This project demonstrates the implementation of Amazon S3 Lifecycle policies to automatically transition objects between storage classes and delete data after a defined period. The goal is to optimize storage costs while maintaining data availability.
- Amazon S3
- S3 Lifecycle Rules
- S3 Storage Classes (Standard, Standard-IA, Glacier)
- IAM (for access control)
- Objects are stored in an S3 bucket
- Lifecycle rules manage object transitions based on age
- Older data is moved to lower-cost storage classes
- Expired data is automatically deleted
- Created an S3 bucket with a unique name
- Enabled versioning (optional)
- Navigated to the Management tab of the S3 bucket
- Created a new lifecycle rule
- Applied rule to the entire bucket or specific object prefix
- Transition objects to S3 Standard-IA after 30 days
- Transition objects to S3 Glacier after 90 days
- Permanently delete objects after 180 days
- Expire non-current object versions (if versioning enabled)
- Reviewed lifecycle rule configuration
- Enabled the rule to start automated data management
- Uploaded sample objects to the S3 bucket
- Verified lifecycle rule configuration
- Confirmed objects transitioned according to defined policies
- Automated data lifecycle management implemented
- Storage costs reduced by transitioning data to lower-cost tiers
- No manual intervention required for data cleanup
- Understanding S3 storage classes and lifecycle policies
- Automating data transitions and expiration
- Cost optimization using AWS managed services
- Managing versioned objects with lifecycle rules