S3 to Glacier transfer cost: what to include in the move

Moving data from S3 to Glacier is usually cheap, but the workflow can create extra costs. Use this checklist to model transition requests, minimum duration rules, and any transfer overhead.

What to include in the transfer cost

• Transition requests: lifecycle transitions and batch operations often have per-request fees.
• Minimum storage duration: early deletion can create fees that erase savings.
• Cross-region moves: transfers across regions can incur data transfer charges.
• Rewrites or re-uploads: data repackaging can double-write costs.

Estimate the transition request volume

• Count objects to transition (requests track object count).
• Batch operations still count as per-object requests for cost.
• If you have many small objects, request fees can be meaningful.

Check minimum duration rules before migrating

• Archive tiers have minimum storage duration requirements.
• Short-lived objects can trigger early deletion charges.
• If your data changes frequently, reconsider moving it to archive tiers.

Plan a migration window

• Stagger transitions to avoid large spikes in retrieval or lifecycle activity.
• Track restore needs before moving data to a slower tier.
• Validate a small sample before full migration.

Simple cost model (use before migration)

• Transition requests = objects transitioned x $ per 1,000 requests.
• Storage delta = (current GB-month - archive GB-month) x months retained.
• Early deletion risk = objects deleted before minimum duration x remaining months.

The goal is to ensure the storage savings exceed the transition and early deletion penalties.

Example: lifecycle migration for log archives

If you move 50 TB of logs into Glacier and keep them for 12 months, the storage savings are large. But if 20% of those objects are re-written or deleted within the minimum duration window, early deletion fees can offset a big chunk of the expected savings. Validate object churn first.

Validation checklist

• Measure object count and average object size (requests scale with count).
• Confirm lifecycle rules do not transition hot or frequently rewritten data.
• Estimate restore frequency (audit or reprocessing jobs) before moving data.
• Run a small pilot and compare the first bill to your model.

Migration strategy tips

• Transition by age (for example, only objects older than 90 or 180 days).
• Keep a short hot window to avoid immediate restore needs.
• Separate compliance archives from operational logs to reduce restore churn.

What to monitor after the move

• Early deletion fees and unexpected transitions.
• Restore request volume and average restore size.
• Origin egress during restores (if restored data is copied elsewhere).

Data classification checklist

• Identify data with legal retention or audit requirements.
• Separate frequently accessed reports from cold archives.
• Tag objects with lifecycle intent so rules are predictable.

Restore readiness test

• Pick a sample archive and perform a full restore workflow.
• Measure total time from restore request to usable data.
• Document the steps so future restores are repeatable.

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