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S3 Storage Class Recommendations

AWS S3 offers various storage classes, each optimized for different use cases and cost structures. By periodically reviewing and optimizing the storage class of your S3 objects, you can significantly reduce storage costs without impacting data accessibility. This script analyzes S3 objects and recommends more cost-effective storage classes based on object age and access patterns.

Benefits of Storage Class Optimization

  1. Cost Savings: Moving objects to cheaper storage classes based on access frequency and age can reduce monthly storage costs.
  2. Improved Resource Management: Optimizing storage classes helps align storage spending with actual data usage patterns.
  3. Data Lifecycle Management: Implementing storage class recommendations can support data lifecycle policies by automating the transition of data to cheaper, long-term storage.

Storage Class Pricing (Per GB/Month)

  • STANDARD: $0.023
  • STANDARD_IA: $0.0125
  • ONEZONE_IA: $0.01
  • GLACIER: $0.004
  • DEEP_ARCHIVE: $0.00099

Optimization Strategy

Analyzing Buckets and Objects

  • Objective: Analyze a sample of objects within each S3 bucket to identify opportunities for storage class optimization.
  • Method: For each object, check its current storage class, last modified date, and size. Based on these attributes, suggest a more cost-effective storage class if applicable.

Storage Class Recommendations

  1. STANDARD objects older than 90 days are candidates for transitioning to:
  2. STANDARD_IA if older than 90 days but less than a year.

  3. GLACIER if older than one year.

  4. STANDARD_IA objects older than 180 days may be transitioned to:

  5. GLACIER for deeper archival storage.

These recommendations are based on object age and intended access patterns, with the goal of balancing cost and accessibility.

Calculating Potential Savings

For each suggested storage class change: - Calculate the current monthly cost based on the object’s size and its existing storage class. - Calculate the suggested monthly cost using the recommended storage class. - Potential savings are the difference between the current cost and suggested cost, giving an estimate of cost reduction for each object.

Implementation Strategy

  1. Sampling and Analysis: Sample a subset of objects in each bucket to estimate overall optimization potential. This script defaults to analyzing 20% of objects in each bucket, up to a maximum of 50 objects.
  2. Automated Execution: Use a thread pool to analyze multiple buckets concurrently, improving efficiency for large S3 environments.
  3. Review and Implement Recommendations: After generating recommendations, review them for accuracy and potential impact, then implement transitions either manually or through automated lifecycle policies.

By regularly reviewing and adjusting S3 storage classes, you can ensure a cost-effective data storage strategy that aligns with the access needs of your data.