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/*
Copyright 2015 The Kubernetes Authors.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
*/
package framework
import (
"bytes"
"context"
"encoding/json"
"fmt"
"io"
"math"
"reflect"
"sort"
"strconv"
"strings"
"sync"
"time"
metav1 "k8s.io/apimachinery/pkg/apis/meta/v1"
"k8s.io/apimachinery/pkg/util/sets"
clientset "k8s.io/client-go/kubernetes"
"k8s.io/kubernetes/pkg/master/ports"
schedulermetric "k8s.io/kubernetes/pkg/scheduler/metrics"
"k8s.io/kubernetes/pkg/util/system"
"k8s.io/kubernetes/test/e2e/framework/metrics"
"github.com/prometheus/common/expfmt"
"github.com/prometheus/common/model"
)
const (
// NodeStartupThreshold is a rough estimate of the time allocated for a pod to start on a node.
NodeStartupThreshold = 4 * time.Second
// We are setting 1s threshold for apicalls even in small clusters to avoid flakes.
// The problem is that if long GC is happening in small clusters (where we have e.g.
// 1-core master machines) and tests are pretty short, it may consume significant
// portion of CPU and basically stop all the real work.
// Increasing threshold to 1s is within our SLO and should solve this problem.
apiCallLatencyThreshold time.Duration = 1 * time.Second
// We use a higher threshold for list apicalls if the cluster is big (i.e having > 500 nodes)
// as list response sizes are bigger in general for big clusters. We also use a higher threshold
// for list calls at cluster scope (this includes non-namespaced and all-namespaced calls).
apiListCallLatencyThreshold time.Duration = 5 * time.Second
apiClusterScopeListCallThreshold time.Duration = 10 * time.Second
bigClusterNodeCountThreshold = 500
// Cluster Autoscaler metrics names
caFunctionMetric = "cluster_autoscaler_function_duration_seconds_bucket"
caFunctionMetricLabel = "function"
)
type MetricsForE2E metrics.MetricsCollection
func (m *MetricsForE2E) filterMetrics() {
interestingApiServerMetrics := make(metrics.ApiServerMetrics)
for _, metric := range InterestingApiServerMetrics {
interestingApiServerMetrics[metric] = (*m).ApiServerMetrics[metric]
}
interestingControllerManagerMetrics := make(metrics.ControllerManagerMetrics)
for _, metric := range InterestingControllerManagerMetrics {
interestingControllerManagerMetrics[metric] = (*m).ControllerManagerMetrics[metric]
}
interestingClusterAutoscalerMetrics := make(metrics.ClusterAutoscalerMetrics)
for _, metric := range InterestingClusterAutoscalerMetrics {
interestingClusterAutoscalerMetrics[metric] = (*m).ClusterAutoscalerMetrics[metric]
}
interestingKubeletMetrics := make(map[string]metrics.KubeletMetrics)
for kubelet, grabbed := range (*m).KubeletMetrics {
interestingKubeletMetrics[kubelet] = make(metrics.KubeletMetrics)
for _, metric := range InterestingKubeletMetrics {
interestingKubeletMetrics[kubelet][metric] = grabbed[metric]
}
}
(*m).ApiServerMetrics = interestingApiServerMetrics
(*m).ControllerManagerMetrics = interestingControllerManagerMetrics
(*m).KubeletMetrics = interestingKubeletMetrics
}
func (m *MetricsForE2E) PrintHumanReadable() string {
buf := bytes.Buffer{}
for _, interestingMetric := range InterestingApiServerMetrics {
buf.WriteString(fmt.Sprintf("For %v:\n", interestingMetric))
for _, sample := range (*m).ApiServerMetrics[interestingMetric] {
buf.WriteString(fmt.Sprintf("\t%v\n", metrics.PrintSample(sample)))
}
}
for _, interestingMetric := range InterestingControllerManagerMetrics {
buf.WriteString(fmt.Sprintf("For %v:\n", interestingMetric))
for _, sample := range (*m).ControllerManagerMetrics[interestingMetric] {
buf.WriteString(fmt.Sprintf("\t%v\n", metrics.PrintSample(sample)))
}
}
for _, interestingMetric := range InterestingClusterAutoscalerMetrics {
buf.WriteString(fmt.Sprintf("For %v:\n", interestingMetric))
for _, sample := range (*m).ClusterAutoscalerMetrics[interestingMetric] {
buf.WriteString(fmt.Sprintf("\t%v\n", metrics.PrintSample(sample)))
}
}
for kubelet, grabbed := range (*m).KubeletMetrics {
buf.WriteString(fmt.Sprintf("For %v:\n", kubelet))
for _, interestingMetric := range InterestingKubeletMetrics {
buf.WriteString(fmt.Sprintf("\tFor %v:\n", interestingMetric))
for _, sample := range grabbed[interestingMetric] {
buf.WriteString(fmt.Sprintf("\t\t%v\n", metrics.PrintSample(sample)))
}
}
}
return buf.String()
}
func (m *MetricsForE2E) PrintJSON() string {
m.filterMetrics()
return PrettyPrintJSON(m)
}
func (m *MetricsForE2E) SummaryKind() string {
return "MetricsForE2E"
}
var SchedulingLatencyMetricName = model.LabelValue(schedulermetric.SchedulerSubsystem + "_" + schedulermetric.SchedulingLatencyName)
var InterestingApiServerMetrics = []string{
"apiserver_request_count",
"apiserver_request_latencies_summary",
"etcd_helper_cache_entry_count",
"etcd_helper_cache_hit_count",
"etcd_helper_cache_miss_count",
"etcd_request_cache_add_latencies_summary",
"etcd_request_cache_get_latencies_summary",
"etcd_request_latencies_summary",
}
var InterestingControllerManagerMetrics = []string{
"garbage_collector_attempt_to_delete_queue_latency",
"garbage_collector_attempt_to_delete_work_duration",
"garbage_collector_attempt_to_orphan_queue_latency",
"garbage_collector_attempt_to_orphan_work_duration",
"garbage_collector_dirty_processing_latency_microseconds",
"garbage_collector_event_processing_latency_microseconds",
"garbage_collector_graph_changes_queue_latency",
"garbage_collector_graph_changes_work_duration",
"garbage_collector_orphan_processing_latency_microseconds",
"namespace_queue_latency",
"namespace_queue_latency_sum",
"namespace_queue_latency_count",
"namespace_retries",
"namespace_work_duration",
"namespace_work_duration_sum",
"namespace_work_duration_count",
}
var InterestingKubeletMetrics = []string{
"kubelet_container_manager_latency_microseconds",
"kubelet_docker_errors",
"kubelet_docker_operations_latency_microseconds",
"kubelet_generate_pod_status_latency_microseconds",
"kubelet_pod_start_latency_microseconds",
"kubelet_pod_worker_latency_microseconds",
"kubelet_pod_worker_start_latency_microseconds",
"kubelet_sync_pods_latency_microseconds",
}
var InterestingClusterAutoscalerMetrics = []string{
"function_duration_seconds",
"errors_total",
"evicted_pods_total",
}
// Dashboard metrics
type LatencyMetric struct {
Perc50 time.Duration `json:"Perc50"`
Perc90 time.Duration `json:"Perc90"`
Perc99 time.Duration `json:"Perc99"`
Perc100 time.Duration `json:"Perc100"`
}
type PodStartupLatency struct {
CreateToScheduleLatency LatencyMetric `json:"createToScheduleLatency"`
ScheduleToRunLatency LatencyMetric `json:"scheduleToRunLatency"`
RunToWatchLatency LatencyMetric `json:"runToWatchLatency"`
ScheduleToWatchLatency LatencyMetric `json:"scheduleToWatchLatency"`
E2ELatency LatencyMetric `json:"e2eLatency"`
}
func (l *PodStartupLatency) SummaryKind() string {
return "PodStartupLatency"
}
func (l *PodStartupLatency) PrintHumanReadable() string {
return PrettyPrintJSON(l)
}
func (l *PodStartupLatency) PrintJSON() string {
return PrettyPrintJSON(PodStartupLatencyToPerfData(l))
}
type SchedulingMetrics struct {
PredicateEvaluationLatency LatencyMetric `json:"predicateEvaluationLatency"`
PriorityEvaluationLatency LatencyMetric `json:"priorityEvaluationLatency"`
PreemptionEvaluationLatency LatencyMetric `json:"preemptionEvaluationLatency"`
BindingLatency LatencyMetric `json:"bindingLatency"`
ThroughputAverage float64 `json:"throughputAverage"`
ThroughputPerc50 float64 `json:"throughputPerc50"`
ThroughputPerc90 float64 `json:"throughputPerc90"`
ThroughputPerc99 float64 `json:"throughputPerc99"`
}
func (l *SchedulingMetrics) SummaryKind() string {
return "SchedulingMetrics"
}
func (l *SchedulingMetrics) PrintHumanReadable() string {
return PrettyPrintJSON(l)
}
func (l *SchedulingMetrics) PrintJSON() string {
return PrettyPrintJSON(l)
}
type Histogram struct {
Labels map[string]string `json:"labels"`
Buckets map[string]int `json:"buckets"`
}
type HistogramVec []Histogram
func newHistogram(labels map[string]string) *Histogram {
return &Histogram{
Labels: labels,
Buckets: make(map[string]int),
}
}
type EtcdMetrics struct {
BackendCommitDuration HistogramVec `json:"backendCommitDuration"`
SnapshotSaveTotalDuration HistogramVec `json:"snapshotSaveTotalDuration"`
PeerRoundTripTime HistogramVec `json:"peerRoundTripTime"`
WalFsyncDuration HistogramVec `json:"walFsyncDuration"`
MaxDatabaseSize float64 `json:"maxDatabaseSize"`
}
func newEtcdMetrics() *EtcdMetrics {
return &EtcdMetrics{
BackendCommitDuration: make(HistogramVec, 0),
SnapshotSaveTotalDuration: make(HistogramVec, 0),
PeerRoundTripTime: make(HistogramVec, 0),
WalFsyncDuration: make(HistogramVec, 0),
}
}
func (l *EtcdMetrics) SummaryKind() string {
return "EtcdMetrics"
}
func (l *EtcdMetrics) PrintHumanReadable() string {
return PrettyPrintJSON(l)
}
func (l *EtcdMetrics) PrintJSON() string {
return PrettyPrintJSON(l)
}
type EtcdMetricsCollector struct {
stopCh chan struct{}
wg *sync.WaitGroup
metrics *EtcdMetrics
}
func NewEtcdMetricsCollector() *EtcdMetricsCollector {
return &EtcdMetricsCollector{
stopCh: make(chan struct{}),
wg: &sync.WaitGroup{},
metrics: newEtcdMetrics(),
}
}
func getEtcdMetrics() ([]*model.Sample, error) {
// Etcd is only exposed on localhost level. We are using ssh method
if TestContext.Provider == "gke" {
Logf("Not grabbing scheduler metrics through master SSH: unsupported for gke")
return nil, nil
}
cmd := "curl http://localhost:2379/metrics"
sshResult, err := SSH(cmd, GetMasterHost()+":22", TestContext.Provider)
if err != nil || sshResult.Code != 0 {
return nil, fmt.Errorf("unexpected error (code: %d) in ssh connection to master: %#v", sshResult.Code, err)
}
data := sshResult.Stdout
return extractMetricSamples(data)
}
func getEtcdDatabaseSize() (float64, error) {
samples, err := getEtcdMetrics()
if err != nil {
return 0, err
}
for _, sample := range samples {
if sample.Metric[model.MetricNameLabel] == "etcd_debugging_mvcc_db_total_size_in_bytes" {
return float64(sample.Value), nil
}
}
return 0, fmt.Errorf("Couldn't find etcd database size metric")
}
// StartCollecting starts to collect etcd db size metric periodically
// and updates MaxDatabaseSize accordingly.
func (mc *EtcdMetricsCollector) StartCollecting(interval time.Duration) {
mc.wg.Add(1)
go func() {
defer mc.wg.Done()
for {
select {
case <-time.After(interval):
dbSize, err := getEtcdDatabaseSize()
if err != nil {
Logf("Failed to collect etcd database size")
continue
}
mc.metrics.MaxDatabaseSize = math.Max(mc.metrics.MaxDatabaseSize, dbSize)
case <-mc.stopCh:
return
}
}
}()
}
func (mc *EtcdMetricsCollector) StopAndSummarize() error {
close(mc.stopCh)
mc.wg.Wait()
// Do some one-off collection of metrics.
samples, err := getEtcdMetrics()
if err != nil {
return err
}
for _, sample := range samples {
switch sample.Metric[model.MetricNameLabel] {
case "etcd_disk_backend_commit_duration_seconds_bucket":
convertSampleToBucket(sample, &mc.metrics.BackendCommitDuration)
case "etcd_debugging_snap_save_total_duration_seconds_bucket":
convertSampleToBucket(sample, &mc.metrics.SnapshotSaveTotalDuration)
case "etcd_disk_wal_fsync_duration_seconds_bucket":
convertSampleToBucket(sample, &mc.metrics.WalFsyncDuration)
case "etcd_network_peer_round_trip_time_seconds_bucket":
convertSampleToBucket(sample, &mc.metrics.PeerRoundTripTime)
}
}
return nil
}
func (mc *EtcdMetricsCollector) GetMetrics() *EtcdMetrics {
return mc.metrics
}
type SaturationTime struct {
TimeToSaturate time.Duration `json:"timeToSaturate"`
NumberOfNodes int `json:"numberOfNodes"`
NumberOfPods int `json:"numberOfPods"`
Throughput float32 `json:"throughput"`
}
type APICall struct {
Resource string `json:"resource"`
Subresource string `json:"subresource"`
Verb string `json:"verb"`
Scope string `json:"scope"`
Latency LatencyMetric `json:"latency"`
Count int `json:"count"`
}
type APIResponsiveness struct {
APICalls []APICall `json:"apicalls"`
}
func (a *APIResponsiveness) SummaryKind() string {
return "APIResponsiveness"
}
func (a *APIResponsiveness) PrintHumanReadable() string {
return PrettyPrintJSON(a)
}
func (a *APIResponsiveness) PrintJSON() string {
return PrettyPrintJSON(ApiCallToPerfData(a))
}
func (a *APIResponsiveness) Len() int { return len(a.APICalls) }
func (a *APIResponsiveness) Swap(i, j int) {
a.APICalls[i], a.APICalls[j] = a.APICalls[j], a.APICalls[i]
}
func (a *APIResponsiveness) Less(i, j int) bool {
return a.APICalls[i].Latency.Perc99 < a.APICalls[j].Latency.Perc99
}
// Set request latency for a particular quantile in the APICall metric entry (creating one if necessary).
// 0 <= quantile <=1 (e.g. 0.95 is 95%tile, 0.5 is median)
// Only 0.5, 0.9 and 0.99 quantiles are supported.
func (a *APIResponsiveness) addMetricRequestLatency(resource, subresource, verb, scope string, quantile float64, latency time.Duration) {
for i, apicall := range a.APICalls {
if apicall.Resource == resource && apicall.Subresource == subresource && apicall.Verb == verb && apicall.Scope == scope {
a.APICalls[i] = setQuantileAPICall(apicall, quantile, latency)
return
}
}
apicall := setQuantileAPICall(APICall{Resource: resource, Subresource: subresource, Verb: verb, Scope: scope}, quantile, latency)
a.APICalls = append(a.APICalls, apicall)
}
// 0 <= quantile <=1 (e.g. 0.95 is 95%tile, 0.5 is median)
// Only 0.5, 0.9 and 0.99 quantiles are supported.
func setQuantileAPICall(apicall APICall, quantile float64, latency time.Duration) APICall {
setQuantile(&apicall.Latency, quantile, latency)
return apicall
}
// Only 0.5, 0.9 and 0.99 quantiles are supported.
func setQuantile(metric *LatencyMetric, quantile float64, latency time.Duration) {
switch quantile {
case 0.5:
metric.Perc50 = latency
case 0.9:
metric.Perc90 = latency
case 0.99:
metric.Perc99 = latency
}
}
// Add request count to the APICall metric entry (creating one if necessary).
func (a *APIResponsiveness) addMetricRequestCount(resource, subresource, verb, scope string, count int) {
for i, apicall := range a.APICalls {
if apicall.Resource == resource && apicall.Subresource == subresource && apicall.Verb == verb && apicall.Scope == scope {
a.APICalls[i].Count += count
return
}
}
apicall := APICall{Resource: resource, Subresource: subresource, Verb: verb, Count: count, Scope: scope}
a.APICalls = append(a.APICalls, apicall)
}
func readLatencyMetrics(c clientset.Interface) (*APIResponsiveness, error) {
var a APIResponsiveness
body, err := getMetrics(c)
if err != nil {
return nil, err
}
samples, err := extractMetricSamples(body)
if err != nil {
return nil, err
}
ignoredResources := sets.NewString("events")
// TODO: figure out why we're getting non-capitalized proxy and fix this.
ignoredVerbs := sets.NewString("WATCH", "WATCHLIST", "PROXY", "proxy", "CONNECT")
for _, sample := range samples {
// Example line:
// apiserver_request_latencies_summary{resource="namespaces",verb="LIST",quantile="0.99"} 908
// apiserver_request_count{resource="pods",verb="LIST",client="kubectl",code="200",contentType="json"} 233
if sample.Metric[model.MetricNameLabel] != "apiserver_request_latencies_summary" &&
sample.Metric[model.MetricNameLabel] != "apiserver_request_count" {
continue
}
resource := string(sample.Metric["resource"])
subresource := string(sample.Metric["subresource"])
verb := string(sample.Metric["verb"])
scope := string(sample.Metric["scope"])
if ignoredResources.Has(resource) || ignoredVerbs.Has(verb) {
continue
}
switch sample.Metric[model.MetricNameLabel] {
case "apiserver_request_latencies_summary":
latency := sample.Value
quantile, err := strconv.ParseFloat(string(sample.Metric[model.QuantileLabel]), 64)
if err != nil {
return nil, err
}
a.addMetricRequestLatency(resource, subresource, verb, scope, quantile, time.Duration(int64(latency))*time.Microsecond)
case "apiserver_request_count":
count := sample.Value
a.addMetricRequestCount(resource, subresource, verb, scope, int(count))
}
}
return &a, err
}
// Prints top five summary metrics for request types with latency and returns
// number of such request types above threshold. We use a higher threshold for
// list calls if nodeCount is above a given threshold (i.e. cluster is big).
func HighLatencyRequests(c clientset.Interface, nodeCount int) (int, *APIResponsiveness, error) {
isBigCluster := (nodeCount > bigClusterNodeCountThreshold)
metrics, err := readLatencyMetrics(c)
if err != nil {
return 0, metrics, err
}
sort.Sort(sort.Reverse(metrics))
badMetrics := 0
top := 5
for i := range metrics.APICalls {
latency := metrics.APICalls[i].Latency.Perc99
isListCall := (metrics.APICalls[i].Verb == "LIST")
isClusterScopedCall := (metrics.APICalls[i].Scope == "cluster")
isBad := false
latencyThreshold := apiCallLatencyThreshold
if isListCall && isBigCluster {
latencyThreshold = apiListCallLatencyThreshold
if isClusterScopedCall {
latencyThreshold = apiClusterScopeListCallThreshold
}
}
if latency > latencyThreshold {
isBad = true
badMetrics++
}
if top > 0 || isBad {
top--
prefix := ""
if isBad {
prefix = "WARNING "
}
Logf("%vTop latency metric: %+v", prefix, metrics.APICalls[i])
}
}
return badMetrics, metrics, nil
}
// Verifies whether 50, 90 and 99th percentiles of a latency metric are
// within the expected threshold.
func VerifyLatencyWithinThreshold(threshold, actual LatencyMetric, metricName string) error {
if actual.Perc50 > threshold.Perc50 {
return fmt.Errorf("too high %v latency 50th percentile: %v", metricName, actual.Perc50)
}
if actual.Perc90 > threshold.Perc90 {
return fmt.Errorf("too high %v latency 90th percentile: %v", metricName, actual.Perc90)
}
if actual.Perc99 > threshold.Perc99 {
return fmt.Errorf("too high %v latency 99th percentile: %v", metricName, actual.Perc99)
}
return nil
}
// Resets latency metrics in apiserver.
func ResetMetrics(c clientset.Interface) error {
Logf("Resetting latency metrics in apiserver...")
body, err := c.CoreV1().RESTClient().Delete().AbsPath("/metrics").DoRaw()
if err != nil {
return err
}
if string(body) != "metrics reset\n" {
return fmt.Errorf("Unexpected response: %q", string(body))
}
return nil
}
// Retrieves metrics information.
func getMetrics(c clientset.Interface) (string, error) {
body, err := c.CoreV1().RESTClient().Get().AbsPath("/metrics").DoRaw()
if err != nil {
return "", err
}
return string(body), nil
}
// Sends REST request to kube scheduler metrics
func sendRestRequestToScheduler(c clientset.Interface, op string) (string, error) {
opUpper := strings.ToUpper(op)
if opUpper != "GET" && opUpper != "DELETE" {
return "", fmt.Errorf("Unknown REST request")
}
nodes, err := c.CoreV1().Nodes().List(metav1.ListOptions{})
ExpectNoError(err)
var masterRegistered = false
for _, node := range nodes.Items {
if system.IsMasterNode(node.Name) {
masterRegistered = true
}
}
var responseText string
if masterRegistered {
ctx, cancel := context.WithTimeout(context.Background(), SingleCallTimeout)
defer cancel()
body, err := c.CoreV1().RESTClient().Verb(opUpper).
Context(ctx).
Namespace(metav1.NamespaceSystem).
Resource("pods").
Name(fmt.Sprintf("kube-scheduler-%v:%v", TestContext.CloudConfig.MasterName, ports.SchedulerPort)).
SubResource("proxy").
Suffix("metrics").
Do().Raw()
ExpectNoError(err)
responseText = string(body)
} else {
// If master is not registered fall back to old method of using SSH.
if TestContext.Provider == "gke" {
Logf("Not grabbing scheduler metrics through master SSH: unsupported for gke")
return "", nil
}
cmd := "curl -X " + opUpper + " http://localhost:10251/metrics"
sshResult, err := SSH(cmd, GetMasterHost()+":22", TestContext.Provider)
if err != nil || sshResult.Code != 0 {
return "", fmt.Errorf("unexpected error (code: %d) in ssh connection to master: %#v", sshResult.Code, err)
}
responseText = sshResult.Stdout
}
return responseText, nil
}
// Retrieves scheduler latency metrics.
func getSchedulingLatency(c clientset.Interface) (*SchedulingMetrics, error) {
result := SchedulingMetrics{}
data, err := sendRestRequestToScheduler(c, "GET")
if err != nil {
return nil, err
}
samples, err := extractMetricSamples(data)
if err != nil {
return nil, err
}
for _, sample := range samples {
if sample.Metric[model.MetricNameLabel] != SchedulingLatencyMetricName {
continue
}
var metric *LatencyMetric = nil
switch sample.Metric[schedulermetric.OperationLabel] {
case schedulermetric.PredicateEvaluation:
metric = &result.PredicateEvaluationLatency
case schedulermetric.PriorityEvaluation:
metric = &result.PriorityEvaluationLatency
case schedulermetric.PreemptionEvaluation:
metric = &result.PreemptionEvaluationLatency
case schedulermetric.Binding:
metric = &result.BindingLatency
}
if metric == nil {
continue
}
quantile, err := strconv.ParseFloat(string(sample.Metric[model.QuantileLabel]), 64)
if err != nil {
return nil, err
}
setQuantile(metric, quantile, time.Duration(int64(float64(sample.Value)*float64(time.Second))))
}
return &result, nil
}
// Verifies (currently just by logging them) the scheduling latencies.
func VerifySchedulerLatency(c clientset.Interface) (*SchedulingMetrics, error) {
latency, err := getSchedulingLatency(c)
if err != nil {
return nil, err
}
return latency, nil
}
func ResetSchedulerMetrics(c clientset.Interface) error {
responseText, err := sendRestRequestToScheduler(c, "DELETE")
if err != nil {
return fmt.Errorf("Unexpected response: %q", responseText)
}
return nil
}
func convertSampleToBucket(sample *model.Sample, h *HistogramVec) {
labels := make(map[string]string)
for k, v := range sample.Metric {
if k != "le" {
labels[string(k)] = string(v)
}
}
var hist *Histogram
for i := range *h {
if reflect.DeepEqual(labels, (*h)[i].Labels) {
hist = &((*h)[i])
break
}
}
if hist == nil {
hist = newHistogram(labels)
*h = append(*h, *hist)
}
hist.Buckets[string(sample.Metric["le"])] = int(sample.Value)
}
func PrettyPrintJSON(metrics interface{}) string {
output := &bytes.Buffer{}
if err := json.NewEncoder(output).Encode(metrics); err != nil {
Logf("Error building encoder: %v", err)
return ""
}
formatted := &bytes.Buffer{}
if err := json.Indent(formatted, output.Bytes(), "", " "); err != nil {
Logf("Error indenting: %v", err)
return ""
}
return string(formatted.Bytes())
}
// extractMetricSamples parses the prometheus metric samples from the input string.
func extractMetricSamples(metricsBlob string) ([]*model.Sample, error) {
dec := expfmt.NewDecoder(strings.NewReader(metricsBlob), expfmt.FmtText)
decoder := expfmt.SampleDecoder{
Dec: dec,
Opts: &expfmt.DecodeOptions{},
}
var samples []*model.Sample
for {
var v model.Vector
if err := decoder.Decode(&v); err != nil {
if err == io.EOF {
// Expected loop termination condition.
return samples, nil
}
return nil, err
}
samples = append(samples, v...)
}
}
// PodLatencyData encapsulates pod startup latency information.
type PodLatencyData struct {
// Name of the pod
Name string
// Node this pod was running on
Node string
// Latency information related to pod startuptime
Latency time.Duration
}
type LatencySlice []PodLatencyData
func (a LatencySlice) Len() int { return len(a) }
func (a LatencySlice) Swap(i, j int) { a[i], a[j] = a[j], a[i] }
func (a LatencySlice) Less(i, j int) bool { return a[i].Latency < a[j].Latency }
func ExtractLatencyMetrics(latencies []PodLatencyData) LatencyMetric {
length := len(latencies)
perc50 := latencies[int(math.Ceil(float64(length*50)/100))-1].Latency
perc90 := latencies[int(math.Ceil(float64(length*90)/100))-1].Latency
perc99 := latencies[int(math.Ceil(float64(length*99)/100))-1].Latency
perc100 := latencies[length-1].Latency
return LatencyMetric{Perc50: perc50, Perc90: perc90, Perc99: perc99, Perc100: perc100}
}
// LogSuspiciousLatency logs metrics/docker errors from all nodes that had slow startup times
// If latencyDataLag is nil then it will be populated from latencyData
func LogSuspiciousLatency(latencyData []PodLatencyData, latencyDataLag []PodLatencyData, nodeCount int, c clientset.Interface) {
if latencyDataLag == nil {
latencyDataLag = latencyData
}
for _, l := range latencyData {
if l.Latency > NodeStartupThreshold {
HighLatencyKubeletOperations(c, 1*time.Second, l.Node, Logf)
}
}
Logf("Approx throughput: %v pods/min",
float64(nodeCount)/(latencyDataLag[len(latencyDataLag)-1].Latency.Minutes()))
}
func PrintLatencies(latencies []PodLatencyData, header string) {
metrics := ExtractLatencyMetrics(latencies)
Logf("10%% %s: %v", header, latencies[(len(latencies)*9)/10:])
Logf("perc50: %v, perc90: %v, perc99: %v", metrics.Perc50, metrics.Perc90, metrics.Perc99)
}
func (m *MetricsForE2E) computeClusterAutoscalerMetricsDelta(before metrics.MetricsCollection) {
if beforeSamples, found := before.ClusterAutoscalerMetrics[caFunctionMetric]; found {
if afterSamples, found := m.ClusterAutoscalerMetrics[caFunctionMetric]; found {
beforeSamplesMap := make(map[string]*model.Sample)
for _, bSample := range beforeSamples {
beforeSamplesMap[makeKey(bSample.Metric[caFunctionMetricLabel], bSample.Metric["le"])] = bSample
}
for _, aSample := range afterSamples {
if bSample, found := beforeSamplesMap[makeKey(aSample.Metric[caFunctionMetricLabel], aSample.Metric["le"])]; found {
aSample.Value = aSample.Value - bSample.Value
}
}
}
}
}
func makeKey(a, b model.LabelValue) string {
return string(a) + "___" + string(b)
}
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