package influxdb import ( "context" "fmt" "time" "github.com/ethereum/go-ethereum/log" "github.com/ethereum/go-ethereum/metrics" influxdb2 "github.com/influxdata/influxdb-client-go/v2" "github.com/influxdata/influxdb-client-go/v2/api" ) type v2Reporter struct { reg metrics.Registry interval time.Duration endpoint string token string bucket string organization string namespace string tags map[string]string client influxdb2.Client write api.WriteAPI cache map[string]int64 } // InfluxDBWithTags starts a InfluxDB reporter which will post the from the given metrics.Registry at each d interval with the specified tags func InfluxDBV2WithTags(r metrics.Registry, d time.Duration, endpoint string, token string, bucket string, organization string, namespace string, tags map[string]string) { rep := &v2Reporter{ reg: r, interval: d, endpoint: endpoint, token: token, bucket: bucket, organization: organization, namespace: namespace, tags: tags, cache: make(map[string]int64), } rep.client = influxdb2.NewClient(rep.endpoint, rep.token) defer rep.client.Close() // async write client rep.write = rep.client.WriteAPI(rep.organization, rep.bucket) errorsCh := rep.write.Errors() // have to handle write errors in a separate goroutine like this b/c the channel is unbuffered and will block writes if not read go func() { for err := range errorsCh { log.Warn("write error", "err", err.Error()) } }() rep.run() } func (r *v2Reporter) run() { intervalTicker := time.NewTicker(r.interval) pingTicker := time.NewTicker(time.Second * 5) for { select { case <-intervalTicker.C: r.send() case <-pingTicker.C: _, err := r.client.Health(context.Background()) if err != nil { log.Warn("Got error from influxdb client health check", "err", err.Error()) } } } } func (r *v2Reporter) send() { r.reg.Each(func(name string, i interface{}) { now := time.Now() namespace := r.namespace switch metric := i.(type) { case metrics.Counter: v := metric.Count() l := r.cache[name] measurement := fmt.Sprintf("%s%s.count", namespace, name) fields := map[string]interface{}{ "value": v - l, } pt := influxdb2.NewPoint(measurement, r.tags, fields, now) r.write.WritePoint(pt) r.cache[name] = v case metrics.Gauge: ms := metric.Snapshot() measurement := fmt.Sprintf("%s%s.gauge", namespace, name) fields := map[string]interface{}{ "value": ms.Value(), } pt := influxdb2.NewPoint(measurement, r.tags, fields, now) r.write.WritePoint(pt) case metrics.GaugeFloat64: ms := metric.Snapshot() measurement := fmt.Sprintf("%s%s.gauge", namespace, name) fields := map[string]interface{}{ "value": ms.Value(), } pt := influxdb2.NewPoint(measurement, r.tags, fields, now) r.write.WritePoint(pt) case metrics.Histogram: ms := metric.Snapshot() if ms.Count() > 0 { ps := ms.Percentiles([]float64{0.5, 0.75, 0.95, 0.99, 0.999, 0.9999}) measurement := fmt.Sprintf("%s%s.histogram", namespace, name) 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], } pt := influxdb2.NewPoint(measurement, r.tags, fields, now) r.write.WritePoint(pt) } case metrics.Meter: ms := metric.Snapshot() measurement := fmt.Sprintf("%s%s.meter", namespace, name) fields := map[string]interface{}{ "count": ms.Count(), "m1": ms.Rate1(), "m5": ms.Rate5(), "m15": ms.Rate15(), "mean": ms.RateMean(), } pt := influxdb2.NewPoint(measurement, r.tags, fields, now) r.write.WritePoint(pt) case metrics.Timer: ms := metric.Snapshot() ps := ms.Percentiles([]float64{0.5, 0.75, 0.95, 0.99, 0.999, 0.9999}) measurement := fmt.Sprintf("%s%s.timer", namespace, name) 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(), } pt := influxdb2.NewPoint(measurement, r.tags, fields, now) r.write.WritePoint(pt) case metrics.ResettingTimer: t := metric.Snapshot() if len(t.Values()) > 0 { ps := t.Percentiles([]float64{50, 95, 99}) val := t.Values() measurement := fmt.Sprintf("%s%s.span", namespace, name) 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], } pt := influxdb2.NewPoint(measurement, r.tags, fields, now) r.write.WritePoint(pt) } } }) // Force all unwritten data to be sent r.write.Flush() }