// Note that the metrics is partially based on the time exported by the endpoints controller on
	// the master machine. The measurement may be inaccurate if there is a clock drift between the
	// node and master machine.
	NetworkProgrammingLatency = metrics.NewHistogram(
		&metrics.HistogramOpts{
			Subsystem: kubeProxySubsystem,

Measuring the impact is both important and complicated, as cache performance is determined by many factors.
Performing measurements of the cache's impact can validate the extra effort (work, infrastructure) that is required to start using the cache.
These measurements can later serve as baselines for future improvements, and to watch for signs of regressions.

import (
	"bufio"
	"fmt"
	"html/template"
	"io"
	"os"
	"path/filepath"
	"regexp"
	"sort"
	"strconv"
	"strings"

	"github.com/google/pprof/internal/graph"
	"github.com/google/pprof/internal/measurement"
	"github.com/google/pprof/internal/plugin"
	"github.com/google/pprof/profile"
)

// printSource prints an annotated source listing, include all
// functions with samples that match the regexp rpt.options.symbol.

	lock(&ticks.lock)
	t.startTime = nanotime()
	t.startTicks = cputicks()
	unlock(&ticks.lock)
}

// minTimeForTicksPerSecond is the minimum elapsed time we require to consider our ticksPerSecond
// measurement to be of decent enough quality for profiling.
//
// There's a linear relationship here between minimum time and error from the true value.
// The error from the true ticks-per-second in a linux/amd64 VM seems to be:

	startTime            time.Time // Start time for window
	expMovingAvg         float64   // Previously calculated exponential moving average
}

// newRateMeasurement creates a new instance of the measurement with the initial start time.
func newRateMeasurement(initTime time.Time) *rateMeasurement {
	return &rateMeasurement{
		startTime: initTime,
	}
}

// incrementBytes add bytes reported for a bucket/target.

	// so as to be roughly exponential but still round numbers in everyday units. This is to minimise the number
	// of buckets while allowing accurate measurement of thresholds which might be used in SLOs
	// e.g. x% of pods start up within 30 seconds, or 15 minutes, etc.
	PodStartSLIDuration = metrics.NewHistogramVec(
		&metrics.HistogramOpts{
			Subsystem:      KubeletSubsystem,

		"Show percentages relative to focused subgraph",
		"If unset, percentages are relative to full graph before focusing",
		"to facilitate comparison with original graph."),
	"unit": helpText(
		"Measurement units to display",
		"Scale the sample values to this unit.",
		"For time-based profiles, use seconds, milliseconds, nanoseconds, etc.",
		"For memory profiles, use megabytes, kilobytes, bytes, etc.",

	{170, "EDC5170I", "An error was encountered with WLM."},
	{171, "EDC5171I", "An error was encountered with CPL."},
	{172, "EDC5172I", "An error was encountered with Application Response Measurement (ARM) component."},
	{200, "EDC5200I", "The application contains a Language Environment member language that cannot tolerate a fork()."},

		return nil, err
	}

	// If *most* samples have the same second-to-the-bottom frame, it
	// strongly suggests that it is an uninteresting artifact of
	// measurement -- a stack frame pushed by the signal handler. The
	// bottom frame is always correct as it is picked up from the signal
	// structure, not the stack. Check if this is the case and if so,
	// remove.

volume plugin path on each kubelet node. This is an alpha feature and may
change in future.
  * Kubelet exposes a new Alpha metrics API - /stats/summary in a user friendly format with reduced system overhead. The measurement is done in PR [#22542](https://github.com/kubernetes/kubernetes/pull/22542).

### Action required

  * Docker v1.9.1 is officially recommended. Docker v1.8.3 and Docker v1.10 are