Metrics Cardinality Explosion Sizer

Visualize the terrifying Datadog/Prometheus bill caused by tagging metrics with unbounded cardinality (like user_id).

Base Custom Metrics (e.g. login_success, checkout_failed)

Environments (e.g. dev, stg, prod)

Regions (e.g. us-east-1, eu-central-1)

High-Cardinality Tag Unique Values (e.g. Unique Active Users)

Total Time Series Generated

3,000,000

Est. SaaS Monitoring Bill

$150,000.00 / mo

The Cardinality Trap: Time series databases create a unique record for every permutation of tags. Tagging a metric with `user_id=123` creates 5,000 distinct metrics instead of 1. Use tracing or logging for user-level debugging, not metrics!

About Metrics Cardinality

Calculate time series count and Datadog/Prometheus monthly bill explosions from high cardinality labels.

Why Use This Calculator?

Accurate infrastructure sizing prevents unexpected cloud budget blowouts while guaranteeing SLA compliance and system reliability under peak traffic.