Observability & SRE
Metrics Cardinality Estimator
Enter your metric's label names and unique value counts to compute total cardinality and identify high-cardinality risks. Runs entirely in your browser.
Calculations run locally in your browserTool
About this tool
Metrics Cardinality Estimator
The Metrics Cardinality Estimator computes total time series count from label dimensions, flags high-cardinality labels, and estimates platform cost impact.
• Estimate cardinality before adding a new label to a high-volume metric
• Identify which label is causing a cardinality explosion in Prometheus
• Calculate the Datadog custom metric cost for a given label set
• Design a low-cardinality label schema for a new service
Affiliate disclosure
Uptime, incident, and on-call management. Better Stack provides status pages, incident management, and on-call scheduling for engineering teams.
View monitoring options with Better Stack
External site · Independent provider · We may receive a commission · Not a recommendation
FAQ
What does this tool tell you?
The Metrics Cardinality Estimator computes total time series count from label dimensions, flags high-cardinality labels, and estimates platform cost impact.
What affects the result most?
Cardinality = unique time series = product of unique label value counts across all label dimensions. Datadog list overage is $5 per 100 custom metrics/month ($0.05 each). High-volume contracts may be lower; this calculator uses list overage pricing. High-cardinality label warning: user_id, request_id, trace_id in labels cause storage explosion.
How should I use the result?
The calculation is deterministic — the same inputs always produce the same output — so the most useful workflow is to vary one input at a time and see which factor moves the result most. That tells you where to focus your attention before committing to a decision.
Related tools