INTRODUCTION
As software engineers familiar with Hexagonal Architecture, Domain-Driven Design, and Clean Architecture, you have already internalized powerful principles for building maintainable systems. You understand the value of separating domain logic from infrastructure concerns. You appreciate the importance of clear boundaries and dependency management. You recognize that architecture is not just about organizing code, but about managing complexity over time.
Yet despite these powerful tools, you have likely encountered situations where traditional architectural patterns feel inadequate. Perhaps you have worked on an embedded system where Clean Architecture's concentric circles seemed to fight against the need for direct hardware access. Or maybe you have watched an enterprise system's carefully designed hexagonal boundaries erode as circular dependencies crept in between bounded contexts. You might have struggled to integrate modern technologies like machine learning models or big data pipelines into architectures designed for simpler times.
Capability-Centric Architecture addresses these challenges by extending and synthesizing concepts from the patterns you already know, while introducing new mechanisms specifically designed to handle the full spectrum from embedded systems to cloud-native enterprise platforms. This tutorial will guide you through CCA step by step, building your understanding from foundational concepts to practical implementation.
THE FUNDAMENTAL TENSION IN SOFTWARE ARCHITECTURE
Before diving into Capability-Centric Architecture, we must understand the problem it solves. Software systems exist on a spectrum. At one end lie embedded systems running on microcontrollers with kilobytes of RAM, reading sensors through memory-mapped registers, and controlling actuators with microsecond timing constraints. At the other end lie enterprise systems running across cloud infrastructure, processing millions of transactions, integrating with dozens of external services, and evolving rapidly to meet changing business needs.
Traditional architectural patterns force us to choose. Layered architectures work well for business applications but become awkward when hardware access does not fit neatly into a data access layer. Hexagonal Architecture elegantly handles external service integration but obscures the fundamental difference between a replaceable database adapter and a hardware timer that defines the system's real-time capabilities. Clean Architecture's dependency rule works beautifully for business logic but creates friction when the "infrastructure" is actually the foundation upon which capabilities are built.
Let us examine these problems concretely. Consider a typical layered architecture applied to an industrial control system. The presentation layer displays sensor values, the business logic layer processes control algorithms, the data access layer manages persistence, and somewhere we need hardware access to read sensors and control actuators. Where does the hardware access layer fit? Place it below the data access layer and we create an awkward dependency structure. Make it a separate concern and we violate the layering principle. Most critically, the rigid layering makes it nearly impossible to optimize critical paths. When a sensor interrupt occurs, the signal must traverse multiple layers before reaching the control algorithm, introducing unacceptable latency.
Hexagonal Architecture attempts to solve this through ports and adapters. The core domain logic sits in the center, and adapters connect to external systems through defined ports. This works well for enterprise systems where database adapters and API adapters make sense. For embedded systems, however, treating a hardware timer as just another adapter obscures the fundamental difference between a replaceable external service and a hardware component that defines the system's real-time capabilities.
Consider this typical hexagonal approach for embedded systems:
// Port definition
public interface SensorPort {
SensorReading read();
}
// Domain logic
public class TemperatureController {
private final SensorPort sensor;
public TemperatureController(SensorPort sensor) {
this.sensor = sensor;
}
public void regulate() {
SensorReading reading = sensor.read();
// Control logic here
}
}
// Hardware adapter
public class HardwareSensorAdapter implements SensorPort {
private static final int SENSOR_REGISTER = 0x40001000;
public SensorReading read() {
// Direct memory access
int rawValue = readRegister(SENSOR_REGISTER);
return new SensorReading(convertToTemperature(rawValue));
}
private native int readRegister(int address);
}
This code looks clean at first glance, but it hides critical problems. The abstraction prevents the controller from accessing sensor metadata available in adjacent hardware registers. It forces all sensor access through a method call, preventing the use of DMA or interrupt-driven reading. It makes testing harder because we cannot easily inject timing behavior. Most critically, it treats hardware as just another replaceable component, even though hardware capabilities fundamentally shape what the system can do.
Clean Architecture faces similar problems. Its concentric circles with inward- pointing dependencies work wonderfully for business applications. The entities layer contains business rules, the use cases layer contains application- specific rules, and outer layers handle UI and infrastructure. But embedded systems do not fit this model. Hardware is not infrastructure that can be abstracted away. It is the foundation upon which capabilities are built.
Enterprise systems face different but equally challenging problems. As systems grow, bounded contexts multiply, and dependencies between them become tangled. Teams try to enforce layering or hexagonal boundaries, but practical constraints create backdoors and shortcuts. A customer service needs data from an inventory service, which needs prices from a catalog service, which needs customer segments from the customer service. The circular dependency is obvious, but the business need is real.
Modern technologies exacerbate these problems. AI models are not simple components that fit into a layer or an adapter. They have their own infrastructure needs, training pipelines, versioning requirements, and inference characteristics. Big data processing does not fit traditional request-response patterns. Infrastructure as Code blurs the line between application architecture and deployment architecture. Kubernetes and containerization change how we think about deployment units and scaling boundaries.
CORE CONCEPTS OF CAPABILITY-CENTRIC ARCHITECTURE
Capability-Centric Architecture introduces several interconnected concepts that work together to address these challenges. At the foundation lies the recognition that systems, whether embedded or enterprise, are built from capabilities. A capability is a cohesive set of functionality that delivers value, either to users or to other capabilities.
This sounds similar to bounded contexts from Domain-Driven Design, and indeed there are significant overlaps. However, capabilities extend the concept in important ways. A bounded context focuses on domain modeling and linguistic boundaries. A capability encompasses the domain model but also includes the technical mechanisms needed to deliver that capability, the quality attributes it must satisfy, and the evolution strategy for that capability.
The Capability Nucleus
Every capability is structured as a Capability Nucleus. The nucleus contains three concentric regions, but unlike the circles of Clean Architecture, these regions have different permeability rules and serve different purposes.
The innermost region is the Essence. This contains the pure domain logic or algorithmic core that defines what the capability does. For a temperature control capability, the essence contains the control algorithm. For a payment processing capability, the essence contains the business rules for validating and executing payments. The essence has no dependencies on anything outside itself, except for capability contracts, which we will explore shortly.
The middle region is the Realization. This contains the necessary mechanisms to make the essence work in the real world. For embedded systems, this includes hardware access, interrupt handlers, and DMA controllers. For enterprise systems, this includes database access, message queue integration, and API implementations. The realization depends on the essence and on the external technical infrastructure.
The outer region is the Adaptation. This provides the interfaces through which other capabilities interact with this capability and through which this capability interacts with external systems. Unlike traditional adapters, adaptations are bidirectional and can have varying scopes depending on the capability's needs.
Let us see this structure in a concrete example:
// ESSENCE - Pure domain logic
public class TemperatureControlEssence {
private final ControlParameters parameters;
public TemperatureControlEssence(ControlParameters parameters) {
this.parameters = parameters;
}
/**
* Calculates control output based on current temperature.
* This is pure logic with no side effects or external dependencies.
*
* @param currentTemp The current temperature measurement
* @param targetTemp The desired temperature
* @return Control output value between 0.0 and 1.0
*/
public double calculateControl(double currentTemp, double targetTemp) {
double error = targetTemp - currentTemp;
double proportional = parameters.getKp() * error;
double integral = parameters.getKi() * parameters.getAccumulatedError();
double derivative = parameters.getKd() * (error - parameters.getLastError());
double output = proportional + integral + derivative;
return clamp(output, 0.0, 1.0);
}
private double clamp(double value, double min, double max) {
return Math.max(min, Math.min(max, value));
}
}
The essence shown above implements a PID control algorithm. Notice that it is completely independent of how temperature is measured or how the control output is applied. It contains pure algorithmic logic that can be tested in isolation, reasoned about mathematically, and evolved independently of infrastructure concerns. This separation is similar to the entities layer in Clean Architecture, but with a crucial difference: the essence is not trying to be technology-agnostic. It is domain-focused, which means it can use whatever computational approach best serves the domain, whether that is object-oriented design, functional programming, or even bare-metal bit manipulation for performance-critical embedded algorithms.
Now let us see how the realization brings this essence to life in an embedded system:
// REALIZATION - Hardware integration for embedded system
public class TemperatureControlRealization {
private final TemperatureControlEssence essence;
private final HardwareTimer timer;
private final ADCController adc;
private final PWMController pwm;
public TemperatureControlRealization(
TemperatureControlEssence essence,
HardwareTimer timer,
ADCController adc,
PWMController pwm
) {
this.essence = essence;
this.timer = timer;
this.adc = adc;
this.pwm = pwm;
}
/**
* Initializes hardware resources and sets up interrupt-driven control loop.
* This realization uses direct hardware access for real-time performance.
*/
public void initialize() {
// Configure ADC for temperature sensor on channel 0
adc.configure(0, ADCResolution.BITS_12, ADCSampleTime.CYCLES_15);
// Configure PWM for heater control on channel 1
pwm.configure(1, PWMFrequency.KHZ_10, PWMMode.EDGE_ALIGNED);
// Set up timer interrupt for 100Hz control loop
timer.setPeriod(10); // 10ms = 100Hz
timer.setInterruptHandler(this::controlLoopInterrupt);
timer.start();
}
/**
* Interrupt handler called at 100Hz by hardware timer.
* Reads sensor, calculates control output, updates actuator.
* Must complete within 10ms to maintain real-time behavior.
*/
private void controlLoopInterrupt() {
// Read current temperature from ADC
int rawADC = adc.readChannel(0);
double currentTemp = convertADCToTemperature(rawADC);
// Get target temperature from shared memory
double targetTemp = getTargetTemperature();
// Calculate control output using essence
double controlOutput = essence.calculateControl(currentTemp, targetTemp);
// Update PWM duty cycle
pwm.setDutyCycle(1, controlOutput);
}
private double convertADCToTemperature(int adcValue) {
// Convert 12-bit ADC value to temperature
// Assuming linear sensor: 0 degrees C = 0, 100 degrees C = 4095
return (adcValue / 4095.0) * 100.0;
}
private double getTargetTemperature() {
// Read from shared memory location set by user interface
return SharedMemory.readDouble(TARGET_TEMP_ADDRESS);
}
}
The realization shown above demonstrates how the same essence can be connected to real hardware. Notice several important aspects. First, the realization has direct access to hardware controllers for the ADC, PWM, and timer. There is no abstraction layer preventing efficient hardware access. Second, the interrupt handler is part of the realization, not hidden behind an interface. This allows the realization to optimize the critical path for real-time performance. Third, the realization depends on the essence, calling its calculateControl method, but the essence knows nothing about the realization. This dependency direction is crucial for testability and evolution.
Finally, let us see how the adaptation provides external interfaces:
// ADAPTATION - Interface for other capabilities
public class TemperatureControlAdaptation {
private final TemperatureControlRealization realization;
public TemperatureControlAdaptation(TemperatureControlRealization realization) {
this.realization = realization;
}
/**
* Provides a high-level interface for other capabilities to interact
* with temperature control without knowledge of implementation details.
*/
public void start() {
realization.initialize();
}
public void stop() {
// Cleanup and shutdown
}
public TemperatureStatus getStatus() {
// Return current status information
return new TemperatureStatus(
realization.getCurrentTemperature(),
realization.getTargetTemperature(),
realization.isControlActive()
);
}
public void setTargetTemperature(double temperature) {
// Validate and set new target
if (temperature < 0 || temperature > 100) {
throw new IllegalArgumentException("Temperature out of range");
}
realization.setTargetTemperature(temperature);
}
}
The adaptation provides a clean interface that other capabilities can use without knowing about hardware details or real-time constraints. This is similar to ports in Hexagonal Architecture, but with an important difference: the adaptation is not trying to make the capability look like something it is not. It exposes the capability's true nature through an appropriate interface.
This three-layer structure of Essence, Realization, and Adaptation forms the Capability Nucleus. It provides clear separation of concerns while avoiding the pitfalls of traditional layered or hexagonal approaches. The essence contains pure domain logic. The realization connects that logic to the real world, whether that world is hardware registers or cloud services. The adaptation provides appropriate interfaces for interaction.
Capability Contracts
The second core concept of CCA is Capability Contracts. Capabilities interact with each other through contracts rather than through direct dependencies. A contract defines what a capability provides and what it requires, but not how it fulfills those provisions and requirements.
A capability contract consists of three parts. The Provision declares what the capability offers to others. The Requirement declares what the capability needs from others. The Protocol defines the supported interaction patterns.
Let us examine a concrete contract:
/**
* Contract for temperature monitoring capability.
* Defines what this capability provides and requires.
*/
public interface TemperatureMonitoringContract {
/**
* PROVISION: This capability provides temperature measurements.
* Other capabilities can subscribe to updates.
*/
public interface Provision {
/**
* Subscribe to temperature updates.
*
* @param subscriber The subscriber to receive updates
* @param updateRate The desired update rate in Hz
*/
void subscribeToTemperature(TemperatureSubscriber subscriber, int updateRate);
/**
* Get current temperature reading.
*
* @return Current temperature in Celsius
*/
double getCurrentTemperature();
/**
* Get historical temperature data.
*
* @param startTime Start of time range
* @param endTime End of time range
* @return Temperature readings in specified range
*/
TemperatureHistory getHistory(Timestamp startTime, Timestamp endTime);
}
/**
* REQUIREMENT: This capability requires calibration data.
* Must be provided by a calibration management capability.
*/
public interface Requirement {
/**
* Get calibration parameters for the temperature sensor.
*
* @param sensorId The sensor identifier
* @return Calibration parameters
*/
CalibrationData getCalibration(String sensorId);
/**
* Notify when calibration data changes.
*
* @param listener The listener to notify
*/
void onCalibrationChange(CalibrationChangeListener listener);
}
/**
* PROTOCOL: Defines interaction patterns.
*/
public interface Protocol {
/**
* Specifies that temperature updates are delivered asynchronously
* through callbacks at the requested rate.
*/
void deliverySemantics();
/**
* Specifies quality attributes for this contract.
* Temperature readings must be delivered within 100ms of measurement.
*/
QualityAttributes getQualityAttributes();
}
}
This contract demonstrates several important principles. First, it focuses on the "what" rather than the "how". The provision specifies that temperature measurements are available, but not how they are obtained. The requirement specifies that calibration data is needed, but not where it comes from. Second, the contract includes protocol information that defines interaction patterns and quality attributes. This makes expectations explicit and verifiable. Third, the contract is bidirectional, specifying both what the capability provides and what it requires.
Contracts enable loose coupling between capabilities. A capability that needs temperature data depends on the TemperatureMonitoringContract, not on a specific implementation. This allows implementations to evolve independently as long as they continue to satisfy the contract. It also enables testing by allowing mock implementations of contracts.
Contracts also enable the Capability Registry to detect and prevent circular dependencies, which we will explore in detail later. For now, understand that every capability declares which contracts it provides and which it requires, and the registry ensures that the dependency graph remains acyclic.
Efficiency Gradients
The third core concept is Efficiency Gradients. This concept addresses a fundamental challenge in embedded systems: not all code paths have the same performance requirements. An interrupt handler must complete in microseconds with no memory allocation. A background logging task can use high-level abstractions and take milliseconds. Traditional architectures force us to choose a single level of abstraction for the entire system, but CCA allows different parts of the same capability to operate at different efficiency gradients.
An efficiency gradient is a spectrum from high abstraction and flexibility to low abstraction and maximum performance. At the high end, we use object- oriented design, dependency injection, and rich abstractions. At the low end, we use direct hardware access, inline functions, and minimal indirection. A capability can span multiple gradients, using the appropriate level for each code path.
Let us see this in practice with a motor control capability:
/**
* Motor control capability demonstrating efficiency gradients.
* Critical real-time path uses lowest gradient for performance.
* Non-critical paths use higher gradients for maintainability.
*/
public class MotorControlCapability implements CapabilityInstance {
// ESSENCE - Pure control algorithm
private final MotorControlEssence essence;
// Hardware resources
private static final int ENCODER_REGISTER = 0x40002000;
private static final int PWM_BASE_REGISTER = 0x40003000;
// State variables for interrupt handler
private volatile int currentPosition;
private volatile int targetPosition;
private volatile boolean controlEnabled;
public MotorControlCapability(MotorControlEssence essence) {
this.essence = essence;
}
@Override
public void initialize() {
// Initialize hardware
initializeEncoder();
initializePWM();
setupTimer();
}
@Override
public void start() {
controlEnabled = true;
startTimer();
}
@Override
public void stop() {
controlEnabled = false;
stopTimer();
disablePWM();
}
/**
* Timer interrupt handler - runs every 100 microseconds.
* This is the critical real-time path with highest efficiency gradient.
* Must complete within 100 microseconds to maintain control stability.
*/
public void timerInterruptHandler() {
if (!controlEnabled) {
return;
}
// Read encoder position directly from hardware register
// No function call overhead, no abstraction
currentPosition = readRegisterDirect(ENCODER_REGISTER);
// Calculate control output using essence
// This is the only function call in the critical path
int controlOutput = essence.calculateControlOutput(
currentPosition,
targetPosition
);
// Write PWM values directly to hardware registers
// Three-phase motor requires three PWM channels
writeRegisterDirect(PWM_BASE_REGISTER + 0, controlOutput);
writeRegisterDirect(PWM_BASE_REGISTER + 4, calculatePhaseB(controlOutput));
writeRegisterDirect(PWM_BASE_REGISTER + 8, calculatePhaseC(controlOutput));
}
/**
* Set target position for the motor.
* This is called from lower priority tasks, not from interrupt context.
* Uses medium efficiency gradient.
*/
public void setTargetPosition(int position) {
// Validate that position is in safe range
if (position < 0 || position > MAX_POSITION) {
throw new IllegalArgumentException("Position out of range");
}
// Atomic write to volatile variable
// Interrupt handler will see new value on next iteration
targetPosition = position;
}
/**
* Get current motor status.
* Uses low efficiency gradient - can allocate objects and use abstractions.
*/
public MotorStatus getStatus() {
// Create status object with current state
return new MotorStatus(
currentPosition,
targetPosition,
controlEnabled,
essence.getControlState()
);
}
// Native methods for direct hardware access
private native int readRegisterDirect(int address);
private native void writeRegisterDirect(int address, int value);
// Inline calculations for interrupt handler
private int calculatePhaseB(int phaseA) {
return phaseA + 120; // Simplified for example
}
private int calculatePhaseC(int phaseA) {
return phaseA + 240; // Simplified for example
}
}
This example demonstrates three efficiency gradients within a single capability. The timerInterruptHandler operates at the highest gradient, using direct register access and minimal abstraction to meet microsecond timing constraints. The setTargetPosition method operates at a medium gradient, using structured code with validation but avoiding expensive operations. The getStatus method operates at the lowest gradient, freely allocating objects and using abstractions for maintainability.
The key insight is that the architecture does not force us to choose one level for the entire system. We can use bare-metal programming where needed for real-time performance, while using higher abstractions for non-critical functionality. This flexibility is essential for embedded systems that must balance real-time constraints with software engineering best practices.
For enterprise systems, efficiency gradients serve a different but equally important purpose. The critical path for high-traffic operations can be optimized for performance, while administrative operations and batch processing can use more flexible but potentially slower implementations. This allows the same capability to serve both performance-critical and flexibility- critical needs.
Evolution Envelopes
The fourth core concept is Evolution Envelopes. An evolution envelope defines how a capability can change over time while maintaining compatibility with other capabilities. It specifies what can change, what must remain stable, and how changes are communicated.
Every capability has an evolution envelope that includes version information, deprecation policies, and migration paths. When a capability needs to change its contract, the evolution envelope defines how to introduce that change without breaking dependent capabilities.
Let us examine an evolution envelope:
/**
* Evolution envelope for a capability.
* Manages versioning and compatibility.
*/
public class EvolutionEnvelope {
private final String capabilityName;
private final Version currentVersion;
private final List<Version> supportedVersions;
private final DeprecationPolicy deprecationPolicy;
private final MigrationGuide migrationGuide;
/**
* Checks if a capability version is compatible with this capability.
*
* @param requiredVersion The version required by a dependent capability
* @return true if compatible, false otherwise
*/
public boolean isCompatible(Version requiredVersion) {
// Semantic versioning: major.minor.patch
// Same major version = compatible
// Higher minor version = backward compatible
// Patch version = always compatible
if (requiredVersion.getMajor() != currentVersion.getMajor()) {
// Different major version - check if we support it
return supportedVersions.contains(requiredVersion);
}
// Same major version - check minor version
return currentVersion.getMinor() >= requiredVersion.getMinor();
}
/**
* Provides migration path from an old version to the current version.
*
* @param fromVersion The version to migrate from
* @return Migration steps to reach current version
*/
public List<MigrationStep> getMigrationPath(Version fromVersion) {
return migrationGuide.getPath(fromVersion, currentVersion);
}
/**
* Checks if a feature is deprecated.
*
* @param featureName The name of the feature
* @return Deprecation information if deprecated, null otherwise
*/
public DeprecationInfo getDeprecationInfo(String featureName) {
return deprecationPolicy.getDeprecationInfo(featureName);
}
}
Evolution envelopes make architectural evolution explicit and manageable. Instead of hoping that changes will not break anything, we have a formal mechanism for introducing changes, maintaining backward compatibility, and eventually retiring old versions.
Consider a payment processing capability that needs to add support for a new payment method. With an evolution envelope, we can:
- Introduce the new method in a minor version update (e.g., 1.2.0 to 1.3.0)
- Keep the old methods working without changes
- Mark old methods as deprecated in a later minor version
- Provide migration tools and documentation
- Remove deprecated methods in a major version update (e.g., 2.0.0)
- Support both 1.x and 2.x versions during a transition period
This structured approach to evolution prevents the architectural decay that plagues many systems. Changes are planned, communicated, and managed rather than being ad-hoc modifications that accumulate technical debt.
DETAILED ARCHITECTURE DESCRIPTION
Now that we have introduced the core concepts, let us examine how they fit together into a complete architectural pattern. A system built with Capability-Centric Architecture consists of multiple capabilities, each structured as a Capability Nucleus with an Evolution Envelope. Capabilities interact through contracts, use efficiency gradients to balance performance and abstraction, and evolve according to their evolution envelopes.
The overall system structure looks conceptually like this:
System
|
+-- Capability A (Nucleus + Envelope)
| |
| +-- Essence (pure logic)
| +-- Realization (infrastructure integration)
| +-- Adaptation (external interfaces)
| +-- Contract (provisions, requirements, protocols)
| +-- Evolution Envelope (versioning, migration)
|
+-- Capability B (Nucleus + Envelope)
| |
| +-- Essence
| +-- Realization
| +-- Adaptation
| +-- Contract
| +-- Evolution Envelope
|
+-- Capability C (Nucleus + Envelope)
|
+-- Essence
+-- Realization
+-- Adaptation
+-- Contract
+-- Evolution Envelope
Capabilities are connected through their contracts. When Capability A needs something that Capability B provides, we establish a contract binding. These bindings are managed by a Capability Registry that tracks all capabilities, their contracts, and their bindings.
The Capability Registry
The Capability Registry is the central coordination point for the architecture. It maintains a catalog of all capabilities, validates contract compatibility, detects circular dependencies, and determines initialization order.
Let us examine the registry implementation:
/**
* Registry that manages capabilities and their interactions.
* Central coordination point for the architecture.
*/
public class CapabilityRegistry {
private final Map<String, CapabilityDescriptor> capabilities;
private final Map<String, List<ContractBinding>> bindings;
private final DependencyResolver resolver;
public CapabilityRegistry() {
this.capabilities = new ConcurrentHashMap<>();
this.bindings = new ConcurrentHashMap<>();
this.resolver = new DependencyResolver();
}
/**
* Registers a capability in the system.
*
* @param descriptor Description of the capability including its contract
*/
public void registerCapability(CapabilityDescriptor descriptor) {
// Validate capability descriptor
validateDescriptor(descriptor);
// Check contract compatibility with existing capabilities
checkContractCompatibility(descriptor);
// Register the capability
capabilities.put(descriptor.getName(), descriptor);
// Resolve pending bindings
resolvePendingBindings(descriptor);
}
/**
* Binds a requirement of one capability to the provision of another.
*
* @param consumer The capability that needs something
* @param provider The capability that provides it
* @param contractType The type of contract to bind
*/
public void bindCapabilities(
String consumer,
String provider,
Class<?> contractType
) {
CapabilityDescriptor consumerDesc = capabilities.get(consumer);
CapabilityDescriptor providerDesc = capabilities.get(provider);
if (consumerDesc == null || providerDesc == null) {
throw new IllegalArgumentException("Both capabilities must be registered");
}
// Verify that provider actually provides this contract
if (!providerDesc.provides(contractType)) {
throw new IllegalArgumentException(
provider + " does not provide " + contractType.getName()
);
}
// Check for circular dependencies
if (resolver.wouldCreateCycle(consumer, provider)) {
throw new CircularDependencyException(
"Binding would create circular dependency: " +
consumer + " -> " + provider
);
}
// Create the binding
ContractBinding binding = new ContractBinding(
consumer,
provider,
contractType
);
// Store the binding
bindings.computeIfAbsent(consumer, k -> new ArrayList<>()).add(binding);
// Update dependency graph
resolver.addDependency(consumer, provider);
}
/**
* Gets the initialization order for all capabilities.
* Capabilities with no dependencies are initialized first.
*
* @return List of capability names in initialization order
*/
public List<String> getInitializationOrder() {
return resolver.topologicalSort();
}
private void validateDescriptor(CapabilityDescriptor descriptor) {
if (descriptor.getName() == null || descriptor.getName().isEmpty()) {
throw new IllegalArgumentException("Capability must have a name");
}
if (descriptor.getContract() == null) {
throw new IllegalArgumentException("Capability must have a contract");
}
if (descriptor.getEvolutionEnvelope() == null) {
throw new IllegalArgumentException("Capability must have an evolution envelope");
}
}
private void checkContractCompatibility(CapabilityDescriptor descriptor) {
// Check if an existing capability provides the same contract
for (CapabilityDescriptor existing : capabilities.values()) {
if (existing.provides(descriptor.getContract().getClass())) {
// Multiple providers for same contract - ensure compatibility
if (!areContractsCompatible(existing.getContract(), descriptor.getContract())) {
throw new ContractConflictException(
"Incompatible contracts: " + existing.getName() +
" and " + descriptor.getName()
);
}
}
}
}
private boolean areContractsCompatible(Object contract1, Object contract2) {
// Contracts are compatible if they have the same interface
// and compatible evolution envelopes
return contract1.getClass().equals(contract2.getClass());
}
private void resolvePendingBindings(CapabilityDescriptor descriptor) {
// Check if capabilities were waiting for this capability
// and bind them now that it is available
for (CapabilityDescriptor waiting : capabilities.values()) {
for (Class<?> required : waiting.getRequiredContracts()) {
if (descriptor.provides(required)) {
bindCapabilities(waiting.getName(), descriptor.getName(), required);
}
}
}
}
}
The Capability Registry prevents circular dependencies by checking the dependency graph before creating bindings. This is one of the key mechanisms for avoiding architectural antipatterns. If a binding would create a cycle, the registry rejects it and forces the architect to restructure the capabilities.
Let us consider how this prevents a common antipattern. Suppose we have three capabilities: Customer Management, Order Processing, and Inventory Management. Order Processing needs customer information, so it requires the Customer Management contract. Order Processing also needs to check inventory, so it requires the Inventory Management contract. So far this is fine.
Now suppose Inventory Management wants to track which customers order which products most frequently for demand forecasting. In a naive implementation, Inventory Management might use the Customer Management contract. This creates a potential cycle if Customer Management later needs something from Inventory Management.
The Capability Registry would reject this binding. Instead, we must restructure. One solution is to introduce a new capability, Customer Analytics, that depends on both Customer Management and Inventory Management. Customer Analytics provides demand forecasts without creating a cycle:
Customer Management --> Customer Analytics <-- Inventory Management
|
v
Demand Forecast
This forced restructuring leads to better architecture. Customer Analytics is a cohesive capability with a clear purpose. It can evolve independently and be reused by other capabilities that need customer analytics.
The Capability Lifecycle Manager
Another key mechanism is the Capability Lifecycle Manager. This component manages the lifecycle of capabilities from initialization through operation to shutdown. It uses the initialization order from the Capability Registry to start capabilities in the correct sequence.
Let us examine the lifecycle manager:
/**
* Manages the lifecycle of all capabilities in the system.
*/
public class CapabilityLifecycleManager {
private final CapabilityRegistry registry;
private final Map<String, CapabilityInstance> instances;
private final ExecutorService executor;
public CapabilityLifecycleManager(CapabilityRegistry registry) {
this.registry = registry;
this.instances = new ConcurrentHashMap<>();
this.executor = Executors.newCachedThreadPool();
}
/**
* Initializes all capabilities in dependency order.
* Ensures required capabilities are initialized before dependent capabilities.
*/
public void initializeAll() {
List<String> initOrder = registry.getInitializationOrder();
for (String capabilityName : initOrder) {
initializeCapability(capabilityName);
}
}
/**
* Initializes a single capability.
*
* @param capabilityName The name of the capability to initialize
*/
public void initializeCapability(String capabilityName) {
CapabilityDescriptor descriptor = registry.getCapability(capabilityName);
// Create instance
CapabilityInstance instance = createInstance(descriptor);
// Inject dependencies
injectDependencies(instance, capabilityName);
// Initialize
instance.initialize();
// Store instance
instances.put(capabilityName, instance);
// Start if auto-start is enabled
if (descriptor.isAutoStart()) {
instance.start();
}
}
/**
* Shuts down all capabilities in reverse dependency order.
* Ensures dependent capabilities are shut down before required capabilities.
*/
public void shutdownAll() {
List<String> initOrder = registry.getInitializationOrder();
// Shutdown in reverse order
for (int i = initOrder.size() - 1; i >= 0; i--) {
String capabilityName = initOrder.get(i);
shutdownCapability(capabilityName);
}
executor.shutdown();
}
/**
* Shuts down a single capability.
*
* @param capabilityName The name of the capability to shut down
*/
public void shutdownCapability(String capabilityName) {
CapabilityInstance instance = instances.get(capabilityName);
if (instance != null) {
instance.stop();
instance.cleanup();
instances.remove(capabilityName);
}
}
private CapabilityInstance createInstance(CapabilityDescriptor descriptor) {
// Use reflection or factory to create instance
try {
Class<?> capabilityClass = Class.forName(descriptor.getImplementationClass());
return (CapabilityInstance) capabilityClass.getDeclaredConstructor().newInstance();
} catch (Exception e) {
throw new CapabilityInstantiationException(
"Failed to create instance of " + descriptor.getName(),
e
);
}
}
private void injectDependencies(CapabilityInstance instance, String capabilityName) {
List<ContractBinding> capabilityBindings = registry.getBindings(capabilityName);
for (ContractBinding binding : capabilityBindings) {
// Get provider instance
CapabilityInstance provider = instances.get(binding.getProvider());
// Get contract implementation from provider
Object contractImpl = provider.getContractImplementation(binding.getContractType());
// Inject into consumer
instance.injectDependency(binding.getContractType(), contractImpl);
}
}
}
The lifecycle manager ensures that capabilities are initialized in the correct order based on their dependencies. A capability that requires another capability's contract is initialized after that capability. This prevents runtime errors from missing dependencies and makes the system's startup behavior predictable and deterministic.
During shutdown, the lifecycle manager reverses the initialization order. Capabilities that depend on others are shut down first, ensuring they do not try to use capabilities that have already been cleaned up. This graceful shutdown is especially important for embedded systems where improper shutdown can leave hardware in an unsafe state.
APPLICATION TO EMBEDDED SYSTEMS
Now that we understand the core concepts and mechanisms of Capability-Centric Architecture, let us see how it applies to embedded systems. Embedded systems have unique challenges: limited resources, real-time constraints, direct hardware access, and long deployment lifecycles. CCA addresses these challenges through its flexibility in efficiency gradients, explicit resource management, and evolution support.
Let us build a complete embedded system example: a sensor data acquisition system that reads multiple sensors, processes the data, and stores it for analysis. This system must meet real-time constraints for sensor reading while providing flexible data processing and storage.
We will structure this as three capabilities: Sensor Acquisition, Data Processing, and Data Storage. Each capability will demonstrate different aspects of CCA applied to embedded systems.
Sensor Acquisition Capability
The Sensor Acquisition capability reads sensor data through interrupt-driven hardware access. It demonstrates the highest efficiency gradient for the critical path and lower gradients for non-critical operations.
/**
* Sensor acquisition capability for embedded system.
* Demonstrates efficiency gradients and real-time constraints.
*/
public class SensorAcquisitionCapability implements CapabilityInstance {
// ESSENCE - Pure sensor data processing logic
private final SensorCalibration calibration;
private final DataValidator validator;
// Hardware resources for critical path
private static final int SENSOR_REGISTER = 0x40001000;
private static final int BUFFER_SIZE = 256;
private final int[] sensorBuffer = new int[BUFFER_SIZE];
private volatile int bufferWriteIndex = 0;
private volatile int bufferReadIndex = 0;
// Non-critical resources
private final Queue<SensorReading> storageQueue;
public SensorAcquisitionCapability(
SensorCalibration calibration,
DataValidator validator
) {
this.calibration = calibration;
this.validator = validator;
this.storageQueue = new ConcurrentLinkedQueue<>();
}
@Override
public void initialize() {
// Configure sensor hardware
configureSensorADC();
// Set up interrupt handler
setupSensorInterrupt();
}
@Override
public void start() {
// Enable sensor interrupts
enableSensorInterrupts();
// Start background processing thread
startBackgroundProcessing();
}
/**
* Interrupt handler for sensor data ready.
* CRITICAL PATH - Highest efficiency gradient.
* Must complete within 10 microseconds.
*/
public void sensorInterruptHandler() {
// Read raw sensor value directly from hardware register
// No abstraction, no function calls, minimal processing
int rawValue = readRegisterDirect(SENSOR_REGISTER);
// Store in circular buffer
sensorBuffer[bufferWriteIndex] = rawValue;
bufferWriteIndex = (bufferWriteIndex + 1) % BUFFER_SIZE;
// That is it - interrupt handler complete
// Processing happens in background thread
}
/**
* Background processing of sensor data.
* MEDIUM EFFICIENCY GRADIENT - Uses structured processing
* but avoids expensive operations.
*/
public void processSensorData() {
while (bufferReadIndex != bufferWriteIndex) {
int rawValue = sensorBuffer[bufferReadIndex];
bufferReadIndex = (bufferReadIndex + 1) % BUFFER_SIZE;
// Apply calibration using object-oriented design
double calibratedValue = calibration.apply(rawValue);
// Validate measurement
if (validator.isValid(calibratedValue)) {
// Create structured data object
SensorReading reading = new SensorReading(
System.currentTimeMillis(),
calibratedValue
);
// Pass to storage on lower efficiency gradient
storageQueue.enqueue(reading);
}
}
}
// Native method for direct hardware access
private native int readRegisterDirect(int address);
}
This capability demonstrates three efficiency gradients. The interrupt handler operates at the highest gradient with direct register access and minimal processing. The background processing operates at a medium gradient with structured code and object creation. Storage operations, which we will see next, operate at the lowest gradient with full abstraction.
The key insight is that we do not sacrifice real-time performance for clean architecture. The interrupt handler is as efficient as hand-written assembly, yet it is part of a well-structured capability that can be tested, evolved, and maintained.
Resource Management in Embedded Systems
Embedded systems often have limited memory and must manage resource allocation carefully. CCA supports this through explicit resource contracts. Let us see how a capability declares its resource requirements:
/**
* Resource contract for capabilities that need memory allocation.
*/
public interface ResourceContract {
/**
* Declares the memory requirements of this capability.
*
* @return Memory requirements in bytes
*/
MemoryRequirements getMemoryRequirements();
/**
* Declares the CPU requirements of this capability.
*
* @return CPU requirements as percentage of total CPU time
*/
CPURequirements getCPURequirements();
/**
* Allocates resources for this capability.
* Called during initialization.
*
* @param allocator The resource allocator
*/
void allocateResources(ResourceAllocator allocator);
/**
* Releases resources used by this capability.
* Called during shutdown.
*/
void releaseResources();
}
Capabilities declare their resource requirements through this contract, and the system can verify that sufficient resources are available before initializing capabilities. This prevents runtime resource exhaustion and makes resource usage explicit and manageable.
A sensor acquisition capability might declare its requirements like this:
@Override
public MemoryRequirements getMemoryRequirements() {
return new MemoryRequirements()
.withStaticMemory(BUFFER_SIZE * 4) // Sensor buffer
.withStackMemory(512) // Interrupt handler stack
.withHeapMemory(1024); // Background processing
}
@Override
public CPURequirements getCPURequirements() {
return new CPURequirements()
.withInterruptTime(10) // 10 microseconds per interrupt
.withBackgroundTime(5); // 5% of CPU for background processing
}
The system can then verify at startup that the total memory and CPU requirements of all capabilities fit within available resources. This compile- time or startup-time verification prevents runtime failures and makes resource constraints visible in the architecture.
APPLICATION TO ENTERPRISE SYSTEMS
Enterprise systems have different challenges than embedded systems. They must scale to handle varying loads, integrate with numerous external systems, support multiple deployment models, and evolve quickly to meet changing business needs. CCA addresses these challenges through its contract-based interaction model, deployment flexibility, and evolution envelopes.
Let us build an enterprise system example: an e-commerce platform with product catalog, shopping cart, order processing, payment processing, inventory management, and customer management capabilities. Each capability is independently deployable and scalable.
Product Catalog Capability
The Product Catalog capability provides product information to other capabilities. It demonstrates enterprise-focused capability structure with database integration, caching, and event-driven communication.
/**
* Product catalog capability for enterprise e-commerce system.
* Demonstrates enterprise-focused capability structure.
*/
public class ProductCatalogCapability implements CapabilityInstance {
// ESSENCE - Pure product catalog logic
private final ProductCatalogEssence essence;
// REALIZATION - Enterprise infrastructure integration
private final DatabaseConnectionPool database;
private final CacheManager cache;
private final SearchEngine searchEngine;
private final MessageBroker messageBroker;
// Dependencies injected through contracts
private PricingContract pricingService;
private InventoryContract inventoryService;
public ProductCatalogCapability(
DatabaseConnectionPool database,
CacheManager cache,
SearchEngine searchEngine,
MessageBroker messageBroker
) {
this.essence = new ProductCatalogEssence();
this.database = database;
this.cache = cache;
this.searchEngine = searchEngine;
this.messageBroker = messageBroker;
}
@Override
public void initialize() {
// Initialize database schema
initializeSchema();
// Warm up cache with popular products
warmUpCache();
// Initialize search index
initializeSearchIndex();
// Subscribe to inventory change events
subscribeToInventoryChanges();
}
@Override
public void start() {
// Start background tasks
startCacheRefreshTask();
startSearchIndexUpdateTask();
}
/**
* Gets product information by ID.
* Uses caching for performance.
*
* @param productId The product identifier
* @return Product information
*/
public Product getProduct(String productId) {
// Check cache first
Product product = cache.get("product:" + productId);
if (product != null) {
return product;
}
// Cache miss - load from database
product = loadProductFromDatabase(productId);
// Enrich with pricing and inventory
if (product != null) {
enrichProduct(product);
// Store in cache
cache.put("product:" + productId, product, Duration.ofMinutes(15));
}
return product;
}
/**
* Searches for products matching criteria.
* Uses search engine for full-text search.
*
* @param query The search query
* @return List of matching products
*/
public List<Product> searchProducts(SearchQuery query) {
// Execute search
SearchResults results = searchEngine.search(query);
// Load product details
List<Product> products = new ArrayList<>();
for (String productId : results.getProductIds()) {
Product product = getProduct(productId);
if (product != null) {
products.add(product);
}
}
return products;
}
/**
* Updates product information.
* Publishes change event for other capabilities.
*
* @param product The updated product
*/
public void updateProduct(Product product) {
// Validate using essence
ValidationResult validation = essence.validateProduct(product);
if (!validation.isValid()) {
throw new ValidationException(validation.getErrors());
}
// Update in database
updateProductInDatabase(product);
// Invalidate cache
cache.invalidate("product:" + product.getId());
// Update search index
searchEngine.updateDocument(product);
// Publish change event
ProductChangedEvent event = new ProductChangedEvent(product);
messageBroker.publish("product.changed", event);
}
private void enrichProduct(Product product) {
// Get current price from pricing service
if (pricingService != null) {
Price price = pricingService.getPrice(product.getId());
product.setPrice(price);
}
// Get inventory status from inventory service
if (inventoryService != null) {
InventoryStatus status = inventoryService.getStatus(product.getId());
product.setInventoryStatus(status);
}
}
private void subscribeToInventoryChanges() {
// Listen for inventory changes to invalidate cache
messageBroker.subscribe("inventory.changed", event -> {
InventoryChangedEvent invEvent = (InventoryChangedEvent) event;
cache.invalidate("product:" + invEvent.getProductId());
});
}
@Override
public Object getContractImplementation(Class<?> contractType) {
if (contractType == ProductCatalogContract.class) {
return new ProductCatalogContractImpl(this);
}
return null;
}
@Override
public void injectDependency(Class<?> contractType, Object implementation) {
if (contractType == PricingContract.class) {
this.pricingService = (PricingContract) implementation;
} else if (contractType == InventoryContract.class) {
this.inventoryService = (InventoryContract) implementation;
}
}
}
The Product Catalog capability demonstrates several enterprise patterns. It uses caching for performance, a search engine for full-text search, database transactions for consistency, and message-based events for loose coupling. However, all these infrastructure concerns are in the realization layer. The essence contains pure product catalog logic that can be tested independently.
The capability interacts with Pricing and Inventory capabilities through contracts. This allows each capability to evolve independently. For example, the Pricing capability could change from a simple database lookup to a complex dynamic pricing algorithm with machine learning, and the Product Catalog capability would not need to change as long as the contract remains stable.
Deployment Flexibility
For enterprise systems, deployment flexibility is critical. CCA supports multiple deployment models through deployment descriptors. A capability can be deployed in different modes depending on requirements:
/**
* Deployment descriptor for a capability.
* Specifies how the capability should be deployed.
*/
public class DeploymentDescriptor {
private final String capabilityName;
private final DeploymentMode mode;
private final ScalingPolicy scalingPolicy;
private final ResourceLimits resourceLimits;
private final HealthCheck healthCheck;
public enum DeploymentMode {
EMBEDDED, // Deploy in same process as other capabilities
STANDALONE, // Deploy in separate process
CONTAINERIZED, // Deploy in container (Docker, etc.)
SERVERLESS // Deploy as serverless function
}
public DeploymentDescriptor(
String capabilityName,
DeploymentMode mode,
ScalingPolicy scalingPolicy,
ResourceLimits resourceLimits,
HealthCheck healthCheck
) {
this.capabilityName = capabilityName;
this.mode = mode;
this.scalingPolicy = scalingPolicy;
this.resourceLimits = resourceLimits;
this.healthCheck = healthCheck;
}
// Getters omitted for brevity
}
A capability can be deployed in different modes depending on requirements. During development, all capabilities might run in a single process for easy debugging. In production, high-traffic capabilities could be deployed in containers with auto-scaling, while low-traffic capabilities run as serverless functions to reduce costs.
The deployment mode is independent of the capability implementation. The same Product Catalog capability code can run embedded in a monolith, in a standalone microservice, in a Docker container, or as a serverless function. The adaptation layer handles the differences in how the capability is accessed.
INTEGRATION OF MODERN TECHNOLOGIES
Capability-Centric Architecture is designed to integrate modern technologies like AI, big data, cloud computing, and containerization. These technologies are not afterthoughts but are supported by the core architecture mechanisms.
AI and Machine Learning Integration
For AI integration, we treat AI models as specialized capabilities with specific contracts. An AI model capability provides predictions or classifications through its contract and requires training data and model management through other contracts.
/**
* AI model capability for product recommendations.
* Demonstrates integration of machine learning into the architecture.
*/
public class ProductRecommendationAICapability implements CapabilityInstance {
// ESSENCE - Recommendation logic (model-agnostic)
private final RecommendationEssence essence;
// REALIZATION - ML infrastructure integration
private final ModelRegistry modelRegistry;
private final FeatureStore featureStore;
private final InferenceEngine inferenceEngine;
private final ModelTrainingPipeline trainingPipeline;
// Dependencies
private ProductCatalogContract productCatalog;
private CustomerBehaviorContract customerBehavior;
private volatile MLModel currentModel;
public ProductRecommendationAICapability(
ModelRegistry modelRegistry,
FeatureStore featureStore,
InferenceEngine inferenceEngine,
ModelTrainingPipeline trainingPipeline
) {
this.essence = new RecommendationEssence();
this.modelRegistry = modelRegistry;
this.featureStore = featureStore;
this.inferenceEngine = inferenceEngine;
this.trainingPipeline = trainingPipeline;
}
@Override
public void initialize() {
// Load current production model
currentModel = modelRegistry.getProductionModel("product-recommendation");
// Initialize inference engine with model
inferenceEngine.loadModel(currentModel);
// Start model monitoring
startModelMonitoring();
}
@Override
public void start() {
// Start background model training if enabled
if (trainingPipeline.isEnabled()) {
startModelTraining();
}
}
/**
* Gets product recommendations for a customer.
*
* @param customerId The customer identifier
* @param context Additional context for recommendations
* @return List of recommended products
*/
public List<ProductRecommendation> getRecommendations(
String customerId,
RecommendationContext context
) {
// Extract features for the customer
Features features = extractFeatures(customerId, context);
// Run inference with current model
InferenceResult result = inferenceEngine.predict(features);
// Convert model output to product recommendations
List<ProductRecommendation> recommendations =
convertToRecommendations(result);
// Apply business rules using essence
recommendations = essence.applyBusinessRules(
recommendations,
customerId,
context
);
return recommendations;
}
/**
* Triggers retraining of the recommendation model.
* Uses latest customer behavior data.
*/
public void retrainModel() {
// Get training data from feature store
TrainingData data = featureStore.getTrainingData(
"product-recommendation",
Timestamp.now().minusDays(30),
Timestamp.now()
);
// Train new model
trainingPipeline.submitTrainingJob(
"product-recommendation",
data,
new TrainingCallback() {
@Override
public void onTrainingComplete(MLModel newModel) {
handleNewModel(newModel);
}
@Override
public void onTrainingFailed(Exception e) {
// Log error and alert
}
}
);
}
private void handleNewModel(MLModel newModel) {
// Validate new model performance
ModelMetrics metrics = validateModel(newModel);
if (metrics.meetsQualityThreshold()) {
// Register new model
modelRegistry.registerModel(newModel, "product-recommendation");
// Promote to production
modelRegistry.promoteToProduction(newModel.getId());
// Load new model into inference engine
inferenceEngine.loadModel(newModel);
// Update current model reference
currentModel = newModel;
} else {
// Model does not meet quality threshold - keep current model
// Alert data science team
}
}
}
The AI capability follows the same structure as other capabilities. The essence contains business logic for applying rules to recommendations. The realization handles the ML infrastructure including model registry, feature store, and inference engine. The adaptation provides a simple interface to get recommendations.
This structure allows the ML technology to evolve independently. We could replace the inference engine with a different one, change the model architecture, or even switch from one ML framework to another, all without affecting capabilities that use recommendations.
IMPLEMENTATION GUIDELINES
Implementing a system with Capability-Centric Architecture requires following specific guidelines to achieve the benefits of the pattern.
Guideline One: Identify Capabilities Based on Cohesive Functionality
The most important guideline is to identify capabilities based on cohesive functionality rather than technical layers or organizational structure.
A capability should represent a complete unit of functionality that delivers value. It should have a clear purpose that can be expressed in a single sentence. For example, Product Catalog manages product information. Payment Processing handles payment transactions. Motor Control regulates motor speed and position. Each of these is a cohesive capability.
Avoid creating capabilities based on technical layers. Do not create a Database Access capability or a User Interface capability. These are technical concerns that should be part of the realization layer of domain capabilities. Similarly, avoid creating capabilities based on organizational boundaries. The fact that different teams work on different parts of the system does not mean those parts should be separate capabilities.
Guideline Two: Define Clear Contracts for Each Capability
A contract should specify what the capability provides, what it requires, and the protocols for interaction. Contracts should be stable but not rigid. Use semantic versioning to manage contract evolution. Minor version changes add new features while maintaining backward compatibility. Major version changes can break compatibility but should be rare and well-planned.
When defining contracts, focus on the "what" rather than the "how". A contract specifies what functionality is provided, not how it is implemented. This allows the implementation to evolve without affecting consumers of the contract.
Guideline Three: Use Efficiency Gradients Appropriately
Not every operation needs to be optimized to the maximum. Identify the critical paths in your system and optimize those. Use higher abstractions for non-critical paths to improve maintainability.
For embedded systems, the critical path is usually the real-time control loop or interrupt handler. These should use direct hardware access and minimal abstraction. Background tasks like logging, diagnostics, and communication can use higher abstractions.
For enterprise systems, the critical path is usually the request handling path for high-traffic operations. These should be optimized for performance. Administrative operations, batch processing, and analytics can use more flexible but potentially slower implementations.
Guideline Four: Manage Dependencies Carefully
Every dependency should be through a contract, not through a direct reference to another capability's implementation. This allows capabilities to be tested in isolation and deployed independently.
Use the Capability Registry to detect circular dependencies early. If a circular dependency is detected, restructure the capabilities. Often this means extracting a new capability that both original capabilities depend on, which breaks the cycle.
Guideline Five: Plan for Evolution from the Start
Every capability should have an evolution envelope that specifies its versioning strategy and deprecation policy. When you need to make a breaking change to a contract, introduce it as a new major version and maintain the old version for a transition period.
Document migration paths from old to new versions. Provide tools to help consumers migrate. Communicate changes clearly and give consumers sufficient time to adapt.
TESTING STRATEGIES
Capability-Centric Architecture provides natural boundaries for testing. The separation of Essence, Realization, and Adaptation allows different testing strategies for different layers.
Essence Testing
The essence contains pure domain logic with no external dependencies. This makes it ideal for unit testing. Essence tests run in milliseconds, require no infrastructure, and can achieve 100 percent code coverage.
public class TemperatureControlEssenceTest {
@Test
public void testCalculateControl_AtTarget_OutputIsZero() {
ControlParameters params = new ControlParameters(1.0, 0.1, 0.05);
TemperatureControlEssence essence = new TemperatureControlEssence(params);
double output = essence.calculateControl(25.0, 25.0);
assertEquals(0.0, output, 0.001);
}
@Test
public void testCalculateControl_BelowTarget_OutputIsPositive() {
ControlParameters params = new ControlParameters(1.0, 0.1, 0.05);
TemperatureControlEssence essence = new TemperatureControlEssence(params);
double output = essence.calculateControl(20.0, 25.0);
assertTrue(output > 0.0);
}
@Test
public void testCalculateControl_AboveTarget_OutputIsNegative() {
ControlParameters params = new ControlParameters(1.0, 0.1, 0.05);
TemperatureControlEssence essence = new TemperatureControlEssence(params);
double output = essence.calculateControl(30.0, 25.0);
assertTrue(output < 0.0);
}
}
Essence tests are deterministic, fast, and easy to write. They form the foundation of the testing pyramid and should provide comprehensive coverage of domain logic.
Realization Testing
The realization integrates with infrastructure. Realization tests verify that the capability correctly interacts with databases, message queues, hardware, and other infrastructure components. These tests use mock infrastructure and run in seconds rather than milliseconds.
public class ProductCatalogRealizationTest {
@Test
public void testGetProduct_DatabaseQuery_ReturnsProduct() {
// Arrange
MockDatabase database = new MockDatabase();
database.insert("products", new Product("P123", "Test Product"));
ProductCatalogCapability capability = new ProductCatalogCapability(
database,
new MockCache(),
new MockSearchEngine(),
new MockMessageBroker()
);
// Act
Product product = capability.getProduct("P123");
// Assert
assertNotNull(product);
assertEquals("Test Product", product.getName());
}
@Test
public void testUpdateProduct_PublishesEvent() {
// Arrange
MockMessageBroker broker = new MockMessageBroker();
ProductCatalogCapability capability = new ProductCatalogCapability(
new MockDatabase(),
new MockCache(),
new MockSearchEngine(),
broker
);
Product product = new Product("P123", "Updated Product");
// Act
capability.updateProduct(product);
// Assert
assertTrue(broker.wasPublished("product.changed"));
}
}
Realization tests verify infrastructure integration without requiring actual infrastructure. This makes them fast enough to run in continuous integration while still providing confidence that the capability works correctly.
Contract Testing
Contract tests verify that a capability correctly implements its contract. Both provider and consumer tests ensure that the contract is fulfilled and that version compatibility is maintained.
public class ProductCatalogContractTest {
@Test
public void testContract_AllMethodsImplemented() {
ProductCatalogCapability capability = createCapability();
ProductCatalogContract contract =
(ProductCatalogContract) capability.getContractImplementation(
ProductCatalogContract.class
);
assertNotNull(contract);
assertNotNull(contract.getProduct("P123"));
assertNotNull(contract.searchProducts(new SearchQuery()));
}
@Test
public void testContract_BackwardCompatibility_v1_to_v2() {
// Verify that v2 implementation works with v1 consumers
ProductCatalogCapability v2Capability = createV2Capability();
ProductCatalogContract.V1 v1Contract =
(ProductCatalogContract.V1) v2Capability.getContractImplementation(
ProductCatalogContract.V1.class
);
assertNotNull(v1Contract);
// Verify v1 methods still work
}
}
Contract tests ensure that capabilities can be evolved without breaking consumers. They verify that new versions maintain compatibility with old versions and that deprecation policies are followed.
End-to-End Testing
End-to-end tests verify that the complete system works correctly with all capabilities integrated. These tests are the slowest and most expensive but provide the highest confidence in system behavior.
public class ECommerceSystemTest {
@Test
public void testCompleteOrder_AllCapabilities_OrderProcessed() {
// Arrange - Start all capabilities
CapabilityRegistry registry = new CapabilityRegistry();
registerAllCapabilities(registry);
CapabilityLifecycleManager lifecycle = new CapabilityLifecycleManager(registry);
lifecycle.initializeAll();
// Act - Execute complete order flow
String customerId = "C123";
String productId = "P456";
// Add product to cart
ShoppingCartContract cart = getCapability(ShoppingCartContract.class);
cart.addItem(customerId, productId, 1);
// Process order
OrderProcessingContract orders = getCapability(OrderProcessingContract.class);
Order order = orders.createOrder(customerId);
// Process payment
PaymentProcessingContract payments = getCapability(PaymentProcessingContract.class);
Payment payment = payments.processPayment(order.getId(), paymentDetails);
// Assert - Verify order completed
assertEquals(OrderStatus.COMPLETED, order.getStatus());
assertEquals(PaymentStatus.APPROVED, payment.getStatus());
// Cleanup
lifecycle.shutdownAll();
}
}
End-to-end tests should be used sparingly for critical user journeys. The bulk of testing should be at the essence and realization levels where tests are faster and more focused.
CONCLUSION
Capability-Centric Architecture provides a unified pattern for building systems across the embedded-to-enterprise spectrum. By extending concepts from Domain-Driven Design, Hexagonal Architecture, and Clean Architecture, while introducing new mechanisms like Efficiency Gradients and Evolution Envelopes, CCA addresses challenges that traditional patterns struggle with.
For embedded systems, CCA allows critical paths to use direct hardware access while non-critical paths use higher abstractions. This balances real-time performance requirements with software engineering best practices. Resource contracts make resource usage explicit and manageable.
For enterprise systems, contract-based interaction enables independent deployment and scaling of capabilities. Evolution envelopes provide a formal mechanism for managing change over time. Support for modern technologies like AI, big data, and containerization is built into the architecture rather than added as an afterthought.
The architecture is practical to implement. Capabilities follow a clear structure that developers can consistently understand and apply. Testing strategies leverage the separation of Essence, Realization, and Adaptation to provide comprehensive coverage with fast, maintainable tests. Deployment flexibility allows the same capability code to run in different environments, from embedded devices to cloud platforms.
Capability-Centric Architecture represents an evolution in architectural thinking that synthesizes the best ideas from Domain-Driven Design, Hexagonal Architecture, and Clean Architecture while adding new mechanisms specifically designed to support both embedded and enterprise systems in the modern technological landscape. It is not a replacement for those patterns but rather an extension that makes them applicable to a broader spectrum of systems and challenges.
The pattern has been presented here with detailed examples and explanations to enable architects and developers to apply it to their own systems. While the examples use Java-like syntax for clarity, the concepts apply to any programming language and technology stack. The key is to follow the core principles: organize around capabilities, separate essence from realization, interact through contracts, use efficiency gradients appropriately, and plan for evolution from the start.
By following these principles, teams can build systems that are easier to understand, test, deploy, and evolve over time, whether those systems control industrial machines, process billions of transactions, or anything in between.
No comments:
Post a Comment