AWS CloudWatch Alarms Cost Calculator
Estimate CloudWatch Alarms-style costs with a simple alarm-month model. Compare baseline vs peak alarm inventory with your pricing.
Inputs
Standard alarms
Typical 1-minute period alarms.
High-resolution alarms
Alarms that evaluate on shorter periods.
Composite alarms
Total configured: 570 alarms.
Services monitored
Alarms per service
High-res share (%)
Composite share (%)
Est 317 / 29 / 14 alarms.
Price ($ / standard alarm-month)
Price ($ / high-res alarm-month)
Price ($ / composite alarm-month)
Use your effective region pricing.
Scenario presets
This estimates alarm charges only. Metric ingestion, dashboards, and notifications can be additional line items.
Results
Estimated monthly total
$75.00
Standard alarms
$50.00
High-resolution alarms
$15.00
Composite alarms
$10.00
High-res share
8.8%
Composite share
3.5%
How to get your inputs
- Alarm counts: export alarms per account and environment; split standard, high-res, composite.
- Scope: identify per-tenant/per-pod alarms that multiply fast.
- Resolution: flag high-res alarms separately; they cost more.
Result interpretation
- High-res and composite alarms grow cost quickly; review their share of total alarms.
- Alarm sprawl is often the real driver, not price changes.
Common mistakes
- Counting only production and ignoring staging or dev alarm inventories.
- Leaving duplicate alarms after migrations or refactors.
Alarm inventory checklist
- Group alarms by team or service to find ownership gaps.
- Separate composite alarms from standard ones for pricing accuracy.
- Track high-res alarms created for incidents and never removed.
Scenario planning
| Scenario | Standard | High-res | Composite |
|---|---|---|---|
| Baseline | Expected | Limited | Critical only |
| Peak | High | Higher | High |
Validate after changes
- Compare alarm counts by type before and after changes.
- Validate high-res alarm usage in a recent billing week.
Next steps
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Example scenario
- 500 standard alarms, 50 high-res alarms, and 20 composite alarms with your $/alarm-month prices.
- Peak 200% scenario helps capture incident-driven alarm sprawl.
Included
- Alarm charge estimate from alarm counts x $ per alarm-month inputs.
- Optional alarm inventory estimator.
- Baseline vs peak scenario table for alarm sprawl.
Not included
- Metric ingestion/retention and high-cardinality metrics costs.
- Dashboards, logs, and notifications (SNS, PagerDuty, etc.) unless modeled separately.
How we calculate
- Alarm cost per type = alarm count x $ per alarm-month.
- Total = standard + high-resolution + composite.
FAQ
Do alarms include metric costs?
No. Metrics are typically billed separately. If you create many custom metrics or have high-cardinality labels, metrics can dominate the total observability bill.
What's a common reason alarm bills grow unexpectedly?
Alarm sprawl: duplicated alarms across environments, per-tenant/per-pod alarms, and high-resolution alarms enabled broadly.
Related tools
Related guides
AWS CloudWatch Metrics Pricing & Cost Guide
CloudWatch metrics cost model: custom metrics, API requests, dashboards, and retention.
CloudWatch dashboards pricing: what to include (dashboard-month + API)
A practical guide to CloudWatch dashboard costs: dashboard-month charges plus the hidden drivers (metrics API requests, alarms, and high-cardinality metrics).
CloudWatch Logs Insights cost optimization (reduce GB scanned)
A practical playbook to reduce CloudWatch Logs Insights costs: measure GB scanned, fix query patterns, time-bound dashboards, and avoid repeated incident scans.
CloudWatch Logs Insights pricing: what to model (GB scanned)
A practical Logs Insights pricing checklist: the core unit is GB scanned. Model scanned GB from query habits, avoid dashboard re-scan traps, and validate with a measured baseline.
CloudWatch Logs pricing: ingestion, retention, and queries
A practical CloudWatch Logs pricing guide: model ingestion (GB/day), retention (GB-month), and query/scan costs (Insights/Athena). Includes pitfalls and a validation checklist.
CloudWatch metrics cost optimization: reduce custom metric sprawl
A practical playbook to reduce CloudWatch metrics costs: control custom metric cardinality, right-size resolution, reduce API polling, and validate observability coverage.
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Disclaimer
Educational use only. Not legal, financial, or professional advice. Results are estimates based on the inputs and assumptions shown on this page. Verify pricing and limits with your providers and documentation.
Last updated: 2026-01-28