AWS CLI command to set backup retention period

In the previous article, we discussed AWS storage services—specifically Amazon Glacier for cold storage. Glacier is ideal for long-term archival of infrequently accessed data. However, many applications require a fast, scalable database solution to support real-time data access and transaction processing. Today, we’ll dive deep into AWS’s relational database service: Amazon RDS (Relational Database Service).

What Is Amazon RDS?

Amazon RDS is a managed service that simplifies database administration. It supports several popular database engines, including:

• MySQL
• PostgreSQL
• MariaDB
• Oracle
• Microsoft SQL Server

With Amazon RDS, you can rapidly deploy and manage relational databases without worrying about underlying hardware or software maintenance.

Key Features

1. Automated Management

RDS automates numerous administrative tasks, such as:

• Automated Backups: You can configure a backup window; RDS automatically backs up your database to Amazon S3 and supports point-in-time recovery.
• Monitoring and Alerting: Integrated with Amazon CloudWatch, RDS enables performance monitoring and customizable alarm notifications.

2. Scalability

RDS allows seamless scaling of database instance performance and storage capacity. You can scale vertically (by upgrading instance class) or horizontally (by adding read replicas), either via the AWS Management Console or programmatically through the AWS API.

3. High Availability

By enabling Multi-AZ deployment, Amazon RDS automatically replicates data across multiple Availability Zones. In case of primary instance failure, RDS performs automatic failover to ensure minimal downtime.

4. Security

RDS provides layered security mechanisms, including VPC security groups, encrypted storage (at rest and in transit), and IAM-based authentication.

Real-World Use Cases for RDS

Use Case 1: User Data Management for an E-Commerce Website

Suppose you’re building an e-commerce platform requiring persistent storage for user profiles and transaction records. RDS with MySQL delivers ACID-compliant transactions and robust support for complex queries.

CREATE TABLE Users (
    UserID INT AUTO_INCREMENT PRIMARY KEY,
    UserName VARCHAR(255) NOT NULL,
    Email VARCHAR(255) NOT NULL UNIQUE
);

CREATE TABLE Orders (
    OrderID INT AUTO_INCREMENT PRIMARY KEY,
    UserID INT,
    ProductID INT,
    OrderDate TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
    FOREIGN KEY (UserID) REFERENCES Users(UserID)
);

Here, two tables—Users and Orders—model core business entities. This relational structure ensures efficient retrieval of all orders associated with a given user.

Use Case 2: Integration with Backup and Monitoring

In production environments, data durability and operational continuity are critical. For example, on an e-commerce platform, you can configure automated backups and CloudWatch monitoring for your RDS instance.

# AWS CLI command to set backup retention period
aws rds modify-db-instance --db-instance-identifier mydbinstance --backup-retention-period 7

This command configures RDS to retain automated backups for seven days—enabling reliable recovery when needed.

Getting Started with Amazon RDS

You can launch an RDS instance using either the AWS Management Console or the AWS CLI. Below is an example CLI command to create a MySQL database instance:

aws rds create-db-instance \
    --db-instance-identifier mydbinstance \
    --db-instance-class db.t3.micro \
    --engine mysql \
    --master-username admin \
    --master-user-password yourpassword \
    --allocated-storage 20 \
    --backup-retention-period 7 \
    --vpc-security-group-ids sg-12345678

This command specifies key parameters: instance identifier, instance class, database engine (MySQL), master credentials, allocated storage (20 GB), backup retention period (7 days), and associated VPC security group.

Summary

In this article, we explored Amazon RDS—the AWS-managed relational database service—covering its core features, practical use cases, and initial setup steps. With RDS, developers and operators gain operational efficiency, allowing them to focus on application logic rather than infrastructure management.

In the next article, we’ll explore Amazon DynamoDB, AWS’s fully managed NoSQL database service, and examine how it delivers flexibility and power for unstructured and semi-structured data workloads. Stay tuned for more in-depth AWS cloud service tutorials!