CloudWatch dashboards pricing: what to include (dashboard-month + API)

CloudWatch dashboards are usually modeled as dashboard-month, but the “real” costs often live next door: metrics API requests, custom metrics, and alarms created to support dashboards and alerting.

Dashboard pricing inputs

  • Dashboard count: billable dashboard-months.
  • Widget refresh: API requests per refresh.
  • Viewer traffic: shared dashboards multiply calls.

What to model

  • Dashboards: dashboard-month count (how many dashboards exist and are billed)
  • Metrics API requests: GetMetricData / GetMetricStatistics called by dashboards and tools
  • Custom metrics volume: metrics you publish to support visualizations and SLOs
  • Alarm-months: alarms created as “dashboard companions”
CloudWatch metrics cost Alarms cost

A fast estimation workflow

  1. Count dashboards (prod vs non-prod).
  2. Estimate dashboard refresh traffic: users × views × refreshes.
  3. Estimate API requests: refreshes × widgets × metrics per widget.
  4. Apply dashboard-month and API request rates from your region pricing.

Worked example (order-of-magnitude)

Suppose 25 engineers open a dashboard 10 times/day, each view refreshes 5 times, and the dashboard has 20 widgets:

  • Dashboard refreshes/day ~= 25 * 10 * 5 = 1,250
  • If each widget queries ~3 metrics, metric queries/day ~= 1,250 * 20 * 3 = 75,000

This is why “dashboard sprawl” can create surprisingly large API request volume, even with normal usage patterns.

Common pitfalls

  • Dashboard duplication: each team clones a dashboard pack instead of sharing a standard set.
  • High-cardinality metrics: dashboards require per-dimension metrics that explode metric count.
  • Always-on refresh: wallboard TVs and NOC screens refresh continuously and drive constant queries.
  • Tool overlap: multiple observability tools poll the same CloudWatch metrics in parallel.
  • Cross-account views: shared dashboards across accounts can increase polling if multiple teams keep them open.

Cost control levers (without losing visibility)

  • Reduce duplication: maintain a shared “golden dashboard” per service.
  • Reduce refresh: avoid 10-second refresh for slow-moving metrics.
  • Reduce metrics per widget: aggregate where possible and avoid per-instance views by default.
  • Move heavy exploration to logs/traces for investigations and keep dashboards for operational monitoring.

If you need fast detection, prefer alarms for paging and keep dashboards optimized for triage rather than continuous high-frequency polling.

Validation checklist

  • Count dashboards by environment and by ownership/team.
  • Identify “always-on” dashboards (TVs, wallboards) and measure their refresh rate.
  • Measure metrics API request volume from a real week and validate the estimate.

Sources

Related guides

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FAQ

Do dashboards cost money by themselves?
Often yes (dashboard-month), but the bigger driver can be what dashboards cause: metrics API requests and the custom metrics you ingest to make dashboards useful.
Why do dashboard-heavy orgs see higher API request charges?
Dashboards refresh frequently and query multiple metrics each time. Multiply refresh rate × widgets × metrics per widget and it adds up quickly.
Last updated: 2026-02-07