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Prometheus supports 4 types of metrics:

Counter

A counter is a cumulative metric that represents a single monotonically increasing counter whose value can only increase or be reset to zero on restart. For example, you can use a counter to represent the number of requests served, tasks completed, or errors.

Do not use a counter to expose a value that can decrease. For example, do not use a counter for the number of currently running processes; instead use a gauge.

Gauge

A gauge is a metric that represents a single numerical value that can arbitrarily go up and down.

Gauges are typically used for measured values like temperatures or current memory usage, but also "counts" that can go up and down, like the number of concurrent requests.

Histogram

A histogram samples observations (usually things like request durations or response sizes) and counts them in configurable buckets. It also provides a sum of all observed values.

A histogram with a base metric name of <basename> exposes multiple time series during a scrape:

• cumulative counters for the observation buckets, exposed as <basename>_bucket{le="<upper inclusive bound>"}
• the total sum of all observed values, exposed as <basename>_sum
• the count of events that have been observed, exposed as <basename>_count (identical to <basename>_bucket{le="+Inf"} above)

Summary

Similar to a histogram, a summary samples observations (usually things like request durations and response sizes). While it also provides a total count of observations and a sum of all observed values, it calculates configurable quantiles over a sliding time window.

A summary with a base metric name of <basename> exposes multiple time series during a scrape:

• streaming φ-quantiles (0 ≤ φ ≤ 1) of observed events, exposed as <basename>{quantile="<φ>"}
• the total sum of all observed values, exposed as <basename>_sum
• the count of events that have been observed, exposed as <basename>_count

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curl http://localhost:2112/metrics

Annotations

Annotating a Service

apiVersion: v1
kind: Service
metadata:
  name: kafka-azure-sink
  labels:
    app: kafka-azure-sink
  annotations:
    prometheus.io/scrape: "true"
    prometheus.io/port: "8080"
    prometheus.io/path: "/metrics"
spec:
  selector:
    app: kafka-azure-sink
  ports:
    - name: http
      port: 8080
      targetPort: 8080

Annotating a Pod

apiVersion: apps/v1
kind: Deployment
metadata:
  name: kafka-azure-sink
  labels:
    app: kafka-azure-sink
spec:
  replicas: 1
  selector:
    matchLabels:
      app: kafka-azure-sink
  template:
    metadata:
      labels:
        app: kafka-azure-sink
      annotations:
        prometheus.io/scrape: "true"
        prometheus.io/port: "8080"
        prometheus.io/path: "/metrics"
    spec:
      containers:
...

References

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