spring▌

This skill provides expert guide for testing Spring Boot 4 applications with modern patterns and best practices.

Production-ready AWS RDS configuration patterns for Spring Boot applications with Aurora, MySQL, and PostgreSQL. \n \n Supports Aurora MySQL, Aurora PostgreSQL, and standard MySQL/PostgreSQL with datasource configuration, HikariCP connection pooling, and SSL encryption \n Includes environment-specific profiles (dev/prod), Flyway database migrations, and read/write endpoint splitting for read-heavy workloads \n Provides security patterns using environment variables and AWS Secrets Manager integra

Spring Boot auto-configuration and declarative AI services for LangChain4j integration. \n \n Provides property-based configuration for multiple AI providers (OpenAI, Azure, Ollama) with Spring Boot starters and automatic bean wiring \n Enables interface-based AI service definitions using @AiService annotations combined with message templates and Spring dependency injection \n Supports RAG systems through configurable embedding stores (pgvector, Neo4j, Pinecone) and document ingestion pipelines

Distributed transaction management across microservices using choreography or orchestration patterns. \n \n Supports two saga approaches: choreography-based (event-driven, decoupled) and orchestration-based (centralized coordinator with easier tracking) \n Requires compensating transactions for every forward operation to ensure rollback capability and eventual consistency \n Integrates with Spring Boot 3.x, Kafka, RabbitMQ, and frameworks like Axon Framework, Eventuate Tram, and Camunda \n Empha

Event-Driven Architecture patterns for Spring Boot using domain events, transactional listeners, and Kafka messaging. \n \n Covers domain event design, ApplicationEventPublisher integration, and @TransactionalEventListener configuration for local event handling with AFTER_COMMIT phase guarantees \n Supports distributed messaging via Kafka and Spring Cloud Stream for inter-service communication with functional consumer beans \n Implements the transactional outbox pattern for reliable event publis

Spring Data Neo4j integration for graph databases with repositories, Cypher queries, and reactive operations. \n \n Three abstraction levels: Neo4j Client (low-level), Neo4j Template (medium-level), and Neo4j Repositories (high-level query derivation) \n Supports both imperative Neo4jRepository and reactive ReactiveNeo4jRepository patterns; do not mix both in the same application \n Entity mapping with @Node and @Relationship annotations, supporting business keys or generated IDs with immutable

Constructor-first dependency injection patterns for Spring Boot with optional collaborator handling and bean selection strategies. \n \n Prioritizes constructor injection to keep dependencies explicit, immutable, and testable without Spring context. \n Handles optional dependencies through guarded setters, ObjectProvider, and deterministic no-op defaults. \n Resolves bean ambiguity using @Primary, @Qualifier, profiles, and conditional annotations (@ConditionalOnProperty, @ConditionalOnMissingBea

Feature-aligned CRUD services for Spring Boot 3 with layered architecture and Spring Data JPA. \n \n Establishes feature packages with domain, application, presentation, and infrastructure layers to maintain architectural boundaries and DDD principles. \n Covers complete CRUD workflows: entity modeling with invariants, repository interfaces, JPA adapters, transactional services, DTO records, and REST controllers with proper HTTP status codes. \n Includes validation patterns using jakarta.validat

Build MCP servers with Spring AI using declarative tools, prompt templates, and native Spring integration patterns. \n \n Exposes Spring components as AI-callable tools via @Tool annotation, with parameter documentation through @ToolParam for AI model understanding \n Supports three transport modes (stdio, HTTP, SSE) with built-in Spring Security integration for role-based access control and audit logging \n Includes reusable prompt templates using @PromptTemplate , dynamic tool registration, mu

Persistence layer patterns for Spring Data JPA repositories, entities, queries, and advanced features. \n \n Create repository interfaces extending JpaRepository with derived queries, custom @Query methods, and automatic CRUD operations \n Configure entity relationships (one-to-one, one-to-many, many-to-many) with appropriate cascade types and fetch strategies \n Implement pagination, sorting, database auditing with timestamps and user tracking, and transaction management \n Optimize performance