bsc/metrics/influxdb/influxdb.go
turboboost55 7dc100714d
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.
2023-03-23 14:13:50 +01:00

272 lines
6.7 KiB
Go

package influxdb
import (
"fmt"
uurl "net/url"
"time"
"github.com/ethereum/go-ethereum/log"
"github.com/ethereum/go-ethereum/metrics"
"github.com/influxdata/influxdb/client"
)
type reporter struct {
reg metrics.Registry
interval time.Duration
url uurl.URL
database string
username string
password string
namespace string
tags map[string]string
client *client.Client
cache map[string]int64
}
// InfluxDB starts a InfluxDB reporter which will post the from the given metrics.Registry at each d interval.
func InfluxDB(r metrics.Registry, d time.Duration, url, database, username, password, namespace string) {
InfluxDBWithTags(r, d, url, database, username, password, namespace, nil)
}
// InfluxDBWithTags starts a InfluxDB reporter which will post the from the given metrics.Registry at each d interval with the specified tags
func InfluxDBWithTags(r metrics.Registry, d time.Duration, url, database, username, password, namespace string, tags map[string]string) {
u, err := uurl.Parse(url)
if err != nil {
log.Warn("Unable to parse InfluxDB", "url", url, "err", err)
return
}
rep := &reporter{
reg: r,
interval: d,
url: *u,
database: database,
username: username,
password: password,
namespace: namespace,
tags: tags,
cache: make(map[string]int64),
}
if err := rep.makeClient(); err != nil {
log.Warn("Unable to make InfluxDB client", "err", err)
return
}
rep.run()
}
// InfluxDBWithTagsOnce runs once an InfluxDB reporter and post the given metrics.Registry with the specified tags
func InfluxDBWithTagsOnce(r metrics.Registry, url, database, username, password, namespace string, tags map[string]string) error {
u, err := uurl.Parse(url)
if err != nil {
return fmt.Errorf("unable to parse InfluxDB. url: %s, err: %v", url, err)
}
rep := &reporter{
reg: r,
url: *u,
database: database,
username: username,
password: password,
namespace: namespace,
tags: tags,
cache: make(map[string]int64),
}
if err := rep.makeClient(); err != nil {
return fmt.Errorf("unable to make InfluxDB client. err: %v", err)
}
if err := rep.send(); err != nil {
return fmt.Errorf("unable to send to InfluxDB. err: %v", err)
}
return nil
}
func (r *reporter) makeClient() (err error) {
r.client, err = client.NewClient(client.Config{
URL: r.url,
Username: r.username,
Password: r.password,
Timeout: 10 * time.Second,
})
return
}
func (r *reporter) run() {
intervalTicker := time.NewTicker(r.interval)
pingTicker := time.NewTicker(time.Second * 5)
defer intervalTicker.Stop()
defer pingTicker.Stop()
for {
select {
case <-intervalTicker.C:
if err := r.send(); err != nil {
log.Warn("Unable to send to InfluxDB", "err", err)
}
case <-pingTicker.C:
_, _, err := r.client.Ping()
if err != nil {
log.Warn("Got error while sending a ping to InfluxDB, trying to recreate client", "err", err)
if err = r.makeClient(); err != nil {
log.Warn("Unable to make InfluxDB client", "err", err)
}
}
}
}
}
func (r *reporter) send() error {
var pts []client.Point
r.reg.Each(func(name string, i interface{}) {
now := time.Now()
namespace := r.namespace
switch metric := i.(type) {
case metrics.Counter:
count := metric.Count()
pts = append(pts, client.Point{
Measurement: fmt.Sprintf("%s%s.count", namespace, name),
Tags: r.tags,
Fields: map[string]interface{}{
"value": count,
},
Time: now,
})
case metrics.CounterFloat64:
count := metric.Count()
pts = append(pts, client.Point{
Measurement: fmt.Sprintf("%s%s.count", namespace, name),
Tags: r.tags,
Fields: map[string]interface{}{
"value": count,
},
Time: now,
})
case metrics.Gauge:
ms := metric.Snapshot()
pts = append(pts, client.Point{
Measurement: fmt.Sprintf("%s%s.gauge", namespace, name),
Tags: r.tags,
Fields: map[string]interface{}{
"value": ms.Value(),
},
Time: now,
})
case metrics.GaugeFloat64:
ms := metric.Snapshot()
pts = append(pts, client.Point{
Measurement: fmt.Sprintf("%s%s.gauge", namespace, name),
Tags: r.tags,
Fields: map[string]interface{}{
"value": ms.Value(),
},
Time: now,
})
case metrics.Histogram:
ms := metric.Snapshot()
if ms.Count() > 0 {
ps := ms.Percentiles([]float64{0.25, 0.5, 0.75, 0.95, 0.99, 0.999, 0.9999})
fields := map[string]interface{}{
"count": ms.Count(),
"max": ms.Max(),
"mean": ms.Mean(),
"min": ms.Min(),
"stddev": ms.StdDev(),
"variance": ms.Variance(),
"p25": ps[0],
"p50": ps[1],
"p75": ps[2],
"p95": ps[3],
"p99": ps[4],
"p999": ps[5],
"p9999": ps[6],
}
pts = append(pts, client.Point{
Measurement: fmt.Sprintf("%s%s.histogram", namespace, name),
Tags: r.tags,
Fields: fields,
Time: now,
})
}
case metrics.Meter:
ms := metric.Snapshot()
pts = append(pts, client.Point{
Measurement: fmt.Sprintf("%s%s.meter", namespace, name),
Tags: r.tags,
Fields: map[string]interface{}{
"count": ms.Count(),
"m1": ms.Rate1(),
"m5": ms.Rate5(),
"m15": ms.Rate15(),
"mean": ms.RateMean(),
},
Time: now,
})
case metrics.Timer:
ms := metric.Snapshot()
ps := ms.Percentiles([]float64{0.5, 0.75, 0.95, 0.99, 0.999, 0.9999})
pts = append(pts, client.Point{
Measurement: fmt.Sprintf("%s%s.timer", namespace, name),
Tags: r.tags,
Fields: map[string]interface{}{
"count": ms.Count(),
"max": ms.Max(),
"mean": ms.Mean(),
"min": ms.Min(),
"stddev": ms.StdDev(),
"variance": ms.Variance(),
"p50": ps[0],
"p75": ps[1],
"p95": ps[2],
"p99": ps[3],
"p999": ps[4],
"p9999": ps[5],
"m1": ms.Rate1(),
"m5": ms.Rate5(),
"m15": ms.Rate15(),
"meanrate": ms.RateMean(),
},
Time: now,
})
case metrics.ResettingTimer:
t := metric.Snapshot()
if len(t.Values()) > 0 {
ps := t.Percentiles([]float64{50, 95, 99})
val := t.Values()
pts = append(pts, client.Point{
Measurement: fmt.Sprintf("%s%s.span", namespace, name),
Tags: r.tags,
Fields: map[string]interface{}{
"count": len(val),
"max": val[len(val)-1],
"mean": t.Mean(),
"min": val[0],
"p50": ps[0],
"p95": ps[1],
"p99": ps[2],
},
Time: now,
})
}
}
})
bps := client.BatchPoints{
Points: pts,
Database: r.database,
}
_, err := r.client.Write(bps)
return err
}