Aws Rds Spring Boot Integration logo

Aws Rds Spring Boot Integration

Community
giuseppe-trisciuoglio
aws-rds-spring-boot-integration

Provides patterns to configure AWS RDS (Aurora, MySQL, PostgreSQL) with Spring Boot applications. Configures HikariCP connection pools, implements read/write splitting, sets up IAM database authentication, enables SSL connections, and integrates with AWS Secrets Manager. Use when setting up RDS connections in Spring Boot, configuring connection pooling, or managing database credentials securely.

Overview

Publishergiuseppe-trisciuoglio
Repositorydeveloper-kit
Skill nameaws-rds-spring-boot-integration
Stars
345
Forks
41
Bundled files
2
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by giuseppe-trisciuoglio on GitHub. Read the source before you install it.

Installation

Install the Aws Rds Spring Boot Integration AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/giuseppe-trisciuoglio/developer-kit.git /tmp/developer-kit
mkdir -p .claude/skills
cp -r /tmp/developer-kit/plugins/developer-kit-java/skills/aws-rds-spring-boot-integration .claude/skills/aws-rds-spring-boot-integration
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Aws Rds Spring Boot Integration in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Aws Rds Spring Boot Integration on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Aws Rds Spring Boot Integration is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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 detection and configure timeouts for failover scenarios
  • Security: Enable SSL/TLS; use IAM Database Authentication when possible
  • Performance: Disable open-in-view; use appropriate indexing and batch operations
  • Monitoring: Enable Spring Boot Actuator with database health checks

Testing

Verify connectivity with this health check endpoint:

java
@RestController
@RequestMapping("/api/health")
public class DatabaseHealthController {
    @Autowired
    private DataSource dataSource;

    @GetMapping("/db-connection")
    public ResponseEntity<Map<String, Object>> testDatabaseConnection() {
        Map<String, Object> response = new HashMap<>();
        try (Connection connection = dataSource.getConnection()) {
            response.put("status", "success");
            response.put("database", connection.getCatalog());
            response.put("connected", true);
            return ResponseEntity.ok(response);
        } catch (Exception e) {
            response.put("status", "failed");
            response.put("error", e.getMessage());
            response.put("connected", false);
            return ResponseEntity.status(HttpStatus.SERVICE_UNAVAILABLE).body(response);
        }
    }
}
bash
curl http://localhost:8080/api/health/db-connection

Support

For detailed troubleshooting and advanced configuration, refer to:

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Aws Rds Spring Boot Integration AI skill do?

Provides patterns to configure AWS RDS (Aurora, MySQL, PostgreSQL) with Spring Boot applications. Configures HikariCP connection pools, implements read/write splitting, sets up IAM database authentication, enables SSL connections, and integrates with AWS Secrets Manager. Use when setting up RDS connections in Spring Boot, configuring connection pooling, or managing database credentials securely.

Why use Aws Rds Spring Boot Integration on TypingMind?

Because you install it once and use it with any model. Aws Rds Spring Boot Integration is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Aws Rds Spring Boot Integration in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/giuseppe-trisciuoglio/developer-kit/tree/main/plugins/developer-kit-java/skills/aws-rds-spring-boot-integration. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Aws Rds Spring Boot Integration?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Aws Rds Spring Boot Integration?

As many as you like. As long as a model supports skills, you can use Aws Rds Spring Boot Integration with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Aws Rds Spring Boot Integration AI skill free?

Yes. It is published on GitHub by giuseppe-trisciuoglio under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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