コード例 #1
0
ファイル: graphite_outlet.go プロジェクト: heroku/l2met
func (g *GraphiteOutlet) convert() {
	for bucket := range g.Inbox {
		name := bucket.Id.Name
		if len(bucket.Id.Source) > 0 {
			name = bucket.Id.Source + "." + name
		}
		g.Outbox <- &GraphitePayload{name + ".min", bucket.Min()}
		g.Outbox <- &GraphitePayload{name + ".median", bucket.Median()}
		g.Outbox <- &GraphitePayload{name + ".perc95", bucket.P95()}
		g.Outbox <- &GraphitePayload{name + ".perc99", bucket.P99()}
		g.Outbox <- &GraphitePayload{name + ".max", bucket.Max()}
		g.Outbox <- &GraphitePayload{name + ".mean", bucket.Mean()}
		g.Outbox <- &GraphitePayload{name + ".sum", bucket.Sum()}
	}
}
コード例 #2
0
ファイル: librato_outlet.go プロジェクト: heroku/l2met
func (l *LibratoOutlet) convert() {
	for bucket := range l.Inbox {
		if len(bucket.Vals) == 0 {
			fmt.Printf("at=bucket-no-vals bucket=%s\n", bucket.Id.Name)
			continue
		}
		attrs := &LibratoAttributes{Min: 0, Units: bucket.Id.Units}
		//TODO(ryandotsmith): Some day Librato will support these
		//metrics in their complex measurement api. We will need to
		//move these up ^^ into the complex payload.
		l.Conversions <- &Payload{Attr: attrs, User: bucket.Id.User, Pass: bucket.Id.Pass, Time: ft(bucket.Id.Time), Source: bucket.Id.Source, Name: bucket.Id.Name + ".min", Val: ff(bucket.Min())}
		l.Conversions <- &Payload{Attr: attrs, User: bucket.Id.User, Pass: bucket.Id.Pass, Time: ft(bucket.Id.Time), Source: bucket.Id.Source, Name: bucket.Id.Name + ".max", Val: ff(bucket.Max())}
		l.Conversions <- &Payload{Attr: attrs, User: bucket.Id.User, Pass: bucket.Id.Pass, Time: ft(bucket.Id.Time), Source: bucket.Id.Source, Name: bucket.Id.Name + ".sum", Val: ff(bucket.Sum())}
		l.Conversions <- &Payload{Attr: attrs, User: bucket.Id.User, Pass: bucket.Id.Pass, Time: ft(bucket.Id.Time), Source: bucket.Id.Source, Name: bucket.Id.Name + ".count", Val: fi(bucket.Count())}
		l.Conversions <- &Payload{Attr: attrs, User: bucket.Id.User, Pass: bucket.Id.Pass, Time: ft(bucket.Id.Time), Source: bucket.Id.Source, Name: bucket.Id.Name + ".mean", Val: ff(bucket.Mean())}
		l.Conversions <- &Payload{Attr: attrs, User: bucket.Id.User, Pass: bucket.Id.Pass, Time: ft(bucket.Id.Time), Source: bucket.Id.Source, Name: bucket.Id.Name + ".last", Val: ff(bucket.Last())}
		l.Conversions <- &Payload{Attr: attrs, User: bucket.Id.User, Pass: bucket.Id.Pass, Time: ft(bucket.Id.Time), Source: bucket.Id.Source, Name: bucket.Id.Name + ".median", Val: ff(bucket.Median())}
		l.Conversions <- &Payload{Attr: attrs, User: bucket.Id.User, Pass: bucket.Id.Pass, Time: ft(bucket.Id.Time), Source: bucket.Id.Source, Name: bucket.Id.Name + ".perc95", Val: ff(bucket.P95())}
		l.Conversions <- &Payload{Attr: attrs, User: bucket.Id.User, Pass: bucket.Id.Pass, Time: ft(bucket.Id.Time), Source: bucket.Id.Source, Name: bucket.Id.Name + ".perc99", Val: ff(bucket.P99())}
		fmt.Printf("measure.bucket.conversion.delay=%d\n", bucket.Id.Delay(time.Now()))
	}
}
コード例 #3
0
ファイル: librato_outlet.go プロジェクト: raphweiner/l2met
func (l *LibratoOutlet) convert() {
	for bucket := range l.Inbox {
		if len(bucket.Vals) == 0 {
			fmt.Printf("at=bucket-no-vals bucket=%s\n", bucket.Id.Name)
			continue
		}
		//TODO(ryandotsmith): This is getting out of control.
		//We need a succinct way to building payloads.
		countAttr := &LibratoAttributes{Min: 0, Units: "count"}
		attrs := &LibratoAttributes{Min: 0, Units: bucket.Id.Units}
		l.Conversions <- &LibratoPayload{Attr: attrs, User: bucket.Id.User, Pass: bucket.Id.Pass, Time: ft(bucket.Id.Time), Source: bucket.Id.Source, Name: bucket.Id.Name + ".last", Val: ff(bucket.Last())}
		l.Conversions <- &LibratoPayload{Attr: attrs, User: bucket.Id.User, Pass: bucket.Id.Pass, Time: ft(bucket.Id.Time), Source: bucket.Id.Source, Name: bucket.Id.Name + ".min", Val: ff(bucket.Min())}
		l.Conversions <- &LibratoPayload{Attr: attrs, User: bucket.Id.User, Pass: bucket.Id.Pass, Time: ft(bucket.Id.Time), Source: bucket.Id.Source, Name: bucket.Id.Name + ".max", Val: ff(bucket.Max())}
		l.Conversions <- &LibratoPayload{Attr: attrs, User: bucket.Id.User, Pass: bucket.Id.Pass, Time: ft(bucket.Id.Time), Source: bucket.Id.Source, Name: bucket.Id.Name + ".mean", Val: ff(bucket.Mean())}
		l.Conversions <- &LibratoPayload{Attr: attrs, User: bucket.Id.User, Pass: bucket.Id.Pass, Time: ft(bucket.Id.Time), Source: bucket.Id.Source, Name: bucket.Id.Name + ".median", Val: ff(bucket.Median())}
		l.Conversions <- &LibratoPayload{Attr: attrs, User: bucket.Id.User, Pass: bucket.Id.Pass, Time: ft(bucket.Id.Time), Source: bucket.Id.Source, Name: bucket.Id.Name + ".perc95", Val: ff(bucket.P95())}
		l.Conversions <- &LibratoPayload{Attr: attrs, User: bucket.Id.User, Pass: bucket.Id.Pass, Time: ft(bucket.Id.Time), Source: bucket.Id.Source, Name: bucket.Id.Name + ".perc99", Val: ff(bucket.P99())}
		l.Conversions <- &LibratoPayload{Attr: attrs, User: bucket.Id.User, Pass: bucket.Id.Pass, Time: ft(bucket.Id.Time), Source: bucket.Id.Source, Name: bucket.Id.Name + ".sum", Val: ff(bucket.Sum())}
		l.Conversions <- &LibratoPayload{Attr: countAttr, User: bucket.Id.User, Pass: bucket.Id.Pass, Time: ft(bucket.Id.Time), Source: bucket.Id.Source, Name: bucket.Id.Name + ".count", Val: fi(bucket.Count())}
		fmt.Printf("measure.bucket.conversion.delay=%d\n", bucket.Id.Delay(time.Now()))
	}
}