Computer & IT
Log Retention Storage Calculator
Estimate current and forecast log storage after compression, copies, retention, and ingest growth, then reconcile storage and access cost.
Current retained raw data-
Current stored data after compression and replicas-
Daily raw volume at forecast end-
Forecast retained raw data-
Forecast stored data after compression and replicas-
Current storage cost per month-
Forecast storage cost per month-
Forecast storage, access, and egress cost-
Annualized forecast run rate-
Stored-capacity growth through horizon-
Decision view
Daily log blocks inside the retention window
Daily log blocks inside the retention windowNew log blocks enter one side of the active window while expired blocks leave and forecast retained capacity remains labeled.
Log Retention Storage monthly costForecast month is horizontal and modeled storage, access, and egress cost is vertical.
Exact scenario comparisonRetention period (days) changes while all other entered assumptions remain constant.
| Retention period (days) | Current retained raw data | Current stored data after compression and replicas | Daily raw volume at forecast end | Forecast retained raw data | Forecast stored data after compression and replicas | Current storage cost per month | Forecast storage cost per month | Forecast storage, access, and egress cost | Annualized forecast run rate | Stored-capacity growth through horizon |
|---|
Period-by-period detail
log retention monthly capacity and cost forecast
How to use Log Retention Storage Calculator
- Measure indexed and archived daily log volume.
- Set retention to the actual policy for the modeled tier.
- Check forecast capacity, search cost, and deletion behavior.
Calculator guide
Understanding Log Retention Storage Calculator
Log retention turns a high daily event stream into a large searchable and archived estate, especially when replicas and long retention overlap.
Calculation method
How the calculation works
Translate daily log retention creation into retained raw volume, apply compression and replica count, project monthly growth, and reconcile current and forecast storage capacity and run-rate cost. Daily log GB times retention days gives raw retained logs; compression reduces bytes and replicas expand stored capacity.
Retention window
See daily log blocks enter and expire from the window
The timeline shows ingest blocks, active retention, compressed replicas, and the forecast billing point.
Worked situations
Practical examples
- Verbose debug logging can double ingest without adding equivalent monitoring value.
- Hot searchable retention may be shorter than archive retention.
- A 90-day window contains roughly three months of daily ingest before growth.
Better inputs
Useful tips
- Split hot, warm, and archive tiers when their prices differ.
- Sample or filter low-value events before indexing.
- Verify deletion lag and immutable-retention requirements.
Before relying on the result
Limitations and common mistakes
- One retention period and one blended rate are modeled.
- Query compute, indexing overhead, and per-event charges are simplified.
- Compliance policy must be established independently.
Reference
Key terms
- Log ingest
- New raw log data generated per day.
- Hot retention
- Period during which logs remain readily searchable.
- Deletion lag
- Delay between policy expiry and physical byte removal.
Important note
Calculated from the entered technical values using the displayed model. Validate topology, workloads, capacity, security, redundancy, and observed performance before implementation.
Frequently asked questions
Should archive logs use the same calculator?
Use a separate scenario when retention and pricing differ.
Does this include index overhead?
Include it in observed raw growth or adjust the effective compression ratio.
Can negative growth represent filtering?
Yes, but confirm the chosen rate remains realistic over the full horizon.