Enter your log and pricing assumptions
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Formula used for estimation
This calculator assumes a steady-state system where the most recent retention window is always stored. It estimates storage size after compression, metadata overhead, and replication.
- monthly_storage = stored_gb × storage_cost_gb_month
- monthly_ingest = (raw_daily_gb × days_in_month) × ingest_cost_gb
- monthly_query = (queries_per_day × gb_scanned_per_query × days_in_month) × query_cost_gb
- monthly_egress = export_gb_month × egress_cost_gb
- total_monthly = (sum of components) × (1 + overhead_pct ÷ 100)
How to use this calculator
- Enter your average raw log volume per day in GB.
- Set retention days based on policy and compliance needs.
- Adjust compression, overhead, and replication for your stack.
- Paste your storage, ingestion, query, and egress unit costs.
- Estimate query behavior: queries/day and GB scanned per query.
- Click Calculate retention cost to see results above.
- Use CSV/PDF exports to share with finance and stakeholders.
Example scenarios table
These are sample inputs to help you sanity-check typical ranges.
| Scenario | Raw GB/day | Retention days | Compression ratio | Replication | Notes |
|---|---|---|---|---|---|
| Dev & test | 5 | 7 | 0.50 | 1 | Short retention, light durability, quick debugging. |
| Production | 25 | 30 | 0.40 | 2 | Balanced retention for troubleshooting and trend analysis. |
| Compliance | 60 | 180 | 0.35 | 3 | Long retention, higher resilience, stricter audit requirements. |
Key inputs that shape retention spend
Daily log volume and retention days set the baseline capacity. Compression and index overhead refine stored size, while replication multiplies it for resilience. Start with measured averages: many teams range from 5–100 GB/day. Retention commonly spans 7, 30, 90, or 180 days depending on risk. A compression ratio of 0.30–0.60 is typical. Metadata overhead often adds 5–20% when labels and indexes are enabled. Validate with weekly samples before finalizing.
Sizing logic behind stored gigabytes
This calculator models steady state, where a full retention window is always present. Effective daily stored volume equals raw GB/day times compression ratio, then increased by index overhead. Steady storage equals that daily stored figure times retention days, then times replication factor. For example, 25 GB/day, 30 days, 0.40 compression, 10% overhead, and 2× replication yields 660 GB stored. That stored GB drives storage charges each month for budgeting.
Monthly cost drivers you should validate
Storage is rarely the only line item. Many services charge ingestion per GB, so raw volume over a 30.44‑day month matters. Query spend depends on how much data is scanned, not how many rows match. If analysts run 40 queries/day and scan 2.5 GB each, that is about 3,044 GB scanned monthly. Export and egress charges apply when logs move to SIEM, archives, or dashboards across regions carefully.
Scenario planning for growth and compliance
Use this form to compare realistic paths over time. If volume grows 10% monthly, the storage footprint and ingestion spend climb in lockstep. Compliance often pushes retention from 30 to 180 days, creating a 6× increase in stored GB before considering replication. You can offset this with tighter filters, lower scan sizes, and structured schemas. Track both monthly and annual totals so procurement and finance can align commitments and reserves over cycles.
Operational tactics to reduce costs safely
Cost control works best when paired with reliability. Reduce scan GB by partitioning on time and service, and by indexing only critical fields. Set tiered retention: keep high‑value logs longer, and archive low‑value logs sooner. Apply sampling for verbose debug streams, but preserve security events. Review replication needs per environment; dev may need 1×, production 2×, and regulated workloads 3×. Revisit overhead buffers quarterly as tooling stabilizes. Document changes, share outcomes broadly.
1) What does “steady state” mean here?
It assumes your full retention window is always stored. New daily logs arrive as older logs expire, so stored gigabytes stay roughly constant for planning.
2) Should I use raw or compressed GB/day?
Enter raw daily volume. The calculator applies your compression ratio and metadata overhead to estimate stored volume consistently across scenarios.
3) Why is query cost based on scanned GB?
Many analytics engines bill by data scanned. Narrow time ranges, partitions, and selective fields reduce scanned GB and often lower query costs.
4) How do I estimate GB scanned per query?
Use query logs or vendor metrics if available. Otherwise, start with a conservative estimate and refine after observing typical filters and time windows.
5) What should overhead buffer include?
Include monitoring, additional indexes, cross‑region replication, feature add‑ons, and variability in usage. A small buffer prevents under‑budgeting during spikes.
6) Are the CSV and PDF exports stored permanently?
No. The exports are generated from your latest calculation saved in the current session. Run the calculator again if the session is cleared.