forked from cerc-io/plugeth
metrics: add cpu counters (#26796)
This PR adds counter metrics for the CPU system and the Geth process. Currently the only metrics available for these items are gauges. Gauges are fine when the consumer scrapes metrics data at the same interval as Geth produces new values (every 3 seconds), but it is likely that most consumers will not scrape that often. Intervals of 10, 15, or maybe even 30 seconds are probably more common. So the problem is, how does the consumer estimate what the CPU was doing in between scrapes. With a counter, it's easy ... you just subtract two successive values and divide by the time to get a nice, accurate average. But with a gauge, you can't do that. A gauge reading is an instantaneous picture of what was happening at that moment, but it gives you no idea about what was going on between scrapes. Taking an average of values is meaningless.
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@@ -50,6 +50,10 @@ func (c *collector) addCounter(name string, m metrics.Counter) {
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c.writeGaugeCounter(name, m.Count())
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}
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func (c *collector) addCounterFloat64(name string, m metrics.CounterFloat64) {
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c.writeGaugeCounter(name, m.Count())
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}
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func (c *collector) addGauge(name string, m metrics.Gauge) {
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c.writeGaugeCounter(name, m.Value())
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}
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@@ -20,6 +20,10 @@ func TestCollector(t *testing.T) {
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counter.Inc(12345)
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c.addCounter("test/counter", counter)
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counterfloat64 := metrics.NewCounterFloat64()
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counterfloat64.Inc(54321.98)
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c.addCounterFloat64("test/counter_float64", counterfloat64)
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gauge := metrics.NewGauge()
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gauge.Update(23456)
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c.addGauge("test/gauge", gauge)
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@@ -61,6 +65,9 @@ func TestCollector(t *testing.T) {
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const expectedOutput = `# TYPE test_counter gauge
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test_counter 12345
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# TYPE test_counter_float64 gauge
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test_counter_float64 54321.98
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# TYPE test_gauge gauge
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test_gauge 23456
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@@ -45,6 +45,8 @@ func Handler(reg metrics.Registry) http.Handler {
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switch m := i.(type) {
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case metrics.Counter:
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c.addCounter(name, m.Snapshot())
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case metrics.CounterFloat64:
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c.addCounterFloat64(name, m.Snapshot())
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case metrics.Gauge:
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c.addGauge(name, m.Snapshot())
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case metrics.GaugeFloat64:
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