Amazon DynamoDB – Consider Using TTL on Tables

DynamoDB tables can accumulate data over time, leading to unnecessary storage costs and potential performance impacts. Time-to-Live (TTL) provides an automated mechanism to remove expired or unnecessary items, helping organizations optimize their database storage and reduce unnecessary expenses.

Why This Policy Matters

TTL is a critical cost optimization strategy for DynamoDB that offers several key benefits:

• Automated Data Cleanup: Automatically remove outdated items without manual intervention
• Cost Reduction: Significantly lower storage expenses by removing unnecessary data
• Performance Optimization: Prevent table bloat and maintain efficient query performance

Cost Impact Analysis

Consider a typical scenario:

• Initial Table Size: 200GB
• Daily Data Growth: 2GB
• Annual Storage Without TTL:
  • Monthly Cost: ~$230
• With 30-Day TTL Implementation:
  • Monthly Cost: ~$15
  • Potential Savings: Over 93% on storage costs

Implementation Guide

Infrastructure as Code Example (Terraform)

resource "aws_dynamodb_table" "example" {
  name           = "user-sessions"
  billing_mode   = "PAY_PER_REQUEST"
 
  # TTL Configuration
  ttl {
    attribute_name = "expires_at"
    enabled        = true
  }

  attribute {
    name = "session_id"
    type = "S"
  }

  attribute {
    name = "expires_at"
    type = "N"
  }
}

Manual Implementation Steps

1. Enable TTL in DynamoDB Console
2. Select an expiration attribute (typically a Unix timestamp)
3. Configure attribute mapping
4. Validate TTL settings

Best Practices

• Choose Appropriate Expiration Time: Align with data retention requirements
• Use Numeric Timestamp: Prefer Unix epoch time
• Monitor TTL Deletion: Track deleted items via CloudWatch metrics
• Test Before Production: Validate TTL behavior in staging environments

Recommended Tools

• Infracost: Automatically detect and recommend TTL configurations
• AWS Cost Explorer: Validate storage cost reductions
• CloudWatch: Monitor TTL deletion processes

Practical Examples

Scenario 1: User Session Management

• Use Case: Web application user sessions
• TTL Setting: 24-hour expiration
• Potential Savings: Prevents accumulation of inactive session data

Scenario 2: Temporary Data Caching

• Use Case: Transient analytics data
• TTL Setting: 7-day retention
• Benefit: Automatic cleanup of stale analytical records

Considerations and Caveats

• Data Dependency: Ensure no critical historical data is lost
• Deletion Timing: TTL deletions occur within 48 hours of expiration
• Performance Impact: Minimal overhead during deletion process

When to Avoid TTL

• Archival tables requiring complete historical preservation
• Compliance scenarios with strict data retention mandates
• Tables with complex interdependent data relationships

Frequently Asked Questions (FAQs)