mirror of
https://github.com/k3s-io/kubernetes.git
synced 2025-07-23 11:50:44 +00:00
Use timing ratio histograms instead of sample-and-watermark histograms
This commit is contained in:
Mike Spreitzer
parent
8039f9d600
commit
0c0b7ca49f
@ -220,13 +220,6 @@ func TestApfRejectRequest(t *testing.T) {
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}
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func TestApfExemptRequest(t *testing.T) {
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epmetrics.Register()
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fcmetrics.Register()
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// Wait for at least one sampling window to pass since creation of metrics.ReadWriteConcurrencyObserverPairGenerator,
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// so that an observation will cause some data to go into the Prometheus metrics.
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time.Sleep(time.Millisecond * 50)
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server := newApfServerWithSingleRequest(t, decisionNoQueuingExecute)
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defer server.Close()
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@ -240,19 +233,11 @@ func TestApfExemptRequest(t *testing.T) {
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checkForExpectedMetrics(t, []string{
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"apiserver_current_inflight_requests",
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"apiserver_flowcontrol_read_vs_write_request_count_watermarks",
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"apiserver_flowcontrol_read_vs_write_request_count_samples",
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"apiserver_flowcontrol_read_vs_write_current_requests",
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})
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}
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func TestApfExecuteRequest(t *testing.T) {
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epmetrics.Register()
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fcmetrics.Register()
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// Wait for at least one sampling window to pass since creation of metrics.ReadWriteConcurrencyObserverPairGenerator,
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// so that an observation will cause some data to go into the Prometheus metrics.
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time.Sleep(time.Millisecond * 50)
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server := newApfServerWithSingleRequest(t, decisionQueuingExecute)
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defer server.Close()
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@ -267,19 +252,11 @@ func TestApfExecuteRequest(t *testing.T) {
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checkForExpectedMetrics(t, []string{
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"apiserver_current_inflight_requests",
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"apiserver_current_inqueue_requests",
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"apiserver_flowcontrol_read_vs_write_request_count_watermarks",
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"apiserver_flowcontrol_read_vs_write_request_count_samples",
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"apiserver_flowcontrol_read_vs_write_current_requests",
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})
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}
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func TestApfExecuteMultipleRequests(t *testing.T) {
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epmetrics.Register()
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fcmetrics.Register()
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// Wait for at least one sampling window to pass since creation of metrics.ReadWriteConcurrencyObserverPairGenerator,
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// so that an observation will cause some data to go into the Prometheus metrics.
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time.Sleep(time.Millisecond * 50)
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concurrentRequests := 5
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preStartExecute, postStartExecute := &sync.WaitGroup{}, &sync.WaitGroup{}
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preEnqueue, postEnqueue := &sync.WaitGroup{}, &sync.WaitGroup{}
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@ -347,8 +324,7 @@ func TestApfExecuteMultipleRequests(t *testing.T) {
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checkForExpectedMetrics(t, []string{
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"apiserver_current_inflight_requests",
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"apiserver_current_inqueue_requests",
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"apiserver_flowcontrol_read_vs_write_request_count_watermarks",
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"apiserver_flowcontrol_read_vs_write_request_count_samples",
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"apiserver_flowcontrol_read_vs_write_current_requests",
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})
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}
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@ -27,7 +27,6 @@ import (
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compbasemetrics "k8s.io/component-base/metrics"
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"k8s.io/component-base/metrics/legacyregistry"
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basemetricstestutil "k8s.io/component-base/metrics/testutil"
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"k8s.io/utils/clock"
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)
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const (
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@ -40,7 +39,9 @@ const (
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priorityLevel = "priority_level"
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flowSchema = "flow_schema"
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phase = "phase"
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mark = "mark"
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LabelNamePhase = "phase"
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LabelValueWaiting = "waiting"
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LabelValueExecuting = "executing"
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)
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var (
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@ -106,66 +107,45 @@ var (
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[]string{priorityLevel, flowSchema},
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)
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// PriorityLevelExecutionSeatsGaugeVec creates observers of seats occupied throughout execution for priority levels
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PriorityLevelExecutionSeatsGaugeVec = NewSampleAndWaterMarkHistogramsVec(clock.RealClock{}, time.Millisecond,
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&compbasemetrics.HistogramOpts{
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PriorityLevelExecutionSeatsGaugeVec = NewTimingRatioHistogramVec(
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&compbasemetrics.TimingHistogramOpts{
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Namespace: namespace,
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Subsystem: subsystem,
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Name: "priority_level_seat_count_samples",
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Help: "Periodic observations of number of seats occupied for any stage of execution (but only initial stage for WATCHes)",
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Buckets: []float64{0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1},
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Name: "priority_level_seat_utilization",
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Help: "Observations, at the end of every nanosecond, of utilization of seats for any stage of execution (but only initial stage for WATCHes)",
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// Buckets for both 0.99 and 1.0 mean PromQL's histogram_quantile will reveal saturation
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Buckets: []float64{0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 0.95, 0.99, 1},
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ConstLabels: map[string]string{phase: "executing"},
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StabilityLevel: compbasemetrics.ALPHA,
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},
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&compbasemetrics.HistogramOpts{
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Namespace: namespace,
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Subsystem: subsystem,
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Name: "priority_level_seat_count_watermarks",
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Help: "Watermarks of the number of seats occupied for any stage of execution (but only initial stage for WATCHes)",
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Buckets: []float64{0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1},
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ConstLabels: map[string]string{phase: "executing"},
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StabilityLevel: compbasemetrics.ALPHA,
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},
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[]string{priorityLevel},
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priorityLevel,
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)
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// PriorityLevelConcurrencyGaugeVec creates gauges of concurrency broken down by phase, priority level
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PriorityLevelConcurrencyGaugeVec = NewSampleAndWaterMarkHistogramsVec(clock.RealClock{}, time.Millisecond,
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&compbasemetrics.HistogramOpts{
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PriorityLevelConcurrencyGaugeVec = NewTimingRatioHistogramVec(
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&compbasemetrics.TimingHistogramOpts{
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Namespace: namespace,
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Subsystem: subsystem,
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Name: "priority_level_request_count_samples",
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Help: "Periodic observations of the number of requests waiting or in any stage of execution (but only initial stage for WATCHes)",
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Buckets: []float64{0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1},
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Name: "priority_level_request_utilization",
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Help: "Observations, at the end of every nanosecond, of number of requests (as a fraction of the relevant limit) waiting or in any stage of execution (but only initial stage for WATCHes)",
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// For executing: the denominator will be seats, so this metric will skew low.
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// FOr waiting: the denominiator is individual queue length limit, so this metric can go over 1. Issue #110160
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Buckets: []float64{0, 0.001, 0.0025, 0.005, 0.1, 0.25, 0.5, 0.75, 1, 10, 100},
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StabilityLevel: compbasemetrics.ALPHA,
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},
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&compbasemetrics.HistogramOpts{
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Namespace: namespace,
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Subsystem: subsystem,
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Name: "priority_level_request_count_watermarks",
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Help: "Watermarks of the number of requests waiting or in any stage of execution (but only initial stage for WATCHes)",
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Buckets: []float64{0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1},
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StabilityLevel: compbasemetrics.ALPHA,
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},
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[]string{LabelNamePhase, priorityLevel},
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LabelNamePhase, priorityLevel,
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)
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// ReadWriteConcurrencyGaugeVec creates gauges of number of requests broken down by phase and mutating vs readonly
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ReadWriteConcurrencyGaugeVec = NewSampleAndWaterMarkHistogramsVec(clock.RealClock{}, time.Millisecond,
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&compbasemetrics.HistogramOpts{
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// ReadWriteConcurrencyPairVec creates gauges of number of requests broken down by phase and mutating vs readonly
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ReadWriteConcurrencyGaugeVec = NewTimingRatioHistogramVec(
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&compbasemetrics.TimingHistogramOpts{
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Namespace: namespace,
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Subsystem: subsystem,
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Name: "read_vs_write_request_count_samples",
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Help: "Periodic observations of the number of requests waiting or in regular stage of execution",
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Buckets: []float64{0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1},
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Name: "read_vs_write_current_requests",
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Help: "Observations, at the end of every nanosecond, of the number of requests (as a fraction of the relevant limit, if max-in-flight filter is being used) waiting or in regular stage of execution",
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Buckets: []float64{0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 0.95, 0.99, 1, 3, 10, 30, 100, 300, 1000, 3000},
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// TODO: something about the utilization vs count irregularity. Issue #109846
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StabilityLevel: compbasemetrics.ALPHA,
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},
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&compbasemetrics.HistogramOpts{
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Namespace: namespace,
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Subsystem: subsystem,
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Name: "read_vs_write_request_count_watermarks",
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Help: "Watermarks of the number of requests waiting or in regular stage of execution",
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Buckets: []float64{0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1},
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StabilityLevel: compbasemetrics.ALPHA,
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},
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[]string{LabelNamePhase, requestKind},
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LabelNamePhase, requestKind,
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)
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apiserverCurrentR = compbasemetrics.NewGaugeVec(
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&compbasemetrics.GaugeOpts{
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@ -1,204 +0,0 @@
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/*
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Copyright 2019 The Kubernetes Authors.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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*/
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package metrics
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import (
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"sync"
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"time"
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compbasemetrics "k8s.io/component-base/metrics"
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"k8s.io/klog/v2"
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"k8s.io/utils/clock"
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)
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const (
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labelNameMark = "mark"
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labelValueLo = "low"
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labelValueHi = "high"
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LabelNamePhase = "phase"
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LabelValueWaiting = "waiting"
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LabelValueExecuting = "executing"
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)
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// SampleAndWaterMarkObserverVec creates RatioedGauges that
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// populate histograms of samples and low- and high-water-marks. The
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// generator has a samplePeriod, and the histograms get an observation
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// every samplePeriod. The sampling windows are quantized based on
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// the monotonic rather than wall-clock times. The `t0` field is
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// there so to provide a baseline for monotonic clock differences.
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type SampleAndWaterMarkObserverVec struct {
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*sampleAndWaterMarkObserverVec
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}
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type sampleAndWaterMarkObserverVec struct {
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clock clock.PassiveClock
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t0 time.Time
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samplePeriod time.Duration
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samples *compbasemetrics.HistogramVec
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waterMarks *compbasemetrics.HistogramVec
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}
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var _ RatioedGaugeVec = SampleAndWaterMarkObserverVec{}
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// NewSampleAndWaterMarkHistogramsVec makes a new one
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func NewSampleAndWaterMarkHistogramsVec(clock clock.PassiveClock, samplePeriod time.Duration, sampleOpts, waterMarkOpts *compbasemetrics.HistogramOpts, labelNames []string) SampleAndWaterMarkObserverVec {
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return SampleAndWaterMarkObserverVec{
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&sampleAndWaterMarkObserverVec{
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clock: clock,
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t0: clock.Now(),
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samplePeriod: samplePeriod,
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samples: compbasemetrics.NewHistogramVec(sampleOpts, labelNames),
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waterMarks: compbasemetrics.NewHistogramVec(waterMarkOpts, append([]string{labelNameMark}, labelNames...)),
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}}
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}
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func (swg *sampleAndWaterMarkObserverVec) quantize(when time.Time) int64 {
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return int64(when.Sub(swg.t0) / swg.samplePeriod)
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}
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// NewForLabelValuesSafe makes a new RatioedGauge
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func (swg *sampleAndWaterMarkObserverVec) NewForLabelValuesSafe(initialNumerator, initialDenominator float64, labelValues []string) RatioedGauge {
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ratio := initialNumerator / initialDenominator
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when := swg.clock.Now()
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return &sampleAndWaterMarkHistograms{
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sampleAndWaterMarkObserverVec: swg,
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labelValues: labelValues,
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loLabelValues: append([]string{labelValueLo}, labelValues...),
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hiLabelValues: append([]string{labelValueHi}, labelValues...),
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denominator: initialDenominator,
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sampleAndWaterMarkAccumulator: sampleAndWaterMarkAccumulator{
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lastSet: when,
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lastSetInt: swg.quantize(when),
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numerator: initialNumerator,
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ratio: ratio,
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loRatio: ratio,
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hiRatio: ratio,
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}}
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}
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func (swg *sampleAndWaterMarkObserverVec) metrics() Registerables {
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return Registerables{swg.samples, swg.waterMarks}
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}
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type sampleAndWaterMarkHistograms struct {
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*sampleAndWaterMarkObserverVec
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labelValues []string
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loLabelValues, hiLabelValues []string
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sync.Mutex
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denominator float64
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sampleAndWaterMarkAccumulator
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}
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type sampleAndWaterMarkAccumulator struct {
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lastSet time.Time
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lastSetInt int64 // lastSet / samplePeriod
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numerator float64
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ratio float64 // numerator/denominator
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loRatio, hiRatio float64
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}
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var _ RatioedGauge = (*sampleAndWaterMarkHistograms)(nil)
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func (saw *sampleAndWaterMarkHistograms) Set(numerator float64) {
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saw.innerSet(func() {
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saw.numerator = numerator
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})
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}
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func (saw *sampleAndWaterMarkHistograms) Add(deltaNumerator float64) {
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saw.innerSet(func() {
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saw.numerator += deltaNumerator
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})
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}
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func (saw *sampleAndWaterMarkHistograms) Sub(deltaNumerator float64) {
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saw.innerSet(func() {
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saw.numerator -= deltaNumerator
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})
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}
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func (saw *sampleAndWaterMarkHistograms) Inc() {
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saw.innerSet(func() {
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saw.numerator += 1
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})
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}
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func (saw *sampleAndWaterMarkHistograms) Dec() {
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saw.innerSet(func() {
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saw.numerator -= 1
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})
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}
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func (saw *sampleAndWaterMarkHistograms) SetToCurrentTime() {
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saw.innerSet(func() {
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saw.numerator = float64(saw.clock.Now().Sub(time.Unix(0, 0)))
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})
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}
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func (saw *sampleAndWaterMarkHistograms) SetDenominator(denominator float64) {
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saw.innerSet(func() {
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saw.denominator = denominator
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})
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}
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func (saw *sampleAndWaterMarkHistograms) innerSet(updateNumeratorOrDenominator func()) {
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when, whenInt, acc, wellOrdered := func() (time.Time, int64, sampleAndWaterMarkAccumulator, bool) {
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saw.Lock()
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defer saw.Unlock()
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// Moved these variables here to tiptoe around https://github.com/golang/go/issues/43570 for #97685
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when := saw.clock.Now()
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whenInt := saw.quantize(when)
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acc := saw.sampleAndWaterMarkAccumulator
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wellOrdered := !when.Before(acc.lastSet)
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updateNumeratorOrDenominator()
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saw.ratio = saw.numerator / saw.denominator
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if wellOrdered {
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if acc.lastSetInt < whenInt {
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saw.loRatio, saw.hiRatio = acc.ratio, acc.ratio
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saw.lastSetInt = whenInt
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}
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saw.lastSet = when
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}
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// `wellOrdered` should always be true because we are using
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// monotonic clock readings and they never go backwards. Yet
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// very small backwards steps (under 1 microsecond) have been
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// observed
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// (https://github.com/kubernetes/kubernetes/issues/96459).
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// In the backwards case, treat the current reading as if it
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// had occurred at time `saw.lastSet` and log an error. It
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// would be wrong to update `saw.lastSet` in this case because
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// that plants a time bomb for future updates to
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// `saw.lastSetInt`.
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if saw.ratio < saw.loRatio {
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saw.loRatio = saw.ratio
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} else if saw.ratio > saw.hiRatio {
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saw.hiRatio = saw.ratio
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}
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return when, whenInt, acc, wellOrdered
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}()
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if !wellOrdered {
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lastSetS := acc.lastSet.String()
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whenS := when.String()
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klog.Errorf("Time went backwards from %s to %s for labelValues=%#+v", lastSetS, whenS, saw.labelValues)
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}
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for acc.lastSetInt < whenInt {
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saw.samples.WithLabelValues(saw.labelValues...).Observe(acc.ratio)
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saw.waterMarks.WithLabelValues(saw.loLabelValues...).Observe(acc.loRatio)
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saw.waterMarks.WithLabelValues(saw.hiLabelValues...).Observe(acc.hiRatio)
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acc.lastSetInt++
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acc.loRatio, acc.hiRatio = acc.ratio, acc.ratio
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}
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}
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@ -1,190 +0,0 @@
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/*
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Copyright 2021 The Kubernetes Authors.
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|
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Licensed under the Apache License, Version 2.0 (the "License");
|
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you may not use this file except in compliance with the License.
|
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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.
|
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*/
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package metrics
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import (
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"errors"
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"fmt"
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"math/rand"
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"testing"
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"time"
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compbasemetrics "k8s.io/component-base/metrics"
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"k8s.io/klog/v2"
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testclock "k8s.io/utils/clock/testing"
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)
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const (
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samplesHistName = "sawtestsamples"
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samplingPeriod = time.Millisecond
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ddtRangeCentiPeriods = 300
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ddtOffsetCentiPeriods = 50
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numIterations = 100
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)
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var errMetricNotFound = errors.New("not found")
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/* TestSampler does a rough behavioral test of the sampling in a
|
||||
SampleAndWatermarkHistograms. The test creates one and exercises
|
||||
it, checking that the count in the sampling histogram is correct at
|
||||
each step. The sampling histogram is expected to get one
|
||||
observation at the end of each sampling period. A fake clock is
|
||||
used, and the exercise consists of repeatedly changing that fake
|
||||
clock by an amount of time chosen uniformly at random from a range
|
||||
that goes from a little negative to somewhat more than two sampling
|
||||
periods. The negative changes are included because small negative
|
||||
changes have been observed in real monotonic clock readings (see
|
||||
issue #96459) and we want to test that they are properly tolerated.
|
||||
The designed toleration is to pretend that the clock did not
|
||||
change, until it resumes net forward progress.
|
||||
*/
|
||||
func TestSampler(t *testing.T) {
|
||||
t0 := time.Now()
|
||||
clk := testclock.NewFakePassiveClock(t0)
|
||||
buckets := []float64{0, 1}
|
||||
gen := NewSampleAndWaterMarkHistogramsVec(clk, samplingPeriod,
|
||||
&compbasemetrics.HistogramOpts{Name: samplesHistName, Buckets: buckets},
|
||||
&compbasemetrics.HistogramOpts{Name: "marks", Buckets: buckets},
|
||||
[]string{})
|
||||
saw := gen.NewForLabelValuesSafe(0, 1, []string{})
|
||||
toRegister := gen.metrics()
|
||||
registry := compbasemetrics.NewKubeRegistry()
|
||||
for _, reg := range toRegister {
|
||||
registry.MustRegister(reg)
|
||||
}
|
||||
// `dt` is the admitted cumulative difference in fake time
|
||||
// since the start of the test. "admitted" means this is
|
||||
// never allowed to decrease, which matches the designed
|
||||
// toleration for negative monotonic clock changes.
|
||||
var dt time.Duration
|
||||
// `t1` is the current fake time
|
||||
t1 := t0.Add(dt)
|
||||
klog.Infof("Expect about %v warnings about time going backwards; this is fake time deliberately misbehaving.", (numIterations*ddtOffsetCentiPeriods)/ddtRangeCentiPeriods)
|
||||
t.Logf("t0=%s", t0)
|
||||
for i := 0; i < numIterations; i++ {
|
||||
// `ddt` is the next step to take in fake time
|
||||
ddt := time.Duration(rand.Intn(ddtRangeCentiPeriods)-ddtOffsetCentiPeriods) * samplingPeriod / 100
|
||||
t1 = t1.Add(ddt)
|
||||
diff := t1.Sub(t0)
|
||||
if diff > dt {
|
||||
dt = diff
|
||||
}
|
||||
clk.SetTime(t1)
|
||||
saw.Set(1)
|
||||
expectedCount := int64(dt / samplingPeriod)
|
||||
actualCount, err := getHistogramCount(registry, samplesHistName)
|
||||
if err != nil && !(err == errMetricNotFound && expectedCount == 0) {
|
||||
t.Fatalf("For t0=%s, t1=%s, failed to getHistogramCount: %#+v", t0, t1, err)
|
||||
}
|
||||
t.Logf("For i=%d, ddt=%s, t1=%s, diff=%s, dt=%s, count=%d", i, ddt, t1, diff, dt, actualCount)
|
||||
if expectedCount != actualCount {
|
||||
t.Errorf("For i=%d, t0=%s, ddt=%s, t1=%s, expectedCount=%d, actualCount=%d", i, t0, ddt, t1, expectedCount, actualCount)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/* getHistogramCount returns the count of the named histogram or an error (if any) */
|
||||
func getHistogramCount(registry compbasemetrics.KubeRegistry, metricName string) (int64, error) {
|
||||
mfs, err := registry.Gather()
|
||||
if err != nil {
|
||||
return 0, fmt.Errorf("failed to gather metrics: %w", err)
|
||||
}
|
||||
for _, mf := range mfs {
|
||||
thisName := mf.GetName()
|
||||
if thisName != metricName {
|
||||
continue
|
||||
}
|
||||
metric := mf.GetMetric()[0]
|
||||
hist := metric.GetHistogram()
|
||||
if hist == nil {
|
||||
return 0, errors.New("dto.Metric has nil Histogram")
|
||||
}
|
||||
if hist.SampleCount == nil {
|
||||
return 0, errors.New("dto.Histogram has nil SampleCount")
|
||||
}
|
||||
return int64(*hist.SampleCount), nil
|
||||
}
|
||||
return 0, errMetricNotFound
|
||||
}
|
||||
|
||||
func BenchmarkSampleAndWaterMarkHistogramsVecEltSafeEarly(b *testing.B) {
|
||||
b.StopTimer()
|
||||
now := time.Now()
|
||||
clk := testclock.NewFakePassiveClock(now)
|
||||
thv := NewSampleAndWaterMarkHistogramsVec(clk, time.Millisecond,
|
||||
&compbasemetrics.HistogramOpts{
|
||||
Namespace: "testns",
|
||||
Subsystem: "testsubsys",
|
||||
Name: "samplehist",
|
||||
Help: "Me",
|
||||
Buckets: []float64{1, 2, 4, 8, 16, 32},
|
||||
},
|
||||
&compbasemetrics.HistogramOpts{
|
||||
Namespace: "testns",
|
||||
Subsystem: "testsubsys",
|
||||
Name: "markhist",
|
||||
Help: "Me",
|
||||
Buckets: []float64{1, 2, 4, 8, 16, 32},
|
||||
},
|
||||
[]string{"labelname"})
|
||||
th := thv.NewForLabelValuesSafe(0, 3, []string{"labelvalue"})
|
||||
registry := compbasemetrics.NewKubeRegistry()
|
||||
registry.MustRegister(thv.metrics()...)
|
||||
var x int
|
||||
b.StartTimer()
|
||||
for i := 0; i < b.N; i++ {
|
||||
delta := (i % 6) + 1
|
||||
now = now.Add(time.Duration(delta) * time.Millisecond)
|
||||
clk.SetTime(now)
|
||||
th.Set(float64(x))
|
||||
x = (x + i) % 60
|
||||
}
|
||||
}
|
||||
|
||||
func BenchmarkSampleAndWaterMarkHistogramsVecEltSafeLate(b *testing.B) {
|
||||
b.StopTimer()
|
||||
now := time.Now()
|
||||
clk := testclock.NewFakePassiveClock(now)
|
||||
thv := NewSampleAndWaterMarkHistogramsVec(clk, time.Millisecond,
|
||||
&compbasemetrics.HistogramOpts{
|
||||
Namespace: "testns",
|
||||
Subsystem: "testsubsys",
|
||||
Name: "samplehist",
|
||||
Help: "Me",
|
||||
Buckets: []float64{1, 2, 4, 8, 16, 32},
|
||||
},
|
||||
&compbasemetrics.HistogramOpts{
|
||||
Namespace: "testns",
|
||||
Subsystem: "testsubsys",
|
||||
Name: "markhist",
|
||||
Help: "Me",
|
||||
Buckets: []float64{1, 2, 4, 8, 16, 32},
|
||||
},
|
||||
[]string{"labelname"})
|
||||
registry := compbasemetrics.NewKubeRegistry()
|
||||
registry.MustRegister(thv.metrics()...)
|
||||
th := thv.NewForLabelValuesSafe(0, 3, []string{"labelvalue"})
|
||||
var x int
|
||||
b.StartTimer()
|
||||
for i := 0; i < b.N; i++ {
|
||||
delta := (i % 6) + 1
|
||||
now = now.Add(time.Duration(delta) * time.Millisecond)
|
||||
clk.SetTime(now)
|
||||
th.Set(float64(x))
|
||||
x = (x + i) % 60
|
||||
}
|
||||
}
|
||||
@ -17,6 +17,8 @@ limitations under the License.
|
||||
package metrics
|
||||
|
||||
import (
|
||||
"errors"
|
||||
"fmt"
|
||||
"math/rand"
|
||||
"testing"
|
||||
"time"
|
||||
@ -26,6 +28,14 @@ import (
|
||||
testclock "k8s.io/utils/clock/testing"
|
||||
)
|
||||
|
||||
const (
|
||||
ddtRangeCentiPeriods = 300
|
||||
ddtOffsetCentiPeriods = 50
|
||||
numIterations = 100
|
||||
)
|
||||
|
||||
var errMetricNotFound = errors.New("not found")
|
||||
|
||||
func TestTimingRatioHistogramVecElementSimple(t *testing.T) {
|
||||
testHistogramName := "vec_element_simple"
|
||||
t0 := time.Now()
|
||||
@ -130,6 +140,30 @@ func exerciseTimingRatioHistogram(t *testing.T, histogramName string, t0 time.Ti
|
||||
}
|
||||
}
|
||||
|
||||
/* getHistogramCount returns the count of the named histogram or an error (if any) */
|
||||
func getHistogramCount(registry compbasemetrics.KubeRegistry, metricName string) (int64, error) {
|
||||
mfs, err := registry.Gather()
|
||||
if err != nil {
|
||||
return 0, fmt.Errorf("failed to gather metrics: %w", err)
|
||||
}
|
||||
for _, mf := range mfs {
|
||||
thisName := mf.GetName()
|
||||
if thisName != metricName {
|
||||
continue
|
||||
}
|
||||
metric := mf.GetMetric()[0]
|
||||
hist := metric.GetHistogram()
|
||||
if hist == nil {
|
||||
return 0, errors.New("dto.Metric has nil Histogram")
|
||||
}
|
||||
if hist.SampleCount == nil {
|
||||
return 0, errors.New("dto.Histogram has nil SampleCount")
|
||||
}
|
||||
return int64(*hist.SampleCount), nil
|
||||
}
|
||||
return 0, errMetricNotFound
|
||||
}
|
||||
|
||||
func BenchmarkTimingRatioHistogram(b *testing.B) {
|
||||
b.StopTimer()
|
||||
now := time.Now()
|
||||
|
||||
Loading…
Reference in New Issue
Block a user