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Add-Ons
RDS (Relational Database Service)

RDS (Relational Database Service)

Overview

RDS (Relational Database Service) provides managed PostgreSQL and MySQL databases for your application. Tapitalee automatically provisions Amazon RDS instances in your AWS account, handling database setup, backups, and maintenance.

Purpose and Benefits

  • Managed Database: Fully managed PostgreSQL or MySQL database with automated backups, patching, and monitoring
  • Scalability: Easy vertical scaling by changing instance size without data loss
  • High Availability: Optional Multi-AZ deployment for automatic failover
  • Security: Automatic encryption at rest and in transit, network isolation via VPC
  • Integration: Automatic environment variable injection for seamless app connectivity

CLI Usage

Create RDS Database 

tapit  create rds engine=<postgres|mysql> name=dbname [variable=DATABASE_URL] [storage=20] [version=14.4] [size=db.t4g.micro] [allowed_ip_ranges=0.0.0.0/0] [multi_az=false]

Required Parameters

  • engine: Database engine (postgres or mysql)
  • name: Database name (alphanumeric, used for RDS instance identifier)

Optional Parameters

  • variable: Environment variable name for connection URL (default: DATABASE_URL)
  • storage: Storage size in GB (default: 20)
  • version: Database version (default: latest supported version)
  • size: RDS instance class (default: db.t4g.micro)
  • allowed_ip_ranges: CIDR blocks allowed to connect (default: 0.0.0.0/0)
  • multi_az: Enable Multi-AZ deployment for high availability (default: false)

Examples 

# Basic PostgreSQL database
tapit create rds engine=postgres name=maindb

# MySQL with custom configuration
tapit create rds engine=mysql name=userdb variable=MYSQL_URL storage=100 size=db.t4g.small multi_az=true

# PostgreSQL with restricted access
tapit create rds engine=postgres name=proddb allowed_ip_ranges=10.0.0.0/16,172.16.0.0/12

Modify RDS Database 

tapit  set rds name=dbname [storage|size|allowed_ip_ranges|multi_az]=value

Modifiable Parameters

  • storage: Increase storage size (cannot decrease)
  • size: Change instance class (requires restart)
  • allowed_ip_ranges: Update network access rules
  • multi_az: Enable/disable Multi-AZ deployment

Examples 

# Scale up storage
tapit set rds name=maindb storage=200

# Upgrade instance class
tapit set rds name=maindb size=db.t4g.medium

# Enable high availability
tapit set rds name=maindb multi_az=true

List and Show RDS Instances 

# List all addons (including RDS)
tapit list addons

# Show specific RDS details
tapit show addon name=dbname

Delete RDS Database 

tapit delete addon name=dbname

Warning: This permanently deletes the database and all data. A final snapshot is automatically created before deletion.

Environment Variables

When you create an RDS database, Tapitalee automatically injects connection details as environment variables:

  • DATABASE_URL (or custom variable name): Complete connection string

Connection String Format

PostgreSQL:

postgres://username:password@hostname:5432/database_name

MySQL:

mysql://username:password@hostname:3306/database_name

Security Considerations

  • Network Isolation: RDS instances are deployed in private subnets
  • Encryption: Data encryption at rest and in transit is enabled by default
  • Access Control: Only your Tapitalee application containers have the password to access the containers.
  • Credentials: Database passwords are automatically generated and stored securely
  • IP Restrictions: Use allowed_ip_ranges to limit access to specific networks

Performance and Scaling

Instance Classes

  • t4g.micro: 2 vCPUs, 1 GB RAM - Development/testing
  • t4g.small: 2 vCPUs, 2 GB RAM - Small applications
  • t4g.medium: 2 vCPUs, 4 GB RAM - Medium workloads
  • m6g.large: 2 vCPUs, 8 GB RAM - Production workloads
  • r6i.large: 2 vCPUs, 16 GB RAM - Memory-intensive applications

Storage Scaling

  • Storage can be increased without downtime
  • Cannot decrease storage size once allocated

Multi-AZ Deployment

  • Provides automatic failover to a standby instance
  • Increases cost but improves availability
  • Recommended for production workloads
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