**Example 1: The Evolving Domain Concept**

Consider an e-commerce system with "Order Management" and "Shipping" microservices. Initially, an `Order` has simple attributes like `status` and `items`. Later, the shipping costs become more complex, requiring detailed `ShippingAddress` information.

* **Option 1: Versioning the Shared Library** – Create a new version of the shared `Order` entity with the `ShippingAddress`. This might necessitate running multiple versions of services in production during a transition period.
* **Option 2: Canonical Model** – Define a separate `ShippingOrder` model for communication. The Order Management service translates its internal `Order` to the `ShippingOrder` format before sending it to the Shipping service.

**Example 2: Shared Kernel Mishap**

Two teams agree on a Shared Kernel within a bounded context, including a `Product` entity. However, one team needs to add product reviews, while the other does not.

* **Risk:** The change to the Shared Kernel affects the team that doesn't need reviews.
* **Mitigation:**
    * **Break the Shared Kernel:** Painful, but may be necessary for long-term autonomy.
    * **Anti-Corruption Layer (ACL):** One team introduces an ACL that translates the shared `Product` into an internal model with additional features.

**Example 3: Technical Utility Gone Wild**

Teams share a `DateUtils` utility library. Gradually, more specialized domain-specific logic like "calculating subscription renewal dates" creeps into this shared utility.

* **Solution:** Separate domain-specific calculations from the generic `DateUtils` library. Place the domain-specific logic into the corresponding microservice's domain layer.

**Advanced Strategies**

* **Consumer-Driven Contracts:** Instead of focusing solely on the provider of a shared entity, use consumer-driven contracts where services outline their expectations for shared data. This can help identify potential conflicts early.
* **Event-Driven Communication:** In some cases, using events to communicate changes in shared state can reduce tight coupling. For example, instead of directly sharing a `Customer` object, the Customer Management service might publish a `CustomerUpdated` event.

**Important Considerations:**

* **Team Communication:** Strong collaboration between teams managing bounded contexts is crucial when shared libraries are involved.
* **Governance:** Establish a lightweight governance process to review proposals for shared libraries and changes to existing ones.
* **Documentation:** Thoroughly document any shared concepts, their usage, and version compatibility.

**It's crucial to remember that there is no one-size-fits-all solution.** The best approach will depend on your specific system's complexity, the maturity of your teams, and the nature of the shared concepts.