|
| 1 | +/* |
| 2 | +Copyright 2025 Flant JSC |
| 3 | +
|
| 4 | +Licensed under the Apache License, Version 2.0 (the "License"); |
| 5 | +you may not use this file except in compliance with the License. |
| 6 | +You may obtain a copy of the License at |
| 7 | +
|
| 8 | + http://www.apache.org/licenses/LICENSE-2.0 |
| 9 | +
|
| 10 | +Unless required by applicable law or agreed to in writing, software |
| 11 | +distributed under the License is distributed on an "AS IS" BASIS, |
| 12 | +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| 13 | +See the License for the specific language governing permissions and |
| 14 | +limitations under the License. |
| 15 | +*/ |
| 16 | + |
| 17 | +package metrics |
| 18 | + |
| 19 | +import ( |
| 20 | + "fmt" |
| 21 | + "slices" |
| 22 | + "time" |
| 23 | + |
| 24 | + "github.com/deckhouse/dmt/internal/promremote" |
| 25 | +) |
| 26 | + |
| 27 | +// GetTimeSeries converts Prometheus metric families to a map of promremote.TimeSeries |
| 28 | +// where the key is the metric name and the value is a slice of time series for that metric |
| 29 | +func (p *PrometheusMetricsService) GetTimeSeries() []promremote.TimeSeries { |
| 30 | + var series []promremote.TimeSeries |
| 31 | + |
| 32 | + metricFamilies, err := p.Gatherer.Gather() |
| 33 | + if err != nil { |
| 34 | + return nil |
| 35 | + } |
| 36 | + // Store timestamp for consistent use across series |
| 37 | + timestamp := time.Now() |
| 38 | + |
| 39 | + for _, metricFamily := range metricFamilies { |
| 40 | + metricName := metricFamily.GetName() |
| 41 | + for _, metric := range metricFamily.Metric { |
| 42 | + // Create labels from the metric's label pairs |
| 43 | + labels := make([]promremote.Label, 0, len(metric.Label)+1) // +1 for the name label |
| 44 | + for _, labelPair := range metric.Label { |
| 45 | + labels = append(labels, promremote.Label{ |
| 46 | + Name: labelPair.GetName(), |
| 47 | + Value: labelPair.GetValue(), |
| 48 | + }) |
| 49 | + } |
| 50 | + |
| 51 | + // Extract value based on metric type |
| 52 | + switch { |
| 53 | + case metric.GetCounter() != nil: |
| 54 | + // Add counter as a single time series |
| 55 | + counterLabels := slices.Clone(labels) |
| 56 | + counterLabels = append(counterLabels, promremote.Label{ |
| 57 | + Name: "__name__", |
| 58 | + Value: metricName, |
| 59 | + }) |
| 60 | + |
| 61 | + series = append(series, promremote.TimeSeries{ |
| 62 | + Labels: counterLabels, |
| 63 | + Datapoint: promremote.Datapoint{ |
| 64 | + Timestamp: timestamp, |
| 65 | + Value: metric.GetCounter().GetValue(), |
| 66 | + }, |
| 67 | + }) |
| 68 | + |
| 69 | + case metric.GetGauge() != nil: |
| 70 | + // Add gauge as a single time series |
| 71 | + gaugeLabels := slices.Clone(labels) |
| 72 | + gaugeLabels = append(gaugeLabels, promremote.Label{ |
| 73 | + Name: "__name__", |
| 74 | + Value: metricName, |
| 75 | + }) |
| 76 | + |
| 77 | + series = append(series, promremote.TimeSeries{ |
| 78 | + Labels: gaugeLabels, |
| 79 | + Datapoint: promremote.Datapoint{ |
| 80 | + Timestamp: timestamp, |
| 81 | + Value: metric.GetGauge().GetValue(), |
| 82 | + }, |
| 83 | + }) |
| 84 | + |
| 85 | + case metric.GetHistogram() != nil: |
| 86 | + histogram := metric.GetHistogram() |
| 87 | + |
| 88 | + // 1. Add sum time series |
| 89 | + sumLabels := slices.Clone(labels) |
| 90 | + sumLabels = append(sumLabels, promremote.Label{ |
| 91 | + Name: "__name__", |
| 92 | + Value: metricName + "_sum", |
| 93 | + }) |
| 94 | + |
| 95 | + series = append(series, promremote.TimeSeries{ |
| 96 | + Labels: sumLabels, |
| 97 | + Datapoint: promremote.Datapoint{ |
| 98 | + Timestamp: timestamp, |
| 99 | + Value: histogram.GetSampleSum(), |
| 100 | + }, |
| 101 | + }) |
| 102 | + |
| 103 | + // 2. Add count time series |
| 104 | + countLabels := slices.Clone(labels) |
| 105 | + countLabels = append(countLabels, promremote.Label{ |
| 106 | + Name: "__name__", |
| 107 | + Value: metricName + "_count", |
| 108 | + }) |
| 109 | + |
| 110 | + series = append(series, promremote.TimeSeries{ |
| 111 | + Labels: countLabels, |
| 112 | + Datapoint: promremote.Datapoint{ |
| 113 | + Timestamp: timestamp, |
| 114 | + Value: float64(histogram.GetSampleCount()), |
| 115 | + }, |
| 116 | + }) |
| 117 | + |
| 118 | + // 3. Add bucket time series |
| 119 | + for _, bucket := range histogram.GetBucket() { |
| 120 | + bucketLabels := slices.Clone(labels) |
| 121 | + bucketLabels = append(bucketLabels, |
| 122 | + promremote.Label{ |
| 123 | + Name: "le", |
| 124 | + Value: fmt.Sprintf("%g", bucket.GetUpperBound()), |
| 125 | + }, |
| 126 | + promremote.Label{ |
| 127 | + Name: "__name__", |
| 128 | + Value: metricName + "_bucket", |
| 129 | + }, |
| 130 | + ) |
| 131 | + |
| 132 | + series = append(series, promremote.TimeSeries{ |
| 133 | + Labels: bucketLabels, |
| 134 | + Datapoint: promremote.Datapoint{ |
| 135 | + Timestamp: timestamp, |
| 136 | + Value: float64(bucket.GetCumulativeCount()), |
| 137 | + }, |
| 138 | + }) |
| 139 | + } |
| 140 | + |
| 141 | + case metric.GetSummary() != nil: |
| 142 | + summary := metric.GetSummary() |
| 143 | + |
| 144 | + // 1. Add sum time series |
| 145 | + sumLabels := slices.Clone(labels) |
| 146 | + sumLabels = append(sumLabels, promremote.Label{ |
| 147 | + Name: "__name__", |
| 148 | + Value: metricName + "_sum", |
| 149 | + }) |
| 150 | + |
| 151 | + series = append(series, promremote.TimeSeries{ |
| 152 | + Labels: sumLabels, |
| 153 | + Datapoint: promremote.Datapoint{ |
| 154 | + Timestamp: timestamp, |
| 155 | + Value: summary.GetSampleSum(), |
| 156 | + }, |
| 157 | + }) |
| 158 | + |
| 159 | + // 2. Add count time series |
| 160 | + countLabels := slices.Clone(labels) |
| 161 | + countLabels = append(countLabels, promremote.Label{ |
| 162 | + Name: "__name__", |
| 163 | + Value: metricName + "_count", |
| 164 | + }) |
| 165 | + |
| 166 | + series = append(series, promremote.TimeSeries{ |
| 167 | + Labels: countLabels, |
| 168 | + Datapoint: promremote.Datapoint{ |
| 169 | + Timestamp: timestamp, |
| 170 | + Value: float64(summary.GetSampleCount()), |
| 171 | + }, |
| 172 | + }) |
| 173 | + |
| 174 | + // 3. Add quantile time series |
| 175 | + for _, quantile := range summary.GetQuantile() { |
| 176 | + quantileLabels := slices.Clone(labels) |
| 177 | + quantileLabels = append(quantileLabels, |
| 178 | + promremote.Label{ |
| 179 | + Name: "quantile", |
| 180 | + Value: fmt.Sprintf("%g", quantile.GetQuantile()), |
| 181 | + }, |
| 182 | + promremote.Label{ |
| 183 | + Name: "__name__", |
| 184 | + Value: metricName, |
| 185 | + }, |
| 186 | + ) |
| 187 | + |
| 188 | + series = append(series, promremote.TimeSeries{ |
| 189 | + Labels: quantileLabels, |
| 190 | + Datapoint: promremote.Datapoint{ |
| 191 | + Timestamp: timestamp, |
| 192 | + Value: quantile.GetValue(), |
| 193 | + }, |
| 194 | + }) |
| 195 | + } |
| 196 | + } |
| 197 | + } |
| 198 | + } |
| 199 | + |
| 200 | + return series |
| 201 | +} |
0 commit comments