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.
No data is transmitted — everything runs locallyTool
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
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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. High-cardinality label warning: user_id, request_id, trace_id in labels cause storage explosion. Cardinality budget: Prometheus recommend <10M active series per instance, Thanos/Cortex scales higher.
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.
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