The Software Architecture landscape has often been dominated by two major choices: monolithic applications for simplicity vs microservices for scalability. This has forced teams to make major architectural calls, often sometimes forcing compromises that don’t fully address their needs. However, there may be another path that is gaining traction: Self-Contained Systems (SCS).
Self-Contained Systems represent an architectural pattern that combines the best aspects of both monoliths and microservices while addressing their key limitations. Unlike a typical microservices approach which focuses primarily on decomposing into multiple backend services, SCS embraces a full-stack philosophy where each system/team owns its complete user experience from start to finish.
This post will try to examine why SCS might be the sweet spot in your architecture, providing detailed comparison, practical frameworks and real-world insights to guide your architectural decisions.
Understanding Self-Contained Systems
Defining Self-Contained Systems
A Self-Contained System is an autonomous, full-stack application that:
Owns its complete stack: From the database schemas to the user interfaces
Implements a specific business requirement: Focused on a bounded context
Operates Independently: Can function without other systems
Communicates asynchronously: Primarily through events and data replication
Maintains its own deployment lifecycle: Independent versioning and releases
Core Principles of SCS
Autonomy: Each SCS can be developed, tested, deployed and operated independently by a dedicated team. This autonomy extends beyond just the backend services to include the complete user experience.
Business Alignment: Systems are organized around business capabilities rather than technical layers. For example, an e-commerce SCS might own everything related to Product catalog - the DB Schemas, business logic, APIs and web pages for browsing and searching through products.
Full-Stack Ownership: Unlike microservices that often share frontend applications, each SCS owns its portion of the user interface. This eliminates coordination overhead and enables true end-to-end ownership.
Loose Coupling: SCS instances communicate primarily through async mechanisms like events, message queues or data replication. Synchronous calls are minimized as much as possible and carefully managed.
Technology diversity: Teams can choose the most appropriate tech stack for their specific domain without being constrained by org wide standards.
SCS vs Traditional Microservices
While microservices focus on decomposing the backend into smaller services while often sharing the frontend, SCS takes a more holistic approach, decomposing the entire application stack - including UI - into independent systems.
This fundamental difference has profound implications for team structure, development process, and operational complexity.
The Monolith: Strengths and Limitations
Monolith Strengths
Simplicity: Monoliths offer simpler development, testing and deployment processes. Developers work within a single codebase with familiar patterns and tools.
Performance: In-process communication eliminates network latency. Database transactions can maintain ACID properties across the entire application.
Debugging and Monitoring: Centralized logging, monitoring, and debugging provide clear visibility into an application’s behaviour.
Consistency: Shared Libraries, coding standards and architectural patterns ensure consistency throughout the application.
Initial Development Speed: Small teams can move quickly without the overhead of distributed system complexity.
Monolithic Limitations
Scalability constraints: The entire app must be scaled as a unit, which may lead to resource wasting and scaling bottlenecks if not utilized properly.
Technology Lock-In: Since the entire application becomes bound to a single technology stack, it may limit innovation opportunities.
Team Coordination Overhead: As teams grow, coordination becomes increasingly complex.
Deployment Risk: Changes to any part of the application requires deploying the entire monolith, increasing the blast radius for any potential failures.
Limited Fault Isolation: A failure in any single component may bring down the entire application.
Microservices: Promise and Pitfalls
Microservices Strengths
Independent Scalability: Services can be scaled independently based on their specific load patterns and resource requirements.
Technology Diversity: Teams can choose the most appropriate tech stack for each service’s requirements.
Fault Isolation: Failure in one service doesn’t necessarily cascade to others, thereby improving overall system resilience.
Team Autonomy: Small, focused teams can own and operate individual services with minimal coordination.
CI/CD: Services can be deployed independently, enabling faster release cycles and reduced deployment risk.
Microservices Pitfalls
Operational Complexity: Managing dozens or hundreds of services requires sophisticated tooling for deployment, monitoring, logging and debugging. This may end up being difficult to understand, maintain and coordinate.
Network Complexity: Service-to-Service communication introduces latency, failure modes and the need for specific design patterns for microservices like circuit breakers and retry/resubmit mechanisms.
Frontend Coordination: While backend systems are decomposed, frontends often end up remaining monolithic, creating coordination bottlenecks and deployment dependencies.
Testing Complexity: Integration Testing across Multiple Services is significantly more complex than testing a single application.
Distributed System Fallacies: Teams often underestimate the challenges of distributed systems leading to issues with network reliability, latency and security.
Detailed Architectural Comparison
Development Complexity
Monolith: Low complexity for small teams and simple applications. Complexity increases dramatically as the codebase grows.
Microservices: High Complexity from day 1. Requires expertise in distributed systems, container orchestration and service discovery.
SCS: Moderate Complexity. More complex than Monoliths but significantly less complex than fine-grained microservices. Complexity remains manageable as the system grows.
Operational Overhead
Monolith: Minimal operational overhead. Single deployment, monitoring and logging.
Microservices: High operational overhead. Requires sophisticated tooling for container orchestration, service mesh, distributed tracing and centralized logging.
SCS: Moderate operational Overhead. Fewer systems to manage than microservices, while also providing better isolation than monoliths.
Technology Flexibility
Monolith: Limited to a single stack across the entire application
Microservices: Maximum technology flexibility, but can lead to operational complexity and knowledge fragmentation.
SCS: Good technology flexibility with natural boundaries.
Scalability Patterns
Monolith: Scales the entire application as a unit. Simple, but potentially wasteful blocking up resources it doesn’t need.
Microservices: Fine grained scalability for individual services. Highly Optimized, but complex.
SCS: Coarse grained scalability for business capabilities. Good balance between simplicity and optimization.
Decision Matrix to pick between the styles
| Factor | Monolith | Microservices | SCS |
|---|---|---|---|
| Domain Complexity | Simple | Complex | Moderate |
| Scalability Requirements | Low-Medium | Extremely High | Medium-High |
| Time to Market | Fast | Slow | Medium |
| Technology Diversity | None | Maximum | High |
| Development Speed | Initially Fast | Slow | Medium |
| Testing/Debugging Complexity | Low | High | Medium |
| Deployment Complexity | Low | High | Medium |
| Fault Isolation | Poor | Excellent | Good |
| Learning Curve | Low | High | Medium |
Real World Examples
Zalando
Zalando re-architected its e-commerce platform around autonomous teams and micro-frontends, stitching UI fragments together via their Project Mosaic framework. Each feature team deploys independent UI blocks backed by dedicated services and data stores, accelerating experiments and reducing cross-team impacts.
Breuninger
Breuninger is a leading German fashion and lifestyle retailer with a strong online presence. The company needed to optimize its e-commerce platform to respond more quickly to market demands and customer expectations. Hence they adopted SCS architecture, which allowed independent and rapid development and deployment of new features tailored to the customer journey. This approach improved time-to-market for new features, increased platform stability, and enhanced customer satisfaction through a more optimized shopping experience.
Kühne+Nagel
Kühne+Nagel is a global logistics company. The company needed to break down its monolithic software to improve agility and maintainability. Kühne+Nagel adopted SCS (within the context of logistics), comparing it to microservices and choosing SCS for its clearer boundaries and team ownership. The transition enabled more independent team operations and simplified the management of complex logistics workflows. SCS offered a practical alternative to both monoliths and microservices for large, distributed organizations.
A Personal Anecdote
In my previous role, I had the opportunity to work closely with a team that developed a comprehensive PaaS offering from scratch - a product that exemplified the SCS principles in action. The platform consisted of three very distinct Self-Contained Systems, each addressing a specific business capability. All three systems had their own tech stack for frontend (2x React, 1x Angular), backend (2x Go, 1x Python) and database (2x MongoDB, 1x DB2) integrated with a central authentication API (Go+MongoDB) that handled user login and session management. However, each of these SCS independently managed authorization within their respective areas using the principles of RBAC.
Conclusion
Self-Contained Systems offer a compelling alternative to the traditional monolith versus microservices debate. By focusing on business-aligned, full-stack ownership, SCS provides many of the benefits of microservices while avoiding much of their complexity.
The key insights for architectural decision-making are:
Start with Team Structure: Organize your architecture around how you want to organize your teams. SCS works best when teams can own complete business capabilities.
Embrace Business Alignment: Technical boundaries should reflect business boundaries. This makes systems easier to understand, maintain, and evolve.
Balance Complexity: SCS provides a sweet spot between monolithic simplicity and microservices flexibility. Choose the approach that matches your organization’s current capabilities and growth trajectory.
Focus on Autonomy: The primary benefit of SCS is team autonomy. Optimize for reducing coordination overhead while maintaining necessary integration points.
Evolve Gradually: Architecture is not a destination but a journey. Start with what works for your current situation and evolve as your organization and requirements change.
The future of software architecture likely includes all three approaches - monoliths for simple applications, fine-grained microservices for high-scale optimization, and Self-Contained Systems for the vast middle ground where most applications live. Understanding when and how to apply each approach is the key to successful software architecture in the modern era.
As we continue to learn from industry experiences and evolve our understanding of distributed systems, Self-Contained Systems represent a mature approach to organizing software that aligns technical and business concerns while maintaining manageable complexity. For many organizations, SCS may indeed be the architectural pattern they’ve been searching for.