aws-rds-spring-boot-integration
This Claude Code skill provides configuration patterns for integrating AWS RDS databases (Aurora, MySQL, PostgreSQL) with Spring Boot applications. It covers HikariCP connection pooling, read/write splitting with Aurora replicas, IAM database authentication, SSL/TLS encryption, AWS Secrets Manager integration, and Flyway migration management. Use when establishing RDS connections in Spring Boot, optimizing connection pools, securing database credentials, or troubleshooting database connectivity issues.
git clone --depth 1 https://github.com/giuseppe-trisciuoglio/developer-kit /tmp/aws-rds-spring-boot-integration && cp -r /tmp/aws-rds-spring-boot-integration/plugins/developer-kit-java/skills/aws-rds-spring-boot-integration ~/.claude/skills/aws-rds-spring-boot-integrationSKILL.md
# AWS RDS Spring Boot Integration
## Overview
Configure AWS RDS databases (Aurora, MySQL, PostgreSQL) with Spring Boot applications. Provides patterns for datasource configuration, HikariCP connection pooling, SSL connections, environment-specific configurations, and AWS Secrets Manager integration.
## When to Use
Use when configuring HikariCP connection pools for RDS workloads, implementing read/write split with Aurora replicas, setting up IAM database authentication, enabling SSL/TLS connections, managing database migrations with Flyway, or troubleshooting RDS connectivity issues.
## Instructions
Follow these steps to configure AWS RDS with Spring Boot:
1. **Add Dependencies** — Include Spring Data JPA, database driver (MySQL/PostgreSQL), and Flyway
2. **Configure Datasource** — Set connection properties in application.yml
3. **Configure HikariCP** — Optimize pool settings for your RDS workload
4. **Set Up SSL** — Enable encrypted connections to RDS
5. **Configure Profiles** — Set environment-specific configurations (dev/prod)
6. **Add Migrations** — Create Flyway scripts for schema management
7. **Validate Connectivity** — Run health check to verify database connection
**If validation fails**: Check security group rules, verify credentials, ensure RDS is accessible from your network, and confirm SSL certificate configuration.
8. **Run Migrations** — Apply Flyway migrations only after connectivity validation passes
## Quick Start
### Step 1: Add Dependencies
**Maven (pom.xml):**
```xml
<dependencies>
<!-- Spring Data JPA -->
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-data-jpa</artifactId>
</dependency>
<!-- Aurora MySQL Driver -->
<dependency>
<groupId>com.mysql</groupId>
<artifactId>mysql-connector-j</artifactId>
<version>8.2.0</version>
<scope>runtime</scope>
</dependency>
<!-- Aurora PostgreSQL Driver (alternative) -->
<dependency>
<groupId>org.postgresql</groupId>
<artifactId>postgresql</artifactId>
<scope>runtime</scope>
</dependency>
<!-- Flyway for database migrations -->
<dependency>
<groupId>org.flywaydb</groupId>
<artifactId>flyway-core</artifactId>
</dependency>
<!-- Validation -->
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-validation</artifactId>
</dependency>
</dependencies>
```
**Gradle (build.gradle):**
```gradle
dependencies {
implementation 'org.springframework.boot:spring-boot-starter-data-jpa'
implementation 'org.springframework.boot:spring-boot-starter-validation'
// Aurora MySQL
runtimeOnly 'com.mysql:mysql-connector-j:8.2.0'
// Aurora PostgreSQL (alternative)
runtimeOnly 'org.postgresql:postgresql'
// Flyway
implementation 'org.flywaydb:flyway-core'
}
```
### Step 2: Basic Datasource Configuration
Use the configuration in the **Examples** section below. For PostgreSQL, change:
- Driver: `org.postgresql.Driver`
- URL: `jdbc:postgresql://...` with `?ssl=true&sslmode=require`
- Dialect: `org.hibernate.dialect.PostgreSQLDialect`
### Step 3: Set Up Environment Variables
```bash
# Production environment variables
export DB_PASSWORD=YourStrongPassword123!
export SPRING_PROFILES_ACTIVE=prod
# For development
export SPRING_PROFILES_ACTIVE=dev
```
## Database Migration Setup
Create migration files for Flyway:
```
src/main/resources/db/migration/
├── V1__create_users_table.sql
├── V2__add_phone_column.sql
└── V3__create_orders_table.sql
```
**V1__create_users_table.sql:**
```sql
CREATE TABLE users (
id BIGINT AUTO_INCREMENT PRIMARY KEY,
name VARCHAR(100) NOT NULL,
email VARCHAR(255) NOT NULL UNIQUE,
created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
INDEX idx_email (email)
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;
```
## Examples
### Example 1: Aurora MySQL Configuration
```yaml
spring:
datasource:
url: jdbc:mysql://myapp-aurora-cluster.cluster-abc123xyz.us-east-1.rds.amazonaws.com:3306/devops
username: admin
password: ${DB_PASSWORD}
driver-class-name: com.mysql.cj.jdbc.Driver
hikari:
maximum-pool-size: 20
minimum-idle: 5
connection-timeout: 20000
jpa:
hibernate:
ddl-auto: validate
open-in-view: false
```
### Example 2: Aurora PostgreSQL with SSL
```properties
spring.datasource.url=jdbc:postgresql://myapp-aurora-pg-cluster.cluster-abc123xyz.us-east-1.rds.amazonaws.com:5432/devops?ssl=true&sslmode=require
spring.datasource.username=${DB_USERNAME}
spring.datasource.password=${DB_PASSWORD}
spring.datasource.hikari.maximum-pool-size=30
spring.jpa.properties.hibernate.dialect=org.hibernate.dialect.PostgreSQLDialect
```
### Example 3: Read/Write Split Configuration
```java
@Configuration
public class DataSourceConfiguration {
@Bean
@Primary
public DataSource dataSource(
@Qualifier("writerDataSource") DataSource writerDataSource,
@Qualifier("readerDataSource") DataSource readerDataSource) {
Map<Object, Object> targetDataSources = new HashMap<>();
targetDataSources.put("writer", writerDataSource);
targetDataSources.put("reader", readerDataSource);
RoutingDataSource routingDataSource = new RoutingDataSource();
routingDataSource.setTargetDataSources(targetDataSources);
routingDataSource.setDefaultTargetDataSource(writerDataSource);
return routingDataSource;
}
}
```
## Constraints and Warnings
- HikariCP pool size must respect RDS instance connection limits
- Security groups must allow traffic from your application's IP range
- Use AWS Secrets Manager instead of hardcoding credentials
- Enable storage autoscaling to prevent storage exhaustion
## Best Practices
- **HikariCP**: Enable leak detectioProvides chunking strategies for RAG systems. Generates chunk size recommendations (256-1024 tokens), overlap percentages (10-20%), and semantic boundary detection methods. Validates semantic coherence and evaluates retrieval precision/recall metrics. Use when building retrieval-augmented generation systems, vector databases, or processing large documents.
>
Implements document chunking, embedding generation, vector storage, and retrieval pipelines for Retrieval-Augmented Generation systems. Use when building RAG applications, creating document Q&A systems, or integrating AI with knowledge bases.
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 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 CloudFront distributions, origins (ALB, S3, Lambda@Edge, VPC Origins), CacheBehaviors, Functions, SecurityHeaders, parameters, Outputs and cross-stack references. Use when creating CloudFront distributions with CloudFormation, configuring multiple origins, implementing caching strategies, managing custom domains with ACM, configuring WAF, and optimizing performance.
Provides AWS CloudFormation patterns for CloudWatch monitoring, metrics, alarms, dashboards, logs, and observability. Use when creating CloudWatch metrics, alarms, dashboards, log groups, log subscriptions, anomaly detection, synthesized canaries, Application Signals, and implementing template structure with Parameters, Outputs, Mappings, Conditions, cross-stack references, and CloudWatch best practices for monitoring production infrastructure.
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.