Provides dependency injection patterns for Spring Boot projects covering constructor-first patterns, optional collaborator handling, bean selection, and validation practices. Use when configuring beans, wiring dependencies, or troubleshooting injection issues.

Provides patterns for unit testing Spring Security with @PreAuthorize, @Secured, @RolesAllowed. Validates role-based access control and authorization policies. Use when testing security configurations and access control logic.

Edge case and boundary testing patterns for unit tests. Testing minimum/maximum values, null cases, empty collections, and numeric precision. Pure JUnit 5 unit tests. Use when ensuring code handles limits and special cases correctly.

Provides Qdrant vector database integration patterns with LangChain4j. Handles embedding storage, similarity search, and vector management for Java applications. Use when implementing vector-based retrieval for RAG systems, semantic search, or recommendation engines.

Provides patterns for testing Spring application events (ApplicationEvent) with @EventListener and ApplicationEventPublisher. Handles event publishing, listening, and async event handling in Spring Boot applications. Use when validating event-driven workflows in your Spring Boot services.

Provides patterns for unit testing service layer with Mockito. Validates business logic in isolation by mocking dependencies. Use when testing service behaviors and business logic without database or external services.

Provides patterns to build Retrieval-Augmented Generation (RAG) systems for AI applications with vector databases and semantic search. Use when implementing knowledge-grounded AI, building document Q&A systems, or integrating LLMs with external knowledge bases.

Provides parameterized testing patterns with @ParameterizedTest, @ValueSource, @CsvSource. Enables running a single test method with multiple input combinations. Use when testing multiple scenarios with similar logic.

Provides AWS CloudFormation patterns for DynamoDB tables, GSIs, LSIs, auto-scaling, and streams. Use when creating DynamoDB tables with CloudFormation, configuring primary keys, local/global secondary indexes, capacity modes (on-demand/provisioned), point-in-time recovery, encryption, TTL, and implementing template structure with Parameters, Outputs, Mappings, Conditions, cross-stack references.

Provides distributed transaction patterns using the Saga Pattern in Spring Boot microservices. Use when building microservices requiring transaction management across multiple services, handling compensating transactions, ensuring eventual consistency, or implementing choreography or orchestration-based sagas with Spring Boot, Kafka, or Axon Framework.

Provides Model Context Protocol (MCP) server implementation patterns with LangChain4j. Use when building MCP servers to extend AI capabilities with custom tools, resources, and prompt templates.

Provides patterns for enabling and operating the Spring Cache abstraction in Spring Boot. Use when implementing application-level caching for performance-sensitive workloads.

Provides configuration patterns for LangChain4J vector stores in RAG applications. Use when building semantic search, integrating vector databases (PostgreSQL/pgvector, Pinecone, MongoDB, Milvus, Neo4j), implementing embedding storage/retrieval, setting up hybrid search, or optimizing vector database performance for production AI applications.

Provides patterns for unit testing external REST APIs using WireMock to mock HTTP endpoints. Use when testing service integrations with external APIs.

Provides AWS CloudFormation patterns for Amazon Bedrock resources including agents, knowledge bases, data sources, guardrails, prompts, flows, and inference profiles. Use when creating Bedrock agents with action groups, implementing RAG with knowledge bases, configuring vector stores, setting up content moderation guardrails, managing prompts, orchestrating workflows with flows, and configuring inference profiles for model optimization.

Provides AWS CloudFormation patterns for Auto Scaling including EC2, ECS, and Lambda. Use when creating Auto Scaling groups, launch configurations, launch templates, scaling policies, lifecycle hooks, and predictive scaling. Covers template structure with Parameters, Outputs, Mappings, Conditions, cross-stack references, and best practices for high availability and cost optimization.

Provides AWS CloudFormation patterns for ECS clusters, services, and task definitions. Use when creating ECS infrastructure with CloudFormation, configuring container definitions, scaling policies, service discovery, load balancing integration, and implementing template structure with Parameters, Outputs, Mappings, Conditions, cross-stack references, and blue/green deployments with CodeDeploy.

Provides Spring Data Neo4j integration patterns for graph database development. Use when working with Neo4j graph databases, node entities, relationships, Cypher queries, reactive Neo4j operations, or Spring Data Neo4j repositories.

Provides AWS CloudFormation patterns for IAM users, roles, policies, and managed policies. Use when creating IAM resources with CloudFormation, implementing least privilege access, configuring cross-account access, setting up identity centers, managing permissions boundaries, and organizing template structure with Parameters, Outputs, Mappings, Conditions for secure infrastructure deployments.

Provides patterns for unit testing utility/helper classes and static methods. Validates pure functions and helper logic. Use when verifying utility code correctness.