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[datadogexporter] Implement translation of metrics to Datadog format (#…
…1178) * Add metrics translation functions * Improve docs and make newGauge private * Add basic hostname resolution This will be expanded in the future to more closely replicate the Datadog Agent behavior * Remove Series struct and use []datadog.Metric We can add it back if necessary in the future
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,32 @@ | ||
| // Copyright The OpenTelemetry 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 datadogexporter | ||
|
|
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| import "os" | ||
|
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| // GetHost gets the hostname according to configuration. | ||
| // It gets the configuration hostname and if | ||
| // not available it relies on the OS hostname | ||
| func GetHost(cfg *Config) *string { | ||
| if cfg.TagsConfig.Hostname != "" { | ||
| return &cfg.TagsConfig.Hostname | ||
| } | ||
|
|
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| host, err := os.Hostname() | ||
| if err != nil || host == "" { | ||
| host = "unknown" | ||
| } | ||
| return &host | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,34 @@ | ||
| // Copyright The OpenTelemetry 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. | ||
|
|
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| package datadogexporter | ||
|
|
||
| import ( | ||
| "os" | ||
| "testing" | ||
|
|
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| "github.com/stretchr/testify/assert" | ||
| "github.com/stretchr/testify/require" | ||
| ) | ||
|
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| func TestHost(t *testing.T) { | ||
|
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| host := GetHost(&Config{TagsConfig: TagsConfig{Hostname: "test_host"}}) | ||
| assert.Equal(t, *host, "test_host") | ||
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| host = GetHost(&Config{}) | ||
| osHostname, err := os.Hostname() | ||
| require.NoError(t, err) | ||
| assert.Equal(t, *host, osHostname) | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,214 @@ | ||
| // Copyright The OpenTelemetry 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. | ||
|
|
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| package datadogexporter | ||
|
|
||
| import ( | ||
| "fmt" | ||
|
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| "go.opentelemetry.io/collector/consumer/pdata" | ||
| "go.uber.org/zap" | ||
| "gopkg.in/zorkian/go-datadog-api.v2" | ||
| ) | ||
|
|
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| const ( | ||
| // Gauge is the Datadog Gauge metric type | ||
| Gauge string = "gauge" | ||
| ) | ||
|
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| // newGauge creates a new Datadog Gauge metric given a name, a Unix nanoseconds timestamp | ||
| // a value and a slice of tags | ||
| func newGauge(name string, ts uint64, value float64, tags []string) datadog.Metric { | ||
| // Transform UnixNano timestamp into Unix timestamp | ||
| // 1 second = 1e9 ns | ||
| timestamp := float64(ts / 1e9) | ||
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| gauge := datadog.Metric{ | ||
| Points: []datadog.DataPoint{[2]*float64{×tamp, &value}}, | ||
| Tags: tags, | ||
| } | ||
| gauge.SetMetric(name) | ||
| gauge.SetType(Gauge) | ||
| return gauge | ||
| } | ||
|
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| // getTags maps a stringMap into a slice of Datadog tags | ||
| func getTags(labels pdata.StringMap) []string { | ||
| tags := make([]string, 0, labels.Len()) | ||
| labels.ForEach(func(key string, v pdata.StringValue) { | ||
| value := v.Value() | ||
| if value == "" { | ||
| // Tags can't end with ":" so we replace empty values with "n/a" | ||
| value = "n/a" | ||
| } | ||
| tags = append(tags, fmt.Sprintf("%s:%s", key, value)) | ||
| }) | ||
| return tags | ||
| } | ||
|
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| // mapIntMetrics maps int datapoints into Datadog metrics | ||
| func mapIntMetrics(name string, slice pdata.IntDataPointSlice) []datadog.Metric { | ||
| // Allocate assuming none are nil | ||
| metrics := make([]datadog.Metric, 0, slice.Len()) | ||
| for i := 0; i < slice.Len(); i++ { | ||
| p := slice.At(i) | ||
| if p.IsNil() { | ||
| continue | ||
| } | ||
| metrics = append(metrics, | ||
| newGauge(name, uint64(p.Timestamp()), float64(p.Value()), getTags(p.LabelsMap())), | ||
| ) | ||
| } | ||
| return metrics | ||
| } | ||
|
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| // mapDoubleMetrics maps double datapoints into Datadog metrics | ||
| func mapDoubleMetrics(name string, slice pdata.DoubleDataPointSlice) []datadog.Metric { | ||
| // Allocate assuming none are nil | ||
| metrics := make([]datadog.Metric, 0, slice.Len()) | ||
| for i := 0; i < slice.Len(); i++ { | ||
| p := slice.At(i) | ||
| if p.IsNil() { | ||
| continue | ||
| } | ||
| metrics = append(metrics, | ||
| newGauge(name, uint64(p.Timestamp()), float64(p.Value()), getTags(p.LabelsMap())), | ||
| ) | ||
| } | ||
| return metrics | ||
| } | ||
|
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| // mapIntHistogramMetrics maps histogram metrics slices to Datadog metrics | ||
| // | ||
| // A Histogram metric has: | ||
| // - The count of values in the population | ||
| // - The sum of values in the population | ||
| // - A number of buckets, each of them having | ||
| // - the bounds that define the bucket | ||
| // - the count of the number of items in that bucket | ||
| // - a sample value from each bucket | ||
| // | ||
| // We follow a similar approach to our OpenCensus exporter: | ||
| // we report sum and count by default; buckets count can also | ||
| // be reported (opt-in), but bounds are ignored. | ||
| func mapIntHistogramMetrics(name string, slice pdata.IntHistogramDataPointSlice, buckets bool) []datadog.Metric { | ||
| // Allocate assuming none are nil and no buckets | ||
| metrics := make([]datadog.Metric, 0, 2*slice.Len()) | ||
| for i := 0; i < slice.Len(); i++ { | ||
| p := slice.At(i) | ||
| if p.IsNil() { | ||
| continue | ||
| } | ||
| ts := uint64(p.Timestamp()) | ||
| tags := getTags(p.LabelsMap()) | ||
|
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| metrics = append(metrics, | ||
| newGauge(fmt.Sprintf("%s.count", name), ts, float64(p.Count()), tags), | ||
| newGauge(fmt.Sprintf("%s.sum", name), ts, float64(p.Sum()), tags), | ||
| ) | ||
|
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| if buckets { | ||
| // We have a single metric, 'count_per_bucket', which is tagged with the bucket id. See: | ||
| // https://github.com/DataDog/opencensus-go-exporter-datadog/blob/c3b47f1c6dcf1c47b59c32e8dbb7df5f78162daa/stats.go#L99-L104 | ||
| fullName := fmt.Sprintf("%s.count_per_bucket", name) | ||
| for idx, count := range p.BucketCounts() { | ||
| bucketTags := append(tags, fmt.Sprintf("bucket_idx:%d", idx)) | ||
| metrics = append(metrics, | ||
| newGauge(fullName, ts, float64(count), bucketTags), | ||
| ) | ||
| } | ||
| } | ||
| } | ||
| return metrics | ||
| } | ||
|
|
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| // mapIntHistogramMetrics maps double histogram metrics slices to Datadog metrics | ||
| // | ||
| // see mapIntHistogramMetrics docs for further details. | ||
| func mapDoubleHistogramMetrics(name string, slice pdata.DoubleHistogramDataPointSlice, buckets bool) []datadog.Metric { | ||
| // Allocate assuming none are nil and no buckets | ||
| metrics := make([]datadog.Metric, 0, 2*slice.Len()) | ||
| for i := 0; i < slice.Len(); i++ { | ||
| p := slice.At(i) | ||
| if p.IsNil() { | ||
| continue | ||
| } | ||
| ts := uint64(p.Timestamp()) | ||
| tags := getTags(p.LabelsMap()) | ||
|
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| metrics = append(metrics, | ||
| newGauge(fmt.Sprintf("%s.count", name), ts, float64(p.Count()), tags), | ||
| newGauge(fmt.Sprintf("%s.sum", name), ts, float64(p.Sum()), tags), | ||
| ) | ||
|
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| if buckets { | ||
| // We have a single metric, 'count_per_bucket', which is tagged with the bucket id. See: | ||
| // https://github.com/DataDog/opencensus-go-exporter-datadog/blob/c3b47f1c6dcf1c47b59c32e8dbb7df5f78162daa/stats.go#L99-L104 | ||
| fullName := fmt.Sprintf("%s.count_per_bucket", name) | ||
| for idx, count := range p.BucketCounts() { | ||
| bucketTags := append(tags, fmt.Sprintf("bucket_idx:%d", idx)) | ||
| metrics = append(metrics, | ||
| newGauge(fullName, ts, float64(count), bucketTags), | ||
| ) | ||
| } | ||
| } | ||
| } | ||
| return metrics | ||
| } | ||
|
|
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| // MapMetrics maps OTLP metrics into the DataDog format | ||
| func MapMetrics(logger *zap.Logger, cfg MetricsConfig, md pdata.Metrics) (series []datadog.Metric, droppedTimeSeries int) { | ||
| rms := md.ResourceMetrics() | ||
| for i := 0; i < rms.Len(); i++ { | ||
| rm := rms.At(i) | ||
| if rm.IsNil() { | ||
| continue | ||
| } | ||
| ilms := rm.InstrumentationLibraryMetrics() | ||
| for j := 0; j < ilms.Len(); j++ { | ||
| ilm := ilms.At(j) | ||
| if ilm.IsNil() { | ||
| continue | ||
| } | ||
| metrics := ilm.Metrics() | ||
| for k := 0; k < metrics.Len(); k++ { | ||
| md := metrics.At(k) | ||
| if md.IsNil() { | ||
| continue | ||
| } | ||
| var datapoints []datadog.Metric | ||
| switch md.DataType() { | ||
| case pdata.MetricDataTypeNone: | ||
| continue | ||
| case pdata.MetricDataTypeIntGauge: | ||
| datapoints = mapIntMetrics(md.Name(), md.IntGauge().DataPoints()) | ||
| case pdata.MetricDataTypeDoubleGauge: | ||
| datapoints = mapDoubleMetrics(md.Name(), md.DoubleGauge().DataPoints()) | ||
| case pdata.MetricDataTypeIntSum: | ||
| // Ignore aggregation temporality; report raw values | ||
| datapoints = mapIntMetrics(md.Name(), md.IntSum().DataPoints()) | ||
| case pdata.MetricDataTypeDoubleSum: | ||
| // Ignore aggregation temporality; report raw values | ||
| datapoints = mapDoubleMetrics(md.Name(), md.DoubleSum().DataPoints()) | ||
| case pdata.MetricDataTypeIntHistogram: | ||
| datapoints = mapIntHistogramMetrics(md.Name(), md.IntHistogram().DataPoints(), cfg.Buckets) | ||
| case pdata.MetricDataTypeDoubleHistogram: | ||
| datapoints = mapDoubleHistogramMetrics(md.Name(), md.DoubleHistogram().DataPoints(), cfg.Buckets) | ||
| } | ||
| series = append(series, datapoints...) | ||
| } | ||
| } | ||
| } | ||
| return | ||
| } |
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