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

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 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 integration patterns for LangChain4j with Spring Boot. Handles auto-configuration, dependency injection, and Spring ecosystem integration. Use when embedding LangChain4j into Spring Boot applications.

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 patterns to deploy ECS tasks and services with GitHub Actions CI/CD. Use when building Docker images, pushing to ECR, updating ECS task definitions, deploying ECS services, integrating with CloudFormation stacks, configuring AWS OIDC authentication for GitHub Actions, and implementing production-ready container deployment pipelines. Supports ECS deployments with proper security (OIDC or IAM keys), multi-environment support, blue/green deployments, ECR private repositories with image scanning, and CloudFormation infrastructure updates.

Provides comprehensive React 19 patterns covering Server Components, Actions, use() hook, useOptimistic, useFormStatus, useFormState, React Compiler, concurrent features, Suspense, and modern TypeScript development. Proactively use for any React development, component architecture, state management, performance optimization, or when implementing React 19's latest features.

Provides AWS CloudFormation patterns for VPC infrastructure. Use when creating VPCs, Subnets, Route Tables, NAT Gateways, Internet Gateways, and implementing template structure with Parameters, Outputs, Mappings, Conditions, and cross-stack references.

Provides AWS CloudFormation patterns for Amazon RDS databases. Use when creating RDS instances (MySQL, PostgreSQL, Aurora), DB clusters, multi-AZ deployments, parameter groups, subnet groups, and implementing template structure with Parameters, Outputs, Mappings, Conditions, and cross-stack references.

Provides Model Context Protocol (MCP) server implementation patterns with Spring AI. Use when building MCP servers to extend AI capabilities with custom tools, resources, and prompt templates using Spring's official AI framework.

Provides AWS CloudFormation patterns for infrastructure security, secrets management, encryption, and secure data handling. Use when creating secure CloudFormation templates with AWS Secrets Manager, KMS encryption, secure parameters, IAM policies, VPC security groups, TLS/SSL certificates, and encrypted traffic configurations. Covers template structure, parameter best practices, cross-stack references, and defense-in-depth strategies.

Provides patterns for unit testing REST controllers using MockMvc and @WebMvcTest. Validates request/response mapping, validation, and exception handling. Use when testing web layer endpoints in isolation.

Provides patterns for unit testing @ConfigurationProperties classes with @ConfigurationPropertiesTest. Use when validating application configuration binding and validation.

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

Provides patterns for unit testing @ExceptionHandler and @ControllerAdvice for global exception handling. Use when validating error response formatting and HTTP status codes.

Provides AWS CloudFormation patterns for Amazon S3. Use when creating S3 buckets, policies, versioning, lifecycle rules, and implementing template structure with Parameters, Outputs, Mappings, Conditions, and cross-stack references.

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.