In Amazon S3, Lifecycle Management allows you to automate actions on objects over time, helping to manage costs and optimize data storage. With Lifecycle rules, you can automatically transition objects to more cost-effective storage classes or even delete them when they’re no longer needed. Here’s how it works:

Bucket/Object Lifecycle Concepts

1. Lifecycle Rules

• Purpose: Lifecycle rules define automated actions (like transition or deletion) that apply to objects in a bucket over their lifetimes.
• Scope: Rules can apply to all objects in a bucket or a subset defined by a prefix (like folders) or tags.

2. Transitions

• What They Are: Transitions move objects to different storage classes over time.
• How They Work:
  • You can configure an object to move from Standard to Standard-IA (Infrequent Access) after a certain period.
  • Further transitions could send it to Glacier or Deep Archive for long-term, lower-cost storage.
• Use Case: Transitioning is best for objects that you expect to access less frequently over time, like logs or backup files.

3. Expiration

• What It Is: Expiration automatically deletes objects based on their age.
• How It Works: You set a rule to delete objects after a certain number of days or based on custom criteria.
• Use Case: Useful for managing temporary files, outdated backups, or log files, helping to reduce storage costs over time.

Lifecycle Example

Suppose you have daily logs stored in your S3 bucket, and you only need recent logs frequently. You can set up a Lifecycle policy:

• Days 0–30: Keep in Standard storage for fast access.
• Day 31: Transition to Standard-IA for occasional access.
• Day 180: Move to Glacier for archival.
• Day 365: Expire (delete) the logs to save space.

Best Practices for S3 Lifecycle Management