Part 2: Applying Systems Thinking to Software Development
How to get from A to Z while enjoying the journey
The most complex and resilient systems in our world are living organisms. Even the simplest plant or animal consists of thousands — if not millions — of cells working together in a fluid, coordinated dance. They sense their environment, adapt to change, and maintain internal harmony without central control. This remarkable balance provides an excellent model for systems thinkers.
Coincidentally, I trained as a biologist before stumbling into software design and development. As I learned software engineering on the job, I found myself instinctively applying biological and systems principles to architecture and design. I became a systems thinker by accident — but over time, this mindset served me better than any linear methodology.
Over much of my 50 years as a developer, I’ve built large-scale, distributed software systems. Along the way, I discovered a systems-thinking model that has helped me simplify complexity, foster collaboration, and build software that adapts and endures. Here’s how.
Guiding Principles
Before we design anything, we must deeply understand the problem we’re solving. That leads us to some key principles:
1. Software development is a team effort. Architecture, design, and code should communicate clearly and intuitively with the developers who work with them.
2. Complexity is the enemy. If any individual part isn’t simple, we’re not done yet.
3. Listen to the experts. Developers build software, but the domain experts — the people who live the business every day — better understand what they need it to do. Developers and domain experts should work directly together, not through layers of abstraction.
4. Architecture is plumbing. It defines the flow of information and control. It sets up the pipes, filters, and connectors that keep everything moving.
5. Components do the work. They encapsulate meaningful business functions and operate as message processors — filters in a pipes-and-filters pattern. Small, bindable components are easier to understand, test, and evolve.
6. Connectors link the parts. These pipes bind components and provide communication paths. We recommend using message moderators to manage these interactions dynamically.
7. Messages are the payload. They carry data and instructions between components. Messaging should be flexible — supporting synchronous, asynchronous, and event-driven delivery — and RESTful for clarity and interoperability.
8. Organize for adaptability. Nature thrives through self-organization. Systems should distribute responsibility and avoid central points of failure or control.
9. Design for change. The best way to manage change is through modularity:
- Make parts easy to understand and modify
- Isolate parts from the effects of changes to other parts
- Reduce friction among different teams’ responsibilities
- Simplify deployment of new and updated parts
These principles don’t dictate functionality — they guide structure. They create a shared architectural vocabulary that allows teams to build flexible, maintainable systems — together.
Starting With the People
Most business software systems must integrate with human systems. That means systems thinking begins by modeling the behavior of the people involved — users, stakeholders, and the organizational context within which the system will operate. (Think Conway’s Law.)
Capturing a Shared Understanding
Before we can build anything, we need to model the application domain in a way that both developers and domain experts can understand and agree upon.
Domain-Driven Design (DDD) gives us a practical toolkit for this. It emphasizes modeling business processes through bounded contexts, aggregates, and descriptive objects like entities and value objects.
Finding the Components
In a systems-thinking architecture, these DDD concepts become runtime components:
- Domain: The real-world problem space.
- Bounded Context: A clearly defined part of the domain model. We implement them as components. If one grows too large, we divide it into smaller components.
- Aggregate: A cluster of related entities and value objects, with a root component that enforces consistency rules.
- Entity: A uniquely identifiable object with persistent state. We implement these as database-backed Java records.
- Value Object: An immutable data object without identity, represented in code as a Java record.
We encapsulate relationships in aggregates and enforce data rules inside entities and value objects — so invalid value objects cannot be instantiated or invalid entities persisted.
Now We’ve Got the Functional Requirements
And that’s the hard part — identifying and understanding the core business functions. While implementation choices (deployment, infrastructure, etc.) are still ahead, the foundation is in place.
The Linear-Thinking Solution
Traditionally, software teams now choose an architecture — often Microservices, Event-Driven Architecture (EDA), or a combination of both. They divide the domain into services or event streams and build from there.
But these models have limitations. Each assumes fixed service boundaries and rigid communication patterns. Every interaction must be planned and designed in advance.
Combining architectural patterns adds complexity, and each component must account for its own communication and orchestration logic. The result? Complexity increases faster than functionality.
The Systems-Thinking Solution
Systems thinking — paired with bindable components — offers an alternative.
Instead of building a fixed assembly line of services, we create a network of composable components that can bind dynamically at runtime. Each component processes messages through a standard interface, while message moderators handle routing, orchestration, and adaptability.
What’s a Bindable Component?
A bindable component is a message-processing unit with a common RESTful interface. It can be discovered, bound, and invoked at runtime — adapting dynamically to system conditions.
Where microservices and EDA require static service definitions, bindable components adapt their behavior and connections dynamically — like cells responding to changes in the body.
Communication Models: Rigid vs. Adaptive
Microservices rely on predefined APIs. EDA systems depend on event streams. Both must be designed in advance.
Bindable components, by contrast, use message moderators to dynamically choose between direct calls, sync/async messaging, or event-based delivery — depending upon real-time context.
Execution and Resilience
In traditional systems, services must be deployed, scaled, and monitored externally.
With bindable components, lifecycle management is embedded. Components load on demand, rebalance workloads, and scale automatically — just like biological systems maintain homeostasis: the tendency of an organism to maintain a stable internal state.
Simpler Development and Maintenance
Microservices require custom APIs. EDA needs evolving schemas and brokers.
Bindable components standardize everything behind a common interface. This reduces the effort needed to integrate, evolve, or extend a system.
Why Bindable Components Reflect Systems Thinking
- No more rigid service boundaries. Business logic is modeled in modular units that bind together as needed.
- Dynamic communication. Components use the best interaction method automatically.
- Runtime adaptability. Components are loaded and bound dynamically, not preconfigured.
- Self-healing behavior. The system detects and responds to failures in real time.
- Standardized development. A unified interface replaces custom APIs or broker configurations.
Wrapping Up
Systems thinking and bindable components represent a shift — from rigid, predesigned architecture to a living system of adaptive parts. Traditional models require extensive upfront coordination and rigid boundaries. Systems-thinking architectures, by contrast, are modular, composable, and resilient by design.
By building applications from bindable components, we get a self-organizing, self-healing architecture that grows and adapts organically. Like biological systems, it responds to change, recovers from failure, and evolves to meet new demands — without needing to be re-architected from scratch.
If you’re building complex, distributed systems, it’s time to think like nature — and design like a systems thinker.
Thank you for reading. If you have found this article interesting or thought-provoking, please let us know what you would like to see in Part 3: Systems Thinking: Putting It All Together.
