# Counters and Gauges — Prometheus + Grafana

Source: https://www.skillbyai.com/en/prometheus-grafana/i-counter

> Things that go up, things that go up and down.

## Pick the type by behaviour

A **counter** only increases (or resets to zero when the process restarts): requests served, errors, bytes sent. You almost never graph a raw counter; you graph its rate. A **gauge** goes up and down: memory in use, queue length, temperature, active connections. Do not use a gauge for something you count, because you lose increments between scrapes and restarts.

## Measure the right thing

Choosing the right metric type and instrumenting the key paths makes later queries and alerts simple.

![Three ideas: counters and gauges, histograms and summaries, client libraries.](assets/figures/prometheus-grafana/section-2-map.svg) — Figure 2.1 — Counters, histograms and instrumentation.

## Examples by type

Common choices.

```text
counter  http_requests_total, jobs_failed_total, bytes_sent_total
         -> query with rate() / increase()
gauge    queue_depth, memory_used_bytes, active_sessions, last_success_timestamp_seconds
         -> query directly, or with avg_over_time()/max_over_time()
```

## Record timestamps as gauges

A last_success_timestamp_seconds gauge lets you alert when a batch job has not succeeded recently: time() - metric > threshold.

**Quiz:** Which type fits "number of jobs waiting in a queue"?

- [ ] Counter
- [x] Gauge
- [ ] Histogram only
- [ ] Summary only

*Answer:* Gauge. It goes up and down.