如何使用 OpenCensus 检测 Prometheus Gauge？

Question

I am trying to find a way to instrument Prometheus Gauge metrics using OpenCencus in Golang. The goal is to track no of active sessions. So value can increase and decrease and also can reset to 0 on server restart.

They have an example of it https://opencensus.io/quickstart/go/metrics/ , but I am not able to co-relate any with Gauge and resetting to 0.

Could you suggest which Measure and View I should use to instrument Gauge which can increase, decrease, and reset to 0?

Answer 1

https://opencensus.io/stats/view/

I've not tried this but LastValue may (!?) convert to a Prometheus Gauge.

Count gives you the number of measurements and yields an (increasing) Counter. So, that's not helpful for you.

The only other alternatives are Sum and Distribution .

If LastValue doesn't yield a gauge, you may need to use Distribution .

Update: LastValue == Gauge

Hacked the example that was given:

package main

import (
    "context"
    "fmt"
    "log"
    "math/rand"
    "net/http"
    "os"
    "time"

    "contrib.go.opencensus.io/exporter/prometheus"
    "go.opencensus.io/stats"
    "go.opencensus.io/stats/view"
    "go.opencensus.io/tag"
)

var (
    MLatencyMs = stats.Float64("latency", "The latency in milliseconds", "ms")
)
var (
    KeyMethod, _ = tag.NewKey("method")
)

func main() {

    port := os.Getenv("PORT")
    if port == "" {
        port = "8080"
    }

    view1 := &view.View{
        Name:        "dist",
        Measure:     MLatencyMs,
        Description: "The dist of the latencies",
        TagKeys:     []tag.Key{KeyMethod},
        Aggregation: view.Distribution(0, 10, 100, 1000, 10000, 100000),
    }

    view2 := &view.View{
        Name:        "last",
        Measure:     MLatencyMs,
        Description: "The last of the latencies",
        TagKeys:     []tag.Key{KeyMethod},
        Aggregation: view.LastValue(),
    }

    if err := view.Register(view1, view2); err != nil {
        log.Fatalf("Failed to register the views: %v", err)
    }

    pe, err := prometheus.NewExporter(prometheus.Options{
        Namespace: "distlast",
    })
    if err != nil {
        log.Fatalf("Failed to create the Prometheus stats exporter: %v", err)
    }

    go func() {
        mux := http.NewServeMux()
        mux.Handle("/metrics", pe)
        log.Fatal(http.ListenAndServe(fmt.Sprintf(":%s", port), mux))
    }()

    rand.Seed(time.Now().UnixNano())
    ctx := context.Background()

    for {
        n := rand.Intn(100)
        log.Printf("[loop] n=%d\n", n)
        stats.Record(ctx, MLatencyMs.M(float64(time.Duration(n))))
        time.Sleep(1 * time.Second)
    }

}

And then go run . yields:

2020/10/15 14:03:25 [loop] n=77
2020/10/15 14:03:26 [loop] n=62
2020/10/15 14:03:27 [loop] n=48
2020/10/15 14:03:28 [loop] n=76
2020/10/15 14:03:29 [loop] n=20
2020/10/15 14:03:30 [loop] n=46
2020/10/15 14:03:31 [loop] n=47
2020/10/15 14:03:32 [loop] n=64
2020/10/15 14:03:33 [loop] n=15
2020/10/15 14:03:34 [loop] n=8

And metrics on localhost:8080/metrics yields:

# HELP distlast_dist The dist of the latencies
# TYPE distlast_dist histogram
distlast_dist_bucket{method="",le="10"} 1
distlast_dist_bucket{method="",le="100"} 10
distlast_dist_bucket{method="",le="1000"} 10
distlast_dist_bucket{method="",le="10000"} 10
distlast_dist_bucket{method="",le="100000"} 10
distlast_dist_bucket{method="",le="+Inf"} 10
distlast_dist_sum{method=""} 463.00000000000006
distlast_dist_count{method=""} 10
# HELP distlast_last The last of the latencies
# TYPE distlast_last gauge
distlast_last{method=""} 8

NOTE distlast_last has a value of 8 corresponding to the n=8 and distlast_dist_sum has a value of 463 .