Amazon RDS Proxy and MariaDB Integration

Learn how to build a Python-based AWS Lambda function integrated with Amazon RDS Proxy and MariaDB for secure, scalable CRUD operations via API Gateway using AWS Secrets Manager.We’ll also explore best practices like using AWS Secrets Manager for secure credential storage.

Introduction

When building serverless applications, connecting AWS Lambda functions directly to Amazon RDS can be inefficient and insecure if not handled properly. Every cold start may create a new connection, potentially overwhelming the database. That’s where Amazon RDS Proxy comes into play—it allows efficient pooling and management of database connections while integrating seamlessly with AWS Lambda.

In this blog, we’ll walk through a Python-based AWS Lambda function that integrates with Amazon RDS Proxy and MariaDB to perform stateless CRUD operations via API Gateway. We’ll also explore best practices like using AWS Secrets Manager for secure credential storage.

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Why Use RDS Proxy with Lambda?

• Connection pooling: Avoids opening too many direct DB connections.

• Improved scalability: Manages spikes in database requests.

• Enhanced security: Works natively with AWS Secrets Manager.

• Better availability: Supports automatic failover with Multi-AZ RDS.

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Environment Setup

Before diving into the code, ensure you have:

1. An Amazon RDS (MariaDB) instance.

2. An RDS Proxy configured to connect to the RDS instance.

3. A secret in AWS Secrets Manager containing database credentials.

4. Environment variables set in Lambda:

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Why Use RDS Proxy with Lambda?

• Connection pooling: Avoids opening too many direct DB connections.

• Improved scalability: Manages spikes in database requests.

• Enhanced security: Works natively with AWS Secrets Manager.

• Better availability: Supports automatic failover with Multi-AZ RDS.

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Environment Setup

Before diving into the code, ensure you have:

1. An Amazon RDS (MariaDB) instance.

2. An RDS Proxy configured to connect to the RDS instance.

3. A secret in AWS Secrets Manager containing database credentials.

4. Environment variables set in Lambda:

5. This Lambda function provides CRUD (Create, Read, Update, Delete) APIs for a users table.

6.  DB_SECRET_NAME=mydb-secret
    DB_PROXY_ENDPOINT=mydb.proxy.amazonaws.com 
    DB_NAME=customerdb DB_TABLE=users
   

7. Key components:

   Secrets Manager → Securely fetch DB credentials.

   RDS Proxy → Efficient DB connection pooling.

   API Gateway → Acts as the HTTP interface for CRUD requests.

    def get_db_connection():
        global db_connection
        if db_connection and db_connection.open:
            return db_connection
   
        creds = get_db_credentials()
        db_connection = pymysql.connect(
            host=DB_PROXY_ENDPOINT,
            user=creds["username"],
            password=creds["password"],
            db=DB_NAME,
            connect_timeout=5,
            cursorclass=pymysql.cursors.DictCursor,
        )
        return db_connection
   

   Connections are reused to minimize cold start impact.

   

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   3. Handling CRUD Requests

   • GET → Retrieve a user.

   • POST → Create a new user.

   • PUT → Update user details.

   • DELETE → Remove a user.

Example:

    def handle_post(conn, body):
        name = body.get("name")
        email = body.get("email")
        with conn.cursor() as cursor:
            cursor.execute(f"INSERT INTO `{DB_TABLE}` (name, email) VALUES (%s, %s)", (name, email))
            conn.commit()
        return build_response(201, {"id": conn.insert_id(), "message": "User created"})

Testing via API Gateway:

1. Deploy the Lambda via API Gateway.

2. Test using POST /users with a JSON body:

    { "name": "Alice", "email": "alice@example.com" }
    { "id": 1, "message": "User created" }

8. Conclusion:

   By integrating AWS Lambda with Amazon RDS Proxy and MariaDB, you can build secure, stateless, and scalable serverless applications. This approach minimizes database connection overhead, ensures secure credential management via AWS Secrets Manager, and supports high-concurrency CRUD operations with ease.