Expert guidance for developing and maintaining a Spring Boot microservice that uses Drools rule engine for AI-enhanced dynamic pricing evaluation with PostgreSQL, Redis caching, and comprehensive financial metrics processing.
Expert assistant for working with a Spring Boot microservice that integrates Drools rule engine for dynamic pricing rule evaluation with AI-enhanced optimization.
This skill provides comprehensive guidance for developing, testing, and maintaining a microservice solution that uses Drools for pricing rules evaluation. It covers the full technology stack including Java 21, Spring Boot 3.4.5, Drools 8.47.0.Final, PostgreSQL, Redis, and AI integration for rule optimization.
1. **Rule Engine Integration**
- `DroolsIntegrationService`: Rule deployment, validation, and execution
- Uses KIE (Knowledge Is Everything) APIs
- Implements caching for performance optimization
2. **Financial Metrics Processing**
- `FinancialMetricsService`: Calculates ARR, TCV, ACV, CLV
- `PricingService`: Applies pricing strategies based on metrics
3. **AI-Enhanced Services**
- `SequentialThinkingService`: AI-driven analysis and decision making
- `Context7Service`: Documentation enhancement integration
- `RuleCreationService`: AI-assisted rule generation and optimization
4. **Data Model**
- `FinancialMetrics`: Core financial calculations entity
- `PricingRequest` / `PricingResult`: Pricing operation DTOs
5. **Security Layer**
- JWT-based authentication
- Role-based access control
**Clean and build:**
```bash
mvn clean install
```
**Skip tests during build:**
```bash
mvn clean install -DskipTests
```
**Run application locally:**
```bash
mvn spring-boot:run
```
**Run with specific profile (dev/test/prod):**
```bash
mvn spring-boot:run -Dspring.profiles.active=dev
```
**Execute all tests:**
```bash
mvn test
```
**Run specific test class:**
```bash
mvn test -Dtest=TestClassName
```
**Run specific test method:**
```bash
mvn test -Dtest=TestClassName#testMethodName
```
**Generate coverage report with JaCoCo:**
```bash
mvn clean verify
```
**View coverage report:**
```bash
open target/site/jacoco/index.html
```
**Build Docker image:**
```bash
docker build -t price-dools-service -f docker/Dockerfile .
```
**Run container with basic configuration:**
```bash
docker run -p 8080:8080 price-dools-service
```
**Run with full environment configuration:**
```bash
docker run -p 8080:8080 \
-e SPRING_PROFILES_ACTIVE=prod \
-e JDBC_DATABASE_URL=jdbc:postgresql://host:5432/dbname \
-e JDBC_DATABASE_USERNAME=username \
-e JDBC_DATABASE_PASSWORD=password \
-e REDIS_HOST=redis-host \
-e REDIS_PORT=6379 \
-e REDIS_PASSWORD=redispassword \
-e JWT_SECRET=yoursecret \
price-dools-service
```
The application uses **PostgreSQL** with **Liquibase** for schema management. Key tables:
Database migrations are automatically applied on startup via Liquibase changesets.
**Rule file location:**
```
src/main/resources/rules/
```
**Rule file format:** DRL (Drools Rule Language)
**Best practices for rules:**
**Rule Management** (`/api/rules`)
**Pricing Evaluation** (`/api/pricing`)
**AI-Enhanced Rule Creation** (`/api/ai/rules`)
**Authentication** (`/api/auth`)
**Monitoring** (`/api/actuator`)
The application supports three profiles:
Configuration files:
**Service Layer:**
**Controllers:**
**Testing:**
**Rule Files:**
```java
@Service
@RequiredArgsConstructor
public class SomeServiceImpl implements SomeService {
private final SomeDependency dependency;
@Transactional
public Result performOperation(Request request) {
// Implementation
}
}
```
1. Load rule set from database or file system
2. Validate rules using Drools validator
3. Deploy to KIE container with caching
4. Execute rules against facts
5. Collect results and audit trail
6. Return pricing decisions
1. Analyze business requirements using Sequential Thinking
2. Generate rule candidates with AI assistance
3. Validate generated rules against Drools syntax
4. Test rules with sample data
5. Deploy optimized rules to production
Access application metrics via `/api/actuator` endpoints:
Prometheus-compatible metrics are exposed for integration with monitoring systems.
**Adding a new rule:**
1. Create DRL file in `src/main/resources/rules/`
2. Define rule conditions and consequences
3. Validate syntax using DroolsIntegrationService
4. Test with sample data
5. Deploy via rule management API
**Implementing a new pricing strategy:**
1. Extend FinancialMetrics or create new entity
2. Add calculation logic to FinancialMetricsService
3. Update PricingService with new strategy
4. Create corresponding Drools rules
5. Add integration tests
**Optimizing rule performance:**
1. Review rule execution metrics in actuator
2. Analyze rule salience and agenda ordering
3. Optimize fact insertion and pattern matching
4. Leverage Redis caching for frequently used rule sets
5. Use AI analysis via SequentialThinkingService for recommendations
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