Estimate Glacier/Deep Archive retrieval volume (GB and requests)

Retrieval cost is often the surprise with archival storage. Model both GB retrieved and request count (objects retrieved). The same GB retrieved can have very different cost depending on whether it is a few large objects or millions of small objects.

Define "retrieval" for your workflow

  • Restore: rehydrating an object so it becomes readable again.
  • Read after restore: your jobs scanning the restored data (often the real driver of how often you restore).
  • Object count: how many objects you restore, which maps to request-like fees and operational work.

Method 1: From restore events (best if you have history)

  • Restores/month x average restore GB = retrieval GB/month.
  • Objects restored/month approximates retrieval requests/month.

If restores vary by day, do not use one average. Keep a baseline and a peak month (backfills and audits are typically the peak).

Method 2: From analytics workflows

  • If you rehydrate archives for analytics, model job frequency x data restored.
  • Large-scale backfills can dominate a single month's cost.

Method 3: From object counts (when the request bill matters)

If your archive has many small objects, treat "objects restored/month" as a primary input, not an afterthought. Even modest GB restored can become expensive if it is split into millions of objects.

  • List the top prefixes you restore from and estimate objects restored per job.
  • Multiply by job frequency to get objects/month.
  • Convert to cost using the archive calculator (it models GB and requests separately).

Sanity checks (to avoid underestimating)

  • Many small objects can create very high request counts.
  • Batching and packaging data into larger objects can reduce request charges.
  • Repeated rehydration suggests you may need a warmer tier or cached analysis copy.

Worked estimate template (copy/paste)

  • Retrieval GB/month = restores/month * GB per restore (baseline + peak scenario)
  • Retrieval requests/month = objects restored/month (baseline + peak scenario)
  • One-time event = backfill restores (GB) + backfill objects (requests)

Turn retrieval into cost

Use AWS S3 Glacier / Deep Archive Cost Calculator with your retrieval GB/month and retrieval requests/month assumptions.

  • Create a baseline scenario from the most typical month.
  • Create a peak scenario for audits/backfills and compare.
  • Use Copy inputs (JSON) to share assumptions with teammates during review.

How to validate the estimate

  • After the first month, reconcile your model with actual restore events and billing usage types.
  • Check whether your restores were concentrated in a few days (peaky usage) and keep the peak scenario.
  • Verify object-count assumptions by sampling one representative job and counting restored objects.

Related reading and tools

Archive pricing Reduce archive costs Storage costs Archive cost tool

Sources

Related guides

Glacier/Deep Archive cost optimization (reduce restores and requests)
A practical playbook to reduce archival storage costs: reduce restores, reduce small-object request volume, and avoid minimum duration penalties. Includes validation steps and related tools.
S3 Glacier Pricing & Cost Guide (storage, retrieval, Deep Archive)
Practical S3 Glacier cost model: storage GB-month, retrieval volume and requests, and minimum duration fees.
S3 Glacier retrieval pricing per GB and per request
A practical breakdown of Glacier retrieval pricing: cost per GB retrieved plus request fees, with guidance for small-object amplification and tier selection.
Estimate Secrets Manager API calls per month (GetSecretValue volume)
A practical workflow to estimate Secrets Manager API request volume (especially GetSecretValue): measure and scale when possible, model from runtime churn when not, and validate with CloudTrail so your budget survives peaks.
S3 pricing: a practical model for storage, requests, egress, and replication
A practical S3 pricing guide: what to include (GB-month, requests, egress, replication) and how to estimate the key inputs without copying price tables.
Estimate WAF request volume (CDN/LB to monthly requests)
How to estimate WAF request volume for cost models: from CDN/LB metrics, from logs, and what to do about bot spikes.

Related calculators

RPS to Monthly Requests Calculator
Estimate monthly request volume from RPS, hours/day, and utilization.
API Request Cost Calculator
Estimate request-based charges from monthly requests and $ per million.
CDN Request Cost Calculator
Estimate CDN request fees from monthly requests and $ per 10k/1M pricing.

FAQ

What's the fastest way to estimate retrieval GB/month?
Start with expected restores per month x average restore size. If restores are triggered by analytics jobs, use job frequency x data restored per job.
How do I estimate retrieval requests?
Requests roughly track objects retrieved. If you retrieve 1,000,000 objects in a month, model about 1,000,000 retrieval requests (adjust for your tooling and batching).
Why do retrieval bills spike?
Backfills and audits can restore large volumes in a short time. Many small-object restores can also create large request counts even if GB is modest.
How do I validate the estimate?
Use a representative window of restore jobs (counts and sizes), then compare against actual restore logs or billing once available.
Last updated: 2026-01-27