Strategic DDD: The Balancing Act of Shared Kernel

Welcome to our exploration of Domain-Driven Design's strategic patterns! In this post, we'll dive deep into the Shared Kernel pattern, where bounded contexts share critical common elements.

Understanding Shared Kernel

Think of a Shared Kernel like a common foundation that multiple buildings rely upon. It represents core models, code, or data that multiple bounded contexts share and must jointly maintain. While sharing can reduce duplication, it requires careful coordination to avoid becoming a source of coupling and complexity.

Detailed Analysis

The Shared Kernel pattern involves multiple contexts sharing a common core of models, code, or data. Unlike other patterns, this creates an explicit dependency between teams through shared components. These components must be stable, well-defined, and carefully managed as changes affect all participating contexts simultaneously. This is nowadays handled by a platform team (but we will discuss this some other time).

Architectural Dimensions:

• Coordination Model: Typically requires orchestration for changes to shared components, with clear governance processes and coordination across all participating teams.

• Communication Model: Usually implements synchronous communication for shared resource access, with careful transaction management and consistency controls.

• Consistency Model: Almost always requires atomic consistency for the shared kernel to maintain data integrity across all consuming contexts.

Perfect for:

• Common domain models

• Shared utilities

• Cross-cutting concerns

• Core business rules

• Common validation logic

• Shared security models

• Standard data structures

• Base domain types

NFR Alignment:

• Maintainability: ⭐⭐

• Reliability: ⭐⭐⭐

• Performance: ⭐⭐⭐⭐

• Security: ⭐⭐⭐⭐

Real-world Examples:

1. Common security and authentication libraries shared across applications

2. Core domain models shared between order processing and inventory systems

3. Shared validation rules across multiple financial applications

4. Common customer data model used by multiple business units

Tradeoffs & Challenges

Architectural Challenges:

• High risk of tight coupling across contexts

• Complex deployment coordination requirements

• Versioning challenges with shared components

• Performance bottlenecks in shared resources

• Testing complexity due to shared dependencies

• Schema evolution difficulties

• Challenging error handling scenarios

• Complex transaction management

• Difficult to maintain backward compatibility

• Risk of shared resource contention

Organisational Impacts:

• High coordination overhead between teams

• Risk of "tragedy of the commons"

• Slow evolution due to required consensus

• Complex governance requirements

• Reduced team autonomy

• Challenging priority alignment

• Shared responsibility for maintenance

• Difficult decision-making processes

• Training and documentation overhead

• Complex incident response coordination

Best Practices

1. Change Management

   • Clear governance process

   • Version control strategy

   • Breaking change policies

   • Migration guidelines

   • Compatibility testing

2. Documentation

   • Comprehensive API docs

   • Usage guidelines

   • Change logs

   • Architecture decision records

   • Known limitations

3. Quality Control

   • Shared test suites

   • Performance benchmarks

   • Security reviews

   • Code quality standards

   • Automated checks

4. Team Coordination

   • Regular sync meetings

   • Change review boards

   • Clear ownership matrix

   • Escalation procedures

   • Joint planning sessions

Architect's Alert 🚨

While sharing code or data can reduce duplication, the coordination overhead of a Shared Kernel can outweigh its benefits. Consider carefully whether the shared elements are stable enough and truly common enough to justify the coupling.

Implementation Strategies

1. Kernel Design

   • Minimize scope

   • Clear boundaries

   • Stable interfaces

   • Version strategy

   • Change detection

2. Integration Approaches

   • Package management

   • Dependency controls

   • Update mechanisms

   • Compatibility layers

   • Migration tools

3. Operational Excellence

   • Performance monitoring

   • Usage tracking

   • Error tracking

   • Health checks

   • Deployment coordination

Conclusion

The Shared Kernel pattern can provide significant benefits through reuse and standardisation, but requires careful management to avoid becoming a burden. Success lies in finding the right balance between sharing and independence.

How do you manage the evolution of shared components in your architecture while maintaining team autonomy?