netbird/gvisor
0
0
Fork 0
mirror of https://github.com/netbirdio/gvisor.git synced 2026-05-22 17:12:49 -07:00
Code Issues Packages Projects Releases Wiki Activity

Metrics visualization: Show extrapolated rate for short-duration profiles.

Browse Source 
All rate metrics currently show per-second rates, which cannot be computed
before we have at least 1 second's worth of profile data. However, it's
reasonable to want to run very short workloads (less than 1 second) and still
want to see how those rates evolved over this duration. So this change
computes an extrapolated per-second rate for the first second of execution.

PiperOrigin-RevId: 648513094
This commit is contained in:
Etienne Perot
2024-07-01 16:08:09 -07:00
committed by gVisor bot
parent a5fbf8ba58
commit bcc785fc78
1 changed files with 23 additions and 1 deletions
Download Patch File Download Diff File Expand all files Collapse all files
test/metricsviz/metricsviz.go
+23 -1
View File
@@ -221,9 +221,13 @@ func (c *chart) getXAxis() ([]string, error) {
// series returns a single line series of the chart.
func (c *chart) series(ts *TimeSeries, isCumulative bool) ([]opts.LineData, error) {
const windowDuration = time.Second
const (
windowDuration = time.Second
minTimeToReport = 10 * time.Millisecond
)
seriesData := make([]opts.LineData, len(ts.Data))
if isCumulative {
timeSeriesIsLongEnough := false
lastValidXIndex := 0
for i, p := range ts.Data {
baselineWhen := p.When.Add(-windowDuration)
@@ -263,12 +267,30 @@ func (c *chart) series(ts *TimeSeries, isCumulative bool) ([]opts.LineData, erro
baselineWhenFraction := float64(baselineWhen.Sub(whenBefore)) / float64(whenDelta)
baseline := baselineBefore + uint64(float64(baselineDelta)*baselineWhenFraction)
seriesData[i] = opts.LineData{Value: p.Value - baseline, YAxisIndex: 0, Symbol: "none"}
timeSeriesIsLongEnough = true
case p.When.Sub(ts.Data[0].When) >= minTimeToReport:
// We don't yet have enough points to get a full `windowDuration`'s
// worth of data, but we do have enough data to report something if
// we assume that the rate can be extrapolated from the first point
// until now.
baselineBefore := ts.Data[0].Value
baselineAfter := p.Value
baselineDelta := baselineAfter - baselineBefore
whenBefore := ts.Data[0].When
whenAfter := p.When
whenDelta := whenAfter.Sub(whenBefore)
interpolationMultiplier := float64(windowDuration.Nanoseconds()) / float64(whenDelta.Nanoseconds())
seriesData[i] = opts.LineData{Value: uint64(float64(baselineDelta) * interpolationMultiplier), YAxisIndex: 0, Symbol: "none"}
timeSeriesIsLongEnough = true
default:
// Happens naturally for points too early in the timeseries,
// set the point to nil.
seriesData[i] = opts.LineData{Value: nil, YAxisIndex: 0, Symbol: "none"}
}
}
if !timeSeriesIsLongEnough {
return nil, fmt.Errorf("metric %v is cumulative but timeseries data for it is smaller than minimum chartable duration (%v), please run the workload for longer for cumulative timeseries to become meaningful", ts.Metric.Name, minTimeToReport)
}
} else {
// Non-cumulative time series are more straightforward.
for i, p := range ts.Data {