6.3Prometheus Metric Types

Prometheus is the de facto standard for metrics collection in cloud-native environments:

Type	Description	Example	Use Case
Counter	Monotonically increasing value	http_requests_total	Request count, error count
Gauge	Value that can go up or down	temperature_celsius	Queue depth, active connections
Histogram	Observations bucketed by value	http_request_duration_seconds	Latency distributions
Summary	Pre-calculated percentiles	request_duration_quantile	Client-side percentiles

Choosing Between Histogram and Summary

• Histogram: Use when you need server-side aggregation (multiple pods, dashboards). Prometheus can calculate percentiles across instances.
• Summary: Use for client-side percentiles when you do not need cross-instance aggregation.

In most cases, choose Histogram. It is more flexible and works with Prometheus recording rules and alerts.