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lib/protoparser: adds opentelemetry parser (#2570)
* lib/protoparser: adds opentelemetry parser
app/{vmagent,vminsert}: adds opentelemetry ingestion path
Adds ability to ingest data with opentelemetry protocol
protobuf and json encoding is supported
data converted into prometheus protobuf timeseries
each data type has own converter and it may produce multiple timeseries
from single datapoint (for summary and histogram).
only cumulative aggregationFamily is supported for sum(prometheus
counter) and histogram.
Apply suggestions from code review
Co-authored-by: Roman Khavronenko <roman@victoriametrics.com>
updates deps
fixes tests
wip
wip
wip
wip
lib/protoparser/opentelemetry: moves to vtprotobuf generator
go mod vendor
lib/protoparse/opentelemetry: reduce memory allocations
* wip
- Remove support for JSON parsing, since it is too fragile and is rarely used in practice.
The most clients send OpenTelemetry metrics in protobuf.
The JSON parser can be added in the future if needed.
- Remove unused code from lib/protoparser/opentelemetry/pb and lib/protoparser/opentelemetry/proto
- Do not re-use protobuf message between ParseStream() calls, since there is high chance
of high fragmentation of the re-used message because of too complex nested structure of the message.
* wip
* wip
* wip
---------
Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
This commit is contained in:
Nikolay
GitHub
parent
584400c2f0
commit
46ecbbea26
@ -86,6 +86,7 @@ VictoriaMetrics has the following prominent features:
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* [Arbitrary CSV data](#how-to-import-csv-data).
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* [Native binary format](#how-to-import-data-in-native-format).
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* [DataDog agent or DogStatsD](#how-to-send-data-from-datadog-agent).
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* [OpenTelemetry metrics format](#sending-data-via-opentelemetry).
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* It supports powerful [stream aggregation](https://docs.victoriametrics.com/stream-aggregation.html), which can be used as a [statsd](https://github.com/statsd/statsd) alternative.
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* It supports metrics [relabeling](#relabeling).
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* It can deal with [high cardinality issues](https://docs.victoriametrics.com/FAQ.html#what-is-high-cardinality) and
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@ -1173,6 +1174,7 @@ Additionally, VictoriaMetrics can accept metrics via the following popular data
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* DataDog `submit metrics` API. See [these docs](#how-to-send-data-from-datadog-agent) for details.
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* InfluxDB line protocol. See [these docs](#how-to-send-data-from-influxdb-compatible-agents-such-as-telegraf) for details.
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* Graphite plaintext protocol. See [these docs](#how-to-send-data-from-graphite-compatible-agents-such-as-statsd) for details.
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* OpenTelemetry http API. See [these docs](#sending-data-via-opentelemetry) for details.
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* OpenTSDB telnet put protocol. See [these docs](#sending-data-via-telnet-put-protocol) for details.
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* OpenTSDB http `/api/put` protocol. See [these docs](#sending-opentsdb-data-via-http-apiput-requests) for details.
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* `/api/v1/import` for importing data obtained from [/api/v1/export](#how-to-export-data-in-json-line-format).
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@ -1356,6 +1358,13 @@ Note that it could be required to flush response cache after importing historica
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VictoriaMetrics also may scrape Prometheus targets - see [these docs](#how-to-scrape-prometheus-exporters-such-as-node-exporter).
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## Sending data via OpenTelemetry
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VictoriaMetrics supports data ingestion via [OpenTelemetry protocol for metrics](https://github.com/open-telemetry/opentelemetry-specification/blob/ffddc289462dfe0c2041e3ca42a7b1df805706de/specification/metrics/data-model.md) at `/opentemetry/api/v1/push` path.
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VictoriaMetrics expects `protobuf`-encoded requests at `/opentelemetry/api/v1/push`.
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Set HTTP request header `Content-Encoding: gzip` when sending gzip-compressed data to `/opentelemetry/api/v1/push`.
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## Relabeling
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VictoriaMetrics supports Prometheus-compatible relabeling for all the ingested metrics if `-relabelConfig` command-line flag points
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@ -93,6 +93,7 @@ additionally to pull-based Prometheus-compatible targets' scraping:
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* DataDog "submit metrics" API. See [these docs](https://docs.victoriametrics.com/Single-server-VictoriaMetrics.html#how-to-send-data-from-datadog-agent).
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* InfluxDB line protocol via `http://<vmagent>:8429/write`. See [these docs](https://docs.victoriametrics.com/Single-server-VictoriaMetrics.html#how-to-send-data-from-influxdb-compatible-agents-such-as-telegraf).
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* Graphite plaintext protocol if `-graphiteListenAddr` command-line flag is set. See [these docs](https://docs.victoriametrics.com/Single-server-VictoriaMetrics.html#how-to-send-data-from-graphite-compatible-agents-such-as-statsd).
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* OpenTelemetry http API. See [these docs](https://docs.victoriametrics.com/Single-server-VictoriaMetrics.html#sending-data-via-opentelemetry).
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* OpenTSDB telnet and http protocols if `-opentsdbListenAddr` command-line flag is set. See [these docs](https://docs.victoriametrics.com/Single-server-VictoriaMetrics.html#how-to-send-data-from-opentsdb-compatible-agents).
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* Prometheus remote write protocol via `http://<vmagent>:8429/api/v1/write`.
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* JSON lines import protocol via `http://<vmagent>:8429/api/v1/import`. See [these docs](https://docs.victoriametrics.com/Single-server-VictoriaMetrics.html#how-to-import-data-in-json-line-format).
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@ -16,6 +16,7 @@ import (
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"github.com/VictoriaMetrics/VictoriaMetrics/app/vmagent/graphite"
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"github.com/VictoriaMetrics/VictoriaMetrics/app/vmagent/influx"
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"github.com/VictoriaMetrics/VictoriaMetrics/app/vmagent/native"
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"github.com/VictoriaMetrics/VictoriaMetrics/app/vmagent/opentelemetry"
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"github.com/VictoriaMetrics/VictoriaMetrics/app/vmagent/opentsdb"
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"github.com/VictoriaMetrics/VictoriaMetrics/app/vmagent/opentsdbhttp"
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"github.com/VictoriaMetrics/VictoriaMetrics/app/vmagent/prometheusimport"
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@ -308,6 +309,15 @@ func requestHandler(w http.ResponseWriter, r *http.Request) bool {
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influxQueryRequests.Inc()
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influxutils.WriteDatabaseNames(w)
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return true
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case "/opentelemetry/api/v1/push":
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opentelemetryPushRequests.Inc()
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if err := opentelemetry.InsertHandler(nil, r); err != nil {
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opentelemetryPushErrors.Inc()
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httpserver.Errorf(w, r, "%s", err)
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return true
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}
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w.WriteHeader(http.StatusOK)
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return true
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case "/datadog/api/v1/series":
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datadogWriteRequests.Inc()
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if err := datadog.InsertHandlerForHTTP(nil, r); err != nil {
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@ -499,6 +509,15 @@ func processMultitenantRequest(w http.ResponseWriter, r *http.Request, path stri
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influxQueryRequests.Inc()
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influxutils.WriteDatabaseNames(w)
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return true
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case "opentelemetry/api/v1/push":
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opentelemetryPushRequests.Inc()
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if err := opentelemetry.InsertHandler(at, r); err != nil {
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opentelemetryPushErrors.Inc()
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httpserver.Errorf(w, r, "%s", err)
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return true
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}
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w.WriteHeader(http.StatusOK)
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return true
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case "datadog/api/v1/series":
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datadogWriteRequests.Inc()
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if err := datadog.InsertHandlerForHTTP(at, r); err != nil {
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@ -568,6 +587,9 @@ var (
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datadogIntakeRequests = metrics.NewCounter(`vmagent_http_requests_total{path="/datadog/intake", protocol="datadog"}`)
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datadogMetadataRequests = metrics.NewCounter(`vmagent_http_requests_total{path="/datadog/api/v1/metadata", protocol="datadog"}`)
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opentelemetryPushRequests = metrics.NewCounter(`vmagent_http_requests_total{path="/opentelemetry/api/v1/push", protocol="opentelemetry"}`)
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opentelemetryPushErrors = metrics.NewCounter(`vmagent_http_request_errors_total{path="/opentelemetry/api/v1/push", protocol="opentelemetry"}`)
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promscrapeTargetsRequests = metrics.NewCounter(`vmagent_http_requests_total{path="/targets"}`)
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promscrapeServiceDiscoveryRequests = metrics.NewCounter(`vmagent_http_requests_total{path="/service-discovery"}`)
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65
app/vmagent/opentelemetry/request_handler.go
Normal file
65
app/vmagent/opentelemetry/request_handler.go
Normal file
@ -0,0 +1,65 @@
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package opentelemetry
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import (
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"net/http"
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"github.com/VictoriaMetrics/VictoriaMetrics/app/vmagent/common"
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"github.com/VictoriaMetrics/VictoriaMetrics/app/vmagent/remotewrite"
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"github.com/VictoriaMetrics/VictoriaMetrics/lib/auth"
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"github.com/VictoriaMetrics/VictoriaMetrics/lib/prompbmarshal"
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parserCommon "github.com/VictoriaMetrics/VictoriaMetrics/lib/protoparser/common"
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"github.com/VictoriaMetrics/VictoriaMetrics/lib/protoparser/opentelemetry/stream"
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"github.com/VictoriaMetrics/VictoriaMetrics/lib/tenantmetrics"
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"github.com/VictoriaMetrics/metrics"
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)
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var (
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rowsInserted = metrics.NewCounter(`vmagent_rows_inserted_total{type="opentelemetry"}`)
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rowsTenantInserted = tenantmetrics.NewCounterMap(`vmagent_tenant_inserted_rows_total{type="opentelemetry"}`)
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rowsPerInsert = metrics.NewHistogram(`vmagent_rows_per_insert{type="opentelemetry"}`)
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)
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// InsertHandler processes opentelemetry metrics.
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func InsertHandler(at *auth.Token, req *http.Request) error {
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extraLabels, err := parserCommon.GetExtraLabels(req)
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if err != nil {
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return err
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}
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isGzipped := req.Header.Get("Content-Encoding") == "gzip"
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return stream.ParseStream(req.Body, isGzipped, func(tss []prompbmarshal.TimeSeries) error {
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return insertRows(at, tss, extraLabels)
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})
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}
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func insertRows(at *auth.Token, tss []prompbmarshal.TimeSeries, extraLabels []prompbmarshal.Label) error {
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ctx := common.GetPushCtx()
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defer common.PutPushCtx(ctx)
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rowsTotal := 0
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tssDst := ctx.WriteRequest.Timeseries[:0]
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labels := ctx.Labels[:0]
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samples := ctx.Samples[:0]
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for i := range tss {
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ts := &tss[i]
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rowsTotal += len(ts.Samples)
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labelsLen := len(labels)
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labels = append(labels, ts.Labels...)
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labels = append(labels, extraLabels...)
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samplesLen := len(samples)
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samples = append(samples, ts.Samples...)
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tssDst = append(tssDst, prompbmarshal.TimeSeries{
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Labels: labels[labelsLen:],
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Samples: samples[samplesLen:],
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})
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}
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ctx.WriteRequest.Timeseries = tssDst
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ctx.Labels = labels
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ctx.Samples = samples
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remotewrite.Push(at, &ctx.WriteRequest)
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rowsInserted.Add(rowsTotal)
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if at != nil {
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rowsTenantInserted.Get(at).Add(rowsTotal)
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}
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rowsPerInsert.Update(float64(rowsTotal))
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return nil
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}
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@ -15,6 +15,7 @@ import (
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"github.com/VictoriaMetrics/VictoriaMetrics/app/vminsert/graphite"
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"github.com/VictoriaMetrics/VictoriaMetrics/app/vminsert/influx"
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"github.com/VictoriaMetrics/VictoriaMetrics/app/vminsert/native"
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"github.com/VictoriaMetrics/VictoriaMetrics/app/vminsert/opentelemetry"
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"github.com/VictoriaMetrics/VictoriaMetrics/app/vminsert/opentsdb"
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"github.com/VictoriaMetrics/VictoriaMetrics/app/vminsert/opentsdbhttp"
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"github.com/VictoriaMetrics/VictoriaMetrics/app/vminsert/prometheusimport"
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@ -210,6 +211,15 @@ func RequestHandler(w http.ResponseWriter, r *http.Request) bool {
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addInfluxResponseHeaders(w)
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influxutils.WriteDatabaseNames(w)
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return true
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case "/opentelemetry/api/v1/push":
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opentelemetryPushRequests.Inc()
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if err := opentelemetry.InsertHandler(r); err != nil {
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opentelemetryPushErrors.Inc()
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httpserver.Errorf(w, r, "%s", err)
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return true
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}
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w.WriteHeader(http.StatusOK)
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return true
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case "/datadog/api/v1/series":
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datadogWriteRequests.Inc()
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if err := datadog.InsertHandlerForHTTP(r); err != nil {
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@ -344,6 +354,9 @@ var (
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datadogIntakeRequests = metrics.NewCounter(`vm_http_requests_total{path="/datadog/intake", protocol="datadog"}`)
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datadogMetadataRequests = metrics.NewCounter(`vm_http_requests_total{path="/datadog/api/v1/metadata", protocol="datadog"}`)
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opentelemetryPushRequests = metrics.NewCounter(`vm_http_requests_total{path="/opentelemetry/api/v1/push", protocol="opentelemetry"}`)
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opentelemetryPushErrors = metrics.NewCounter(`vm_http_request_errors_total{path="/opentelemetry/api/v1/push", protocol="opentelemetry"}`)
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promscrapeTargetsRequests = metrics.NewCounter(`vm_http_requests_total{path="/targets"}`)
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promscrapeServiceDiscoveryRequests = metrics.NewCounter(`vm_http_requests_total{path="/service-discovery"}`)
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74
app/vminsert/opentelemetry/request_handler.go
Normal file
74
app/vminsert/opentelemetry/request_handler.go
Normal file
@ -0,0 +1,74 @@
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package opentelemetry
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import (
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"net/http"
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"github.com/VictoriaMetrics/VictoriaMetrics/app/vminsert/common"
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"github.com/VictoriaMetrics/VictoriaMetrics/app/vminsert/relabel"
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"github.com/VictoriaMetrics/VictoriaMetrics/lib/prompbmarshal"
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parserCommon "github.com/VictoriaMetrics/VictoriaMetrics/lib/protoparser/common"
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"github.com/VictoriaMetrics/VictoriaMetrics/lib/protoparser/opentelemetry/stream"
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"github.com/VictoriaMetrics/metrics"
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)
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var (
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rowsInserted = metrics.NewCounter(`vm_rows_inserted_total{type="opentelemetry"}`)
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rowsPerInsert = metrics.NewHistogram(`vm_rows_per_insert{type="opentelemetry"}`)
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)
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// InsertHandler processes opentelemetry metrics.
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func InsertHandler(req *http.Request) error {
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extraLabels, err := parserCommon.GetExtraLabels(req)
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if err != nil {
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return err
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}
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isGzipped := req.Header.Get("Content-Encoding") == "gzip"
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return stream.ParseStream(req.Body, isGzipped, func(tss []prompbmarshal.TimeSeries) error {
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return insertRows(tss, extraLabels)
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})
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}
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func insertRows(tss []prompbmarshal.TimeSeries, extraLabels []prompbmarshal.Label) error {
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ctx := common.GetInsertCtx()
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defer common.PutInsertCtx(ctx)
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rowsLen := 0
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for i := range tss {
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rowsLen += len(tss[i].Samples)
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}
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ctx.Reset(rowsLen)
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rowsTotal := 0
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hasRelabeling := relabel.HasRelabeling()
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for i := range tss {
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ts := &tss[i]
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rowsTotal += len(ts.Samples)
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ctx.Labels = ctx.Labels[:0]
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for _, label := range ts.Labels {
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ctx.AddLabel(label.Name, label.Value)
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}
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for _, label := range extraLabels {
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ctx.AddLabel(label.Name, label.Value)
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}
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if hasRelabeling {
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ctx.ApplyRelabeling()
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}
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if len(ctx.Labels) == 0 {
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// Skip metric without labels.
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continue
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}
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ctx.SortLabelsIfNeeded()
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var metricNameRaw []byte
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var err error
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samples := ts.Samples
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for i := range samples {
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r := &samples[i]
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metricNameRaw, err = ctx.WriteDataPointExt(metricNameRaw, ctx.Labels, r.Timestamp, r.Value)
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if err != nil {
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return err
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}
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}
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}
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rowsInserted.Add(rowsTotal)
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rowsPerInsert.Update(float64(rowsTotal))
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return ctx.FlushBufs()
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}
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@ -49,6 +49,7 @@ The previous behavior can be restored in the following ways:
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- `WITH (f(window, step, off) = m[window:step] offset off) f(5m, 10s, 1h)` is automatically transformed to `m[5m:10s] offset 1h`
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Thanks to @lujiajing1126 for the initial idea and [implementation](https://github.com/VictoriaMetrics/metricsql/pull/13). See [this feature request](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4025).
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* FEATURE: [vmui](https://docs.victoriametrics.com/#vmui): added a new page with the list of currently running queries. See [this issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4598) and [these docs](https://docs.victoriametrics.com/#active-queries).
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* FEATURE: [vmagent](https://docs.victoriametrics.com/vmagent.html): add support for data ingestion via [OpenTelemetry protocol](https://opentelemetry.io/docs/reference/specification/metrics/). See [these docs](https://docs.victoriametrics.com/Single-server-VictoriaMetrics.html#sending-data-via-opentelemetry), [this feature request](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/2424) and [this pull request](https://github.com/VictoriaMetrics/VictoriaMetrics/pull/2570).
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* FEATURE: [vmagent](https://docs.victoriametrics.com/vmagent.html): allow sharding outgoing time series among the configured remote storage systems. This can be useful for building horizontally scalable [stream aggregation](https://docs.victoriametrics.com/stream-aggregation.html), when samples for the same time series must be aggregated by the same `vmagent` instance at the second level. See [these docs](https://docs.victoriametrics.com/vmagent.html#sharding-among-remote-storages) and [this feature request](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4637) for details.
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* FEATURE: [vmagent](https://docs.victoriametrics.com/vmagent.html): allow configuring staleness interval in [stream aggregation](https://docs.victoriametrics.com/stream-aggregation.html) config. See [this issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4667) for details.
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* FEATURE: [vmagent](https://docs.victoriametrics.com/vmagent.html): allow specifying a list of [series selectors](https://docs.victoriametrics.com/keyConcepts.html#filtering) inside `if` option of relabeling rules. The corresponding relabeling rule is executed when at least a single series selector matches. See [these docs](https://docs.victoriametrics.com/vmagent.html#relabeling-enhancements).
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@ -335,13 +335,14 @@ Check practical examples of VictoriaMetrics API [here](https://docs.victoriametr
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The `<accountID>` can be set to `multitenant` string, e.g. `http://<vminsert>:8480/insert/multitenant/<suffix>`. Such urls accept data from multiple tenants
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specified via `vm_account_id` and `vm_project_id` labels. See [multitenancy via labels](#multitenancy-via-labels) for more details.
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- `<suffix>` may have the following values:
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- `prometheus` and `prometheus/api/v1/write` - for inserting data with [Prometheus remote write API](https://prometheus.io/docs/prometheus/latest/configuration/configuration/#remote_write).
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- `prometheus` and `prometheus/api/v1/write` - for ingesting data with [Prometheus remote write API](https://prometheus.io/docs/prometheus/latest/configuration/configuration/#remote_write).
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- `prometheus/api/v1/import` - for importing data obtained via `api/v1/export` at `vmselect` (see below), JSON line format.
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- `prometheus/api/v1/import/native` - for importing data obtained via `api/v1/export/native` on `vmselect` (see below).
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- `prometheus/api/v1/import/csv` - for importing arbitrary CSV data. See [these docs](https://docs.victoriametrics.com/Single-server-VictoriaMetrics.html#how-to-import-csv-data) for details.
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- `prometheus/api/v1/import/prometheus` - for importing data in [Prometheus text exposition format](https://github.com/prometheus/docs/blob/master/content/docs/instrumenting/exposition_formats.md#text-based-format) and in [OpenMetrics format](https://github.com/OpenObservability/OpenMetrics/blob/master/specification/OpenMetrics.md). This endpoint also supports [Pushgateway protocol](https://github.com/prometheus/pushgateway#url). See [these docs](https://docs.victoriametrics.com/Single-server-VictoriaMetrics.html#how-to-import-data-in-prometheus-exposition-format) for details.
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- `datadog/api/v1/series` - for inserting data with [DataDog submit metrics API](https://docs.datadoghq.com/api/latest/metrics/#submit-metrics). See [these docs](https://docs.victoriametrics.com/Single-server-VictoriaMetrics.html#how-to-send-data-from-datadog-agent) for details.
|
||||
- `influx/write` and `influx/api/v2/write` - for inserting data with [InfluxDB line protocol](https://docs.influxdata.com/influxdb/v1.7/write_protocols/line_protocol_tutorial/). See [these docs](https://docs.victoriametrics.com/Single-server-VictoriaMetrics.html#how-to-send-data-from-influxdb-compatible-agents-such-as-telegraf) for details.
|
||||
- `opentemetry/api/v1/push` - for ingesting data via [OpenTelemetry protocol for metrics](https://github.com/open-telemetry/opentelemetry-specification/blob/ffddc289462dfe0c2041e3ca42a7b1df805706de/specification/metrics/data-model.md). See [these docs](https://docs.victoriametrics.com/Single-server-VictoriaMetrics.html#sending-data-via-opentelemetry).
|
||||
- `datadog/api/v1/series` - for ingesting data with [DataDog submit metrics API](https://docs.datadoghq.com/api/latest/metrics/#submit-metrics). See [these docs](https://docs.victoriametrics.com/Single-server-VictoriaMetrics.html#how-to-send-data-from-datadog-agent) for details.
|
||||
- `influx/write` and `influx/api/v2/write` - for ingesting data with [InfluxDB line protocol](https://docs.influxdata.com/influxdb/v1.7/write_protocols/line_protocol_tutorial/). See [these docs](https://docs.victoriametrics.com/Single-server-VictoriaMetrics.html#how-to-send-data-from-influxdb-compatible-agents-such-as-telegraf) for details.
|
||||
- `opentsdb/api/put` - for accepting [OpenTSDB HTTP /api/put requests](http://opentsdb.net/docs/build/html/api_http/put.html). This handler is disabled by default. It is exposed on a distinct TCP address set via `-opentsdbHTTPListenAddr` command-line flag. See [these docs](https://docs.victoriametrics.com/Single-server-VictoriaMetrics.html#sending-opentsdb-data-via-http-apiput-requests) for details.
|
||||
|
||||
- URLs for [Prometheus querying API](https://prometheus.io/docs/prometheus/latest/querying/api/): `http://<vmselect>:8481/select/<accountID>/prometheus/<suffix>`, where:
|
||||
|
||||
@ -89,6 +89,7 @@ VictoriaMetrics has the following prominent features:
|
||||
* [Arbitrary CSV data](#how-to-import-csv-data).
|
||||
* [Native binary format](#how-to-import-data-in-native-format).
|
||||
* [DataDog agent or DogStatsD](#how-to-send-data-from-datadog-agent).
|
||||
* [OpenTelemetry metrics format](#sending-data-via-opentelemetry).
|
||||
* It supports powerful [stream aggregation](https://docs.victoriametrics.com/stream-aggregation.html), which can be used as a [statsd](https://github.com/statsd/statsd) alternative.
|
||||
* It supports metrics [relabeling](#relabeling).
|
||||
* It can deal with [high cardinality issues](https://docs.victoriametrics.com/FAQ.html#what-is-high-cardinality) and
|
||||
@ -1176,6 +1177,7 @@ Additionally, VictoriaMetrics can accept metrics via the following popular data
|
||||
* DataDog `submit metrics` API. See [these docs](#how-to-send-data-from-datadog-agent) for details.
|
||||
* InfluxDB line protocol. See [these docs](#how-to-send-data-from-influxdb-compatible-agents-such-as-telegraf) for details.
|
||||
* Graphite plaintext protocol. See [these docs](#how-to-send-data-from-graphite-compatible-agents-such-as-statsd) for details.
|
||||
* OpenTelemetry http API. See [these docs](#sending-data-via-opentelemetry) for details.
|
||||
* OpenTSDB telnet put protocol. See [these docs](#sending-data-via-telnet-put-protocol) for details.
|
||||
* OpenTSDB http `/api/put` protocol. See [these docs](#sending-opentsdb-data-via-http-apiput-requests) for details.
|
||||
* `/api/v1/import` for importing data obtained from [/api/v1/export](#how-to-export-data-in-json-line-format).
|
||||
@ -1359,6 +1361,13 @@ Note that it could be required to flush response cache after importing historica
|
||||
|
||||
VictoriaMetrics also may scrape Prometheus targets - see [these docs](#how-to-scrape-prometheus-exporters-such-as-node-exporter).
|
||||
|
||||
## Sending data via OpenTelemetry
|
||||
|
||||
VictoriaMetrics supports data ingestion via [OpenTelemetry protocol for metrics](https://github.com/open-telemetry/opentelemetry-specification/blob/ffddc289462dfe0c2041e3ca42a7b1df805706de/specification/metrics/data-model.md) at `/opentemetry/api/v1/push` path.
|
||||
|
||||
VictoriaMetrics expects `protobuf`-encoded requests at `/opentelemetry/api/v1/push`.
|
||||
Set HTTP request header `Content-Encoding: gzip` when sending gzip-compressed data to `/opentelemetry/api/v1/push`.
|
||||
|
||||
## Relabeling
|
||||
|
||||
VictoriaMetrics supports Prometheus-compatible relabeling for all the ingested metrics if `-relabelConfig` command-line flag points
|
||||
|
||||
@ -97,6 +97,7 @@ VictoriaMetrics has the following prominent features:
|
||||
* [Arbitrary CSV data](#how-to-import-csv-data).
|
||||
* [Native binary format](#how-to-import-data-in-native-format).
|
||||
* [DataDog agent or DogStatsD](#how-to-send-data-from-datadog-agent).
|
||||
* [OpenTelemetry metrics format](#sending-data-via-opentelemetry).
|
||||
* It supports powerful [stream aggregation](https://docs.victoriametrics.com/stream-aggregation.html), which can be used as a [statsd](https://github.com/statsd/statsd) alternative.
|
||||
* It supports metrics [relabeling](#relabeling).
|
||||
* It can deal with [high cardinality issues](https://docs.victoriametrics.com/FAQ.html#what-is-high-cardinality) and
|
||||
@ -1184,6 +1185,7 @@ Additionally, VictoriaMetrics can accept metrics via the following popular data
|
||||
* DataDog `submit metrics` API. See [these docs](#how-to-send-data-from-datadog-agent) for details.
|
||||
* InfluxDB line protocol. See [these docs](#how-to-send-data-from-influxdb-compatible-agents-such-as-telegraf) for details.
|
||||
* Graphite plaintext protocol. See [these docs](#how-to-send-data-from-graphite-compatible-agents-such-as-statsd) for details.
|
||||
* OpenTelemetry http API. See [these docs](#sending-data-via-opentelemetry) for details.
|
||||
* OpenTSDB telnet put protocol. See [these docs](#sending-data-via-telnet-put-protocol) for details.
|
||||
* OpenTSDB http `/api/put` protocol. See [these docs](#sending-opentsdb-data-via-http-apiput-requests) for details.
|
||||
* `/api/v1/import` for importing data obtained from [/api/v1/export](#how-to-export-data-in-json-line-format).
|
||||
@ -1367,6 +1369,13 @@ Note that it could be required to flush response cache after importing historica
|
||||
|
||||
VictoriaMetrics also may scrape Prometheus targets - see [these docs](#how-to-scrape-prometheus-exporters-such-as-node-exporter).
|
||||
|
||||
## Sending data via OpenTelemetry
|
||||
|
||||
VictoriaMetrics supports data ingestion via [OpenTelemetry protocol for metrics](https://github.com/open-telemetry/opentelemetry-specification/blob/ffddc289462dfe0c2041e3ca42a7b1df805706de/specification/metrics/data-model.md) at `/opentemetry/api/v1/push` path.
|
||||
|
||||
VictoriaMetrics expects `protobuf`-encoded requests at `/opentelemetry/api/v1/push`.
|
||||
Set HTTP request header `Content-Encoding: gzip` when sending gzip-compressed data to `/opentelemetry/api/v1/push`.
|
||||
|
||||
## Relabeling
|
||||
|
||||
VictoriaMetrics supports Prometheus-compatible relabeling for all the ingested metrics if `-relabelConfig` command-line flag points
|
||||
|
||||
@ -104,6 +104,7 @@ additionally to pull-based Prometheus-compatible targets' scraping:
|
||||
* DataDog "submit metrics" API. See [these docs](https://docs.victoriametrics.com/Single-server-VictoriaMetrics.html#how-to-send-data-from-datadog-agent).
|
||||
* InfluxDB line protocol via `http://<vmagent>:8429/write`. See [these docs](https://docs.victoriametrics.com/Single-server-VictoriaMetrics.html#how-to-send-data-from-influxdb-compatible-agents-such-as-telegraf).
|
||||
* Graphite plaintext protocol if `-graphiteListenAddr` command-line flag is set. See [these docs](https://docs.victoriametrics.com/Single-server-VictoriaMetrics.html#how-to-send-data-from-graphite-compatible-agents-such-as-statsd).
|
||||
* OpenTelemetry http API. See [these docs](https://docs.victoriametrics.com/Single-server-VictoriaMetrics.html#sending-data-via-opentelemetry).
|
||||
* OpenTSDB telnet and http protocols if `-opentsdbListenAddr` command-line flag is set. See [these docs](https://docs.victoriametrics.com/Single-server-VictoriaMetrics.html#how-to-send-data-from-opentsdb-compatible-agents).
|
||||
* Prometheus remote write protocol via `http://<vmagent>:8429/api/v1/write`.
|
||||
* JSON lines import protocol via `http://<vmagent>:8429/api/v1/import`. See [these docs](https://docs.victoriametrics.com/Single-server-VictoriaMetrics.html#how-to-import-data-in-json-line-format).
|
||||
|
||||
120
lib/protoparser/opentelemetry/pb/common.pb.go
Normal file
120
lib/protoparser/opentelemetry/pb/common.pb.go
Normal file
@ -0,0 +1,120 @@
|
||||
// Copyright 2019, 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.
|
||||
|
||||
// Code generated by protoc-gen-go. DO NOT EDIT.
|
||||
// versions:
|
||||
// protoc-gen-go v1.28.1
|
||||
// protoc v3.21.12
|
||||
// source: lib/protoparser/opentelemetry/proto/common.proto
|
||||
|
||||
package pb
|
||||
|
||||
// AnyValue is used to represent any type of attribute value. AnyValue may contain a
|
||||
// primitive value such as a string or integer or it may contain an arbitrary nested
|
||||
// object containing arrays, key-value lists and primitives.
|
||||
type AnyValue struct {
|
||||
unknownFields []byte
|
||||
|
||||
// The value is one of the listed fields. It is valid for all values to be unspecified
|
||||
// in which case this AnyValue is considered to be "empty".
|
||||
//
|
||||
// Types that are assignable to Value:
|
||||
//
|
||||
// *AnyValue_StringValue
|
||||
// *AnyValue_BoolValue
|
||||
// *AnyValue_IntValue
|
||||
// *AnyValue_DoubleValue
|
||||
// *AnyValue_ArrayValue
|
||||
// *AnyValue_KvlistValue
|
||||
// *AnyValue_BytesValue
|
||||
Value isAnyValue_Value `protobuf_oneof:"value"`
|
||||
}
|
||||
|
||||
type isAnyValue_Value interface {
|
||||
isAnyValue_Value()
|
||||
}
|
||||
|
||||
type AnyValue_StringValue struct {
|
||||
StringValue string `protobuf:"bytes,1,opt,name=string_value,json=stringValue,proto3,oneof"`
|
||||
}
|
||||
|
||||
type AnyValue_BoolValue struct {
|
||||
BoolValue bool `protobuf:"varint,2,opt,name=bool_value,json=boolValue,proto3,oneof"`
|
||||
}
|
||||
|
||||
type AnyValue_IntValue struct {
|
||||
IntValue int64 `protobuf:"varint,3,opt,name=int_value,json=intValue,proto3,oneof"`
|
||||
}
|
||||
|
||||
type AnyValue_DoubleValue struct {
|
||||
DoubleValue float64 `protobuf:"fixed64,4,opt,name=double_value,json=doubleValue,proto3,oneof"`
|
||||
}
|
||||
|
||||
type AnyValue_ArrayValue struct {
|
||||
ArrayValue *ArrayValue `protobuf:"bytes,5,opt,name=array_value,json=arrayValue,proto3,oneof"`
|
||||
}
|
||||
|
||||
type AnyValue_KvlistValue struct {
|
||||
KvlistValue *KeyValueList `protobuf:"bytes,6,opt,name=kvlist_value,json=kvlistValue,proto3,oneof"`
|
||||
}
|
||||
|
||||
type AnyValue_BytesValue struct {
|
||||
BytesValue []byte `protobuf:"bytes,7,opt,name=bytes_value,json=bytesValue,proto3,oneof"`
|
||||
}
|
||||
|
||||
func (*AnyValue_StringValue) isAnyValue_Value() {}
|
||||
|
||||
func (*AnyValue_BoolValue) isAnyValue_Value() {}
|
||||
|
||||
func (*AnyValue_IntValue) isAnyValue_Value() {}
|
||||
|
||||
func (*AnyValue_DoubleValue) isAnyValue_Value() {}
|
||||
|
||||
func (*AnyValue_ArrayValue) isAnyValue_Value() {}
|
||||
|
||||
func (*AnyValue_KvlistValue) isAnyValue_Value() {}
|
||||
|
||||
func (*AnyValue_BytesValue) isAnyValue_Value() {}
|
||||
|
||||
// ArrayValue is a list of AnyValue messages. We need ArrayValue as a message
|
||||
// since oneof in AnyValue does not allow repeated fields.
|
||||
type ArrayValue struct {
|
||||
unknownFields []byte
|
||||
// Array of values. The array may be empty (contain 0 elements).
|
||||
Values []*AnyValue `protobuf:"bytes,1,rep,name=values,proto3" json:"values,omitempty"`
|
||||
}
|
||||
|
||||
// KeyValueList is a list of KeyValue messages. We need KeyValueList as a message
|
||||
// since `oneof` in AnyValue does not allow repeated fields. Everywhere else where we need
|
||||
// a list of KeyValue messages (e.g. in Span) we use `repeated KeyValue` directly to
|
||||
// avoid unnecessary extra wrapping (which slows down the protocol). The 2 approaches
|
||||
// are semantically equivalent.
|
||||
type KeyValueList struct {
|
||||
unknownFields []byte
|
||||
|
||||
// A collection of key/value pairs of key-value pairs. The list may be empty (may
|
||||
// contain 0 elements).
|
||||
// The keys MUST be unique (it is not allowed to have more than one
|
||||
// value with the same key).
|
||||
Values []*KeyValue `protobuf:"bytes,1,rep,name=values,proto3" json:"values,omitempty"`
|
||||
}
|
||||
|
||||
// KeyValue is a key-value pair that is used to store Span attributes, Link
|
||||
// attributes, etc.
|
||||
type KeyValue struct {
|
||||
unknownFields []byte
|
||||
|
||||
Key string `protobuf:"bytes,1,opt,name=key,proto3" json:"key,omitempty"`
|
||||
Value *AnyValue `protobuf:"bytes,2,opt,name=value,proto3" json:"value,omitempty"`
|
||||
}
|
||||
1079
lib/protoparser/opentelemetry/pb/common_vtproto.pb.go
Normal file
1079
lib/protoparser/opentelemetry/pb/common_vtproto.pb.go
Normal file
File diff suppressed because it is too large
Load Diff
69
lib/protoparser/opentelemetry/pb/helpers.go
Normal file
69
lib/protoparser/opentelemetry/pb/helpers.go
Normal file
@ -0,0 +1,69 @@
|
||||
package pb
|
||||
|
||||
import (
|
||||
"encoding/base64"
|
||||
"encoding/json"
|
||||
"fmt"
|
||||
"math"
|
||||
"strconv"
|
||||
)
|
||||
|
||||
// FormatString formats strings
|
||||
func (x *AnyValue) FormatString() string {
|
||||
switch v := x.Value.(type) {
|
||||
case *AnyValue_StringValue:
|
||||
return v.StringValue
|
||||
|
||||
case *AnyValue_BoolValue:
|
||||
return strconv.FormatBool(v.BoolValue)
|
||||
|
||||
case *AnyValue_DoubleValue:
|
||||
return float64AsString(v.DoubleValue)
|
||||
|
||||
case *AnyValue_IntValue:
|
||||
return strconv.FormatInt(v.IntValue, 10)
|
||||
|
||||
case *AnyValue_KvlistValue:
|
||||
jsonStr, _ := json.Marshal(v.KvlistValue.Values)
|
||||
return string(jsonStr)
|
||||
|
||||
case *AnyValue_BytesValue:
|
||||
return base64.StdEncoding.EncodeToString(v.BytesValue)
|
||||
|
||||
case *AnyValue_ArrayValue:
|
||||
jsonStr, _ := json.Marshal(v.ArrayValue.Values)
|
||||
return string(jsonStr)
|
||||
|
||||
default:
|
||||
return ""
|
||||
}
|
||||
}
|
||||
|
||||
func float64AsString(f float64) string {
|
||||
if math.IsInf(f, 0) || math.IsNaN(f) {
|
||||
return fmt.Sprintf("json: unsupported value: %s", strconv.FormatFloat(f, 'g', -1, 64))
|
||||
}
|
||||
|
||||
// Convert as if by ES6 number to string conversion.
|
||||
// This matches most other JSON generators.
|
||||
// See golang.org/issue/6384 and golang.org/issue/14135.
|
||||
// Like fmt %g, but the exponent cutoffs are different
|
||||
// and exponents themselves are not padded to two digits.
|
||||
scratch := [64]byte{}
|
||||
b := scratch[:0]
|
||||
abs := math.Abs(f)
|
||||
fmt := byte('f')
|
||||
if abs != 0 && (abs < 1e-6 || abs >= 1e21) {
|
||||
fmt = 'e'
|
||||
}
|
||||
b = strconv.AppendFloat(b, f, fmt, -1, 64)
|
||||
if fmt == 'e' {
|
||||
// clean up e-09 to e-9
|
||||
n := len(b)
|
||||
if n >= 4 && b[n-4] == 'e' && b[n-3] == '-' && b[n-2] == '0' {
|
||||
b[n-2] = b[n-1]
|
||||
b = b[:n-1]
|
||||
}
|
||||
}
|
||||
return string(b)
|
||||
}
|
||||
736
lib/protoparser/opentelemetry/pb/metrics.pb.go
Normal file
736
lib/protoparser/opentelemetry/pb/metrics.pb.go
Normal file
@ -0,0 +1,736 @@
|
||||
// Copyright 2019, 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.
|
||||
|
||||
// Code generated by protoc-gen-go. DO NOT EDIT.
|
||||
// versions:
|
||||
// protoc-gen-go v1.28.1
|
||||
// protoc v3.21.12
|
||||
// source: lib/protoparser/opentelemetry/proto/metrics.proto
|
||||
|
||||
package pb
|
||||
|
||||
// AggregationTemporality defines how a metric aggregator reports aggregated
|
||||
// values. It describes how those values relate to the time interval over
|
||||
// which they are aggregated.
|
||||
type AggregationTemporality int32
|
||||
|
||||
const (
|
||||
// UNSPECIFIED is the default AggregationTemporality, it MUST not be used.
|
||||
AggregationTemporality_AGGREGATION_TEMPORALITY_UNSPECIFIED AggregationTemporality = 0
|
||||
// DELTA is an AggregationTemporality for a metric aggregator which reports
|
||||
// changes since last report time. Successive metrics contain aggregation of
|
||||
// values from continuous and non-overlapping intervals.
|
||||
//
|
||||
// The values for a DELTA metric are based only on the time interval
|
||||
// associated with one measurement cycle. There is no dependency on
|
||||
// previous measurements like is the case for CUMULATIVE metrics.
|
||||
//
|
||||
// For example, consider a system measuring the number of requests that
|
||||
// it receives and reports the sum of these requests every second as a
|
||||
// DELTA metric:
|
||||
//
|
||||
// 1. The system starts receiving at time=t_0.
|
||||
// 2. A request is received, the system measures 1 request.
|
||||
// 3. A request is received, the system measures 1 request.
|
||||
// 4. A request is received, the system measures 1 request.
|
||||
// 5. The 1 second collection cycle ends. A metric is exported for the
|
||||
// number of requests received over the interval of time t_0 to
|
||||
// t_0+1 with a value of 3.
|
||||
// 6. A request is received, the system measures 1 request.
|
||||
// 7. A request is received, the system measures 1 request.
|
||||
// 8. The 1 second collection cycle ends. A metric is exported for the
|
||||
// number of requests received over the interval of time t_0+1 to
|
||||
// t_0+2 with a value of 2.
|
||||
AggregationTemporality_AGGREGATION_TEMPORALITY_DELTA AggregationTemporality = 1
|
||||
// CUMULATIVE is an AggregationTemporality for a metric aggregator which
|
||||
// reports changes since a fixed start time. This means that current values
|
||||
// of a CUMULATIVE metric depend on all previous measurements since the
|
||||
// start time. Because of this, the sender is required to retain this state
|
||||
// in some form. If this state is lost or invalidated, the CUMULATIVE metric
|
||||
// values MUST be reset and a new fixed start time following the last
|
||||
// reported measurement time sent MUST be used.
|
||||
//
|
||||
// For example, consider a system measuring the number of requests that
|
||||
// it receives and reports the sum of these requests every second as a
|
||||
// CUMULATIVE metric:
|
||||
//
|
||||
// 1. The system starts receiving at time=t_0.
|
||||
// 2. A request is received, the system measures 1 request.
|
||||
// 3. A request is received, the system measures 1 request.
|
||||
// 4. A request is received, the system measures 1 request.
|
||||
// 5. The 1 second collection cycle ends. A metric is exported for the
|
||||
// number of requests received over the interval of time t_0 to
|
||||
// t_0+1 with a value of 3.
|
||||
// 6. A request is received, the system measures 1 request.
|
||||
// 7. A request is received, the system measures 1 request.
|
||||
// 8. The 1 second collection cycle ends. A metric is exported for the
|
||||
// number of requests received over the interval of time t_0 to
|
||||
// t_0+2 with a value of 5.
|
||||
// 9. The system experiences a fault and loses state.
|
||||
// 10. The system recovers and resumes receiving at time=t_1.
|
||||
// 11. A request is received, the system measures 1 request.
|
||||
// 12. The 1 second collection cycle ends. A metric is exported for the
|
||||
// number of requests received over the interval of time t_1 to
|
||||
// t_0+1 with a value of 1.
|
||||
//
|
||||
// Note: Even though, when reporting changes since last report time, using
|
||||
// CUMULATIVE is valid, it is not recommended. This may cause problems for
|
||||
// systems that do not use start_time to determine when the aggregation
|
||||
// value was reset (e.g. Prometheus).
|
||||
AggregationTemporality_AGGREGATION_TEMPORALITY_CUMULATIVE AggregationTemporality = 2
|
||||
)
|
||||
|
||||
// Enum value maps for AggregationTemporality.
|
||||
var (
|
||||
AggregationTemporality_name = map[int32]string{
|
||||
0: "AGGREGATION_TEMPORALITY_UNSPECIFIED",
|
||||
1: "AGGREGATION_TEMPORALITY_DELTA",
|
||||
2: "AGGREGATION_TEMPORALITY_CUMULATIVE",
|
||||
}
|
||||
AggregationTemporality_value = map[string]int32{
|
||||
"AGGREGATION_TEMPORALITY_UNSPECIFIED": 0,
|
||||
"AGGREGATION_TEMPORALITY_DELTA": 1,
|
||||
"AGGREGATION_TEMPORALITY_CUMULATIVE": 2,
|
||||
}
|
||||
)
|
||||
|
||||
func (x AggregationTemporality) Enum() *AggregationTemporality {
|
||||
p := new(AggregationTemporality)
|
||||
*p = x
|
||||
return p
|
||||
}
|
||||
|
||||
// DataPointFlags is defined as a protobuf 'uint32' type and is to be used as a
|
||||
// bit-field representing 32 distinct boolean flags. Each flag defined in this
|
||||
// enum is a bit-mask. To test the presence of a single flag in the flags of
|
||||
// a data point, for example, use an expression like:
|
||||
//
|
||||
// (point.flags & FLAG_NO_RECORDED_VALUE) == FLAG_NO_RECORDED_VALUE
|
||||
type DataPointFlags int32
|
||||
|
||||
const (
|
||||
DataPointFlags_FLAG_NONE DataPointFlags = 0
|
||||
// This DataPoint is valid but has no recorded value. This value
|
||||
// SHOULD be used to reflect explicitly missing data in a series, as
|
||||
// for an equivalent to the Prometheus "staleness marker".
|
||||
DataPointFlags_FLAG_NO_RECORDED_VALUE DataPointFlags = 1
|
||||
)
|
||||
|
||||
// Enum value maps for DataPointFlags.
|
||||
var (
|
||||
DataPointFlags_name = map[int32]string{
|
||||
0: "FLAG_NONE",
|
||||
1: "FLAG_NO_RECORDED_VALUE",
|
||||
}
|
||||
DataPointFlags_value = map[string]int32{
|
||||
"FLAG_NONE": 0,
|
||||
"FLAG_NO_RECORDED_VALUE": 1,
|
||||
}
|
||||
)
|
||||
|
||||
func (x DataPointFlags) Enum() *DataPointFlags {
|
||||
p := new(DataPointFlags)
|
||||
*p = x
|
||||
return p
|
||||
}
|
||||
|
||||
// MetricsData represents the metrics data that can be stored in a persistent
|
||||
// storage, OR can be embedded by other protocols that transfer OTLP metrics
|
||||
// data but do not implement the OTLP protocol.
|
||||
//
|
||||
// The main difference between this message and collector protocol is that
|
||||
// in this message there will not be any "control" or "metadata" specific to
|
||||
// OTLP protocol.
|
||||
//
|
||||
// When new fields are added into this message, the OTLP request MUST be updated
|
||||
// as well.
|
||||
type MetricsData struct {
|
||||
unknownFields []byte
|
||||
|
||||
// An array of ResourceMetrics.
|
||||
// For data coming from a single resource this array will typically contain
|
||||
// one element. Intermediary nodes that receive data from multiple origins
|
||||
// typically batch the data before forwarding further and in that case this
|
||||
// array will contain multiple elements.
|
||||
ResourceMetrics []*ResourceMetrics `protobuf:"bytes,1,rep,name=resource_metrics,json=resourceMetrics,proto3" json:"resource_metrics,omitempty"`
|
||||
}
|
||||
|
||||
// A collection of ScopeMetrics from a Resource.
|
||||
type ResourceMetrics struct {
|
||||
unknownFields []byte
|
||||
|
||||
// The resource for the metrics in this message.
|
||||
// If this field is not set then no resource info is known.
|
||||
Resource *Resource `protobuf:"bytes,1,opt,name=resource,proto3" json:"resource,omitempty"`
|
||||
// A list of metrics that originate from a resource.
|
||||
ScopeMetrics []*ScopeMetrics `protobuf:"bytes,2,rep,name=scope_metrics,json=scopeMetrics,proto3" json:"scope_metrics,omitempty"`
|
||||
// This schema_url applies to the data in the "resource" field. It does not apply
|
||||
// to the data in the "scope_metrics" field which have their own schema_url field.
|
||||
SchemaUrl string `protobuf:"bytes,3,opt,name=schema_url,json=schemaUrl,proto3" json:"schema_url,omitempty"`
|
||||
}
|
||||
|
||||
// A collection of Metrics produced by an Scope.
|
||||
type ScopeMetrics struct {
|
||||
unknownFields []byte
|
||||
|
||||
// A list of metrics that originate from an instrumentation library.
|
||||
Metrics []*Metric `protobuf:"bytes,2,rep,name=metrics,proto3" json:"metrics,omitempty"`
|
||||
// This schema_url applies to all metrics in the "metrics" field.
|
||||
SchemaUrl string `protobuf:"bytes,3,opt,name=schema_url,json=schemaUrl,proto3" json:"schema_url,omitempty"`
|
||||
}
|
||||
|
||||
// Defines a Metric which has one or more timeseries. The following is a
|
||||
// brief summary of the Metric data model. For more details, see:
|
||||
//
|
||||
// https://github.com/open-telemetry/opentelemetry-specification/blob/main/specification/metrics/data-model.md
|
||||
//
|
||||
// The data model and relation between entities is shown in the
|
||||
// diagram below. Here, "DataPoint" is the term used to refer to any
|
||||
// one of the specific data point value types, and "points" is the term used
|
||||
// to refer to any one of the lists of points contained in the Metric.
|
||||
//
|
||||
// - Metric is composed of a metadata and data.
|
||||
//
|
||||
// - Metadata part contains a name, description, unit.
|
||||
//
|
||||
// - Data is one of the possible types (Sum, Gauge, Histogram, Summary).
|
||||
//
|
||||
// - DataPoint contains timestamps, attributes, and one of the possible value type
|
||||
// fields.
|
||||
//
|
||||
// Metric
|
||||
// +------------+
|
||||
// |name |
|
||||
// |description |
|
||||
// |unit | +------------------------------------+
|
||||
// |data |---> |Gauge, Sum, Histogram, Summary, ... |
|
||||
// +------------+ +------------------------------------+
|
||||
//
|
||||
// Data [One of Gauge, Sum, Histogram, Summary, ...]
|
||||
// +-----------+
|
||||
// |... | // Metadata about the Data.
|
||||
// |points |--+
|
||||
// +-----------+ |
|
||||
// | +---------------------------+
|
||||
// | |DataPoint 1 |
|
||||
// v |+------+------+ +------+ |
|
||||
// +-----+ ||label |label |...|label | |
|
||||
// | 1 |-->||value1|value2|...|valueN| |
|
||||
// +-----+ |+------+------+ +------+ |
|
||||
// | . | |+-----+ |
|
||||
// | . | ||value| |
|
||||
// | . | |+-----+ |
|
||||
// | . | +---------------------------+
|
||||
// | . | .
|
||||
// | . | .
|
||||
// | . | .
|
||||
// | . | +---------------------------+
|
||||
// | . | |DataPoint M |
|
||||
// +-----+ |+------+------+ +------+ |
|
||||
// | M |-->||label |label |...|label | |
|
||||
// +-----+ ||value1|value2|...|valueN| |
|
||||
// |+------+------+ +------+ |
|
||||
// |+-----+ |
|
||||
// ||value| |
|
||||
// |+-----+ |
|
||||
// +---------------------------+
|
||||
//
|
||||
// Each distinct type of DataPoint represents the output of a specific
|
||||
// aggregation function, the result of applying the DataPoint's
|
||||
// associated function of to one or more measurements.
|
||||
//
|
||||
// All DataPoint types have three common fields:
|
||||
// - Attributes includes key-value pairs associated with the data point
|
||||
// - TimeUnixNano is required, set to the end time of the aggregation
|
||||
// - StartTimeUnixNano is optional, but strongly encouraged for DataPoints
|
||||
// having an AggregationTemporality field, as discussed below.
|
||||
//
|
||||
// Both TimeUnixNano and StartTimeUnixNano values are expressed as
|
||||
// UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January 1970.
|
||||
//
|
||||
// # TimeUnixNano
|
||||
//
|
||||
// This field is required, having consistent interpretation across
|
||||
// DataPoint types. TimeUnixNano is the moment corresponding to when
|
||||
// the data point's aggregate value was captured.
|
||||
//
|
||||
// Data points with the 0 value for TimeUnixNano SHOULD be rejected
|
||||
// by consumers.
|
||||
//
|
||||
// # StartTimeUnixNano
|
||||
//
|
||||
// StartTimeUnixNano in general allows detecting when a sequence of
|
||||
// observations is unbroken. This field indicates to consumers the
|
||||
// start time for points with cumulative and delta
|
||||
// AggregationTemporality, and it should be included whenever possible
|
||||
// to support correct rate calculation. Although it may be omitted
|
||||
// when the start time is truly unknown, setting StartTimeUnixNano is
|
||||
// strongly encouraged.
|
||||
type Metric struct {
|
||||
unknownFields []byte
|
||||
|
||||
// name of the metric, including its DNS name prefix. It must be unique.
|
||||
Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"`
|
||||
// description of the metric, which can be used in documentation.
|
||||
Description string `protobuf:"bytes,2,opt,name=description,proto3" json:"description,omitempty"`
|
||||
// unit in which the metric value is reported. Follows the format
|
||||
// described by http://unitsofmeasure.org/ucum.html.
|
||||
Unit string `protobuf:"bytes,3,opt,name=unit,proto3" json:"unit,omitempty"`
|
||||
// Data determines the aggregation type (if any) of the metric, what is the
|
||||
// reported value type for the data points, as well as the relatationship to
|
||||
// the time interval over which they are reported.
|
||||
//
|
||||
// Types that are assignable to Data:
|
||||
//
|
||||
// *Metric_Gauge
|
||||
// *Metric_Sum
|
||||
// *Metric_Histogram
|
||||
// *Metric_ExponentialHistogram
|
||||
// *Metric_Summary
|
||||
Data isMetric_Data `protobuf_oneof:"data"`
|
||||
}
|
||||
|
||||
type isMetric_Data interface {
|
||||
isMetric_Data()
|
||||
}
|
||||
|
||||
type Metric_Gauge struct {
|
||||
Gauge *Gauge `protobuf:"bytes,5,opt,name=gauge,proto3,oneof"`
|
||||
}
|
||||
|
||||
type Metric_Sum struct {
|
||||
Sum *Sum `protobuf:"bytes,7,opt,name=sum,proto3,oneof"`
|
||||
}
|
||||
|
||||
type Metric_Histogram struct {
|
||||
Histogram *Histogram `protobuf:"bytes,9,opt,name=histogram,proto3,oneof"`
|
||||
}
|
||||
|
||||
type Metric_ExponentialHistogram struct {
|
||||
ExponentialHistogram *ExponentialHistogram `protobuf:"bytes,10,opt,name=exponential_histogram,json=exponentialHistogram,proto3,oneof"`
|
||||
}
|
||||
|
||||
type Metric_Summary struct {
|
||||
Summary *Summary `protobuf:"bytes,11,opt,name=summary,proto3,oneof"`
|
||||
}
|
||||
|
||||
func (*Metric_Gauge) isMetric_Data() {}
|
||||
|
||||
func (*Metric_Sum) isMetric_Data() {}
|
||||
|
||||
func (*Metric_Histogram) isMetric_Data() {}
|
||||
|
||||
func (*Metric_ExponentialHistogram) isMetric_Data() {}
|
||||
|
||||
func (*Metric_Summary) isMetric_Data() {}
|
||||
|
||||
// Gauge represents the type of a scalar metric that always exports the
|
||||
// "current value" for every data point. It should be used for an "unknown"
|
||||
// aggregation.
|
||||
//
|
||||
// A Gauge does not support different aggregation temporalities. Given the
|
||||
// aggregation is unknown, points cannot be combined using the same
|
||||
// aggregation, regardless of aggregation temporalities. Therefore,
|
||||
// AggregationTemporality is not included. Consequently, this also means
|
||||
// "StartTimeUnixNano" is ignored for all data points.
|
||||
type Gauge struct {
|
||||
unknownFields []byte
|
||||
|
||||
DataPoints []*NumberDataPoint `protobuf:"bytes,1,rep,name=data_points,json=dataPoints,proto3" json:"data_points,omitempty"`
|
||||
}
|
||||
|
||||
// Sum represents the type of a scalar metric that is calculated as a sum of all
|
||||
// reported measurements over a time interval.
|
||||
type Sum struct {
|
||||
unknownFields []byte
|
||||
|
||||
DataPoints []*NumberDataPoint `protobuf:"bytes,1,rep,name=data_points,json=dataPoints,proto3" json:"data_points,omitempty"`
|
||||
// aggregation_temporality describes if the aggregator reports delta changes
|
||||
// since last report time, or cumulative changes since a fixed start time.
|
||||
AggregationTemporality AggregationTemporality `protobuf:"varint,2,opt,name=aggregation_temporality,json=aggregationTemporality,proto3,enum=opentelemetry.AggregationTemporality" json:"aggregation_temporality,omitempty"`
|
||||
// If "true" means that the sum is monotonic.
|
||||
IsMonotonic bool `protobuf:"varint,3,opt,name=is_monotonic,json=isMonotonic,proto3" json:"is_monotonic,omitempty"`
|
||||
}
|
||||
|
||||
// Histogram represents the type of a metric that is calculated by aggregating
|
||||
// as a Histogram of all reported measurements over a time interval.
|
||||
type Histogram struct {
|
||||
unknownFields []byte
|
||||
|
||||
DataPoints []*HistogramDataPoint `protobuf:"bytes,1,rep,name=data_points,json=dataPoints,proto3" json:"data_points,omitempty"`
|
||||
// aggregation_temporality describes if the aggregator reports delta changes
|
||||
// since last report time, or cumulative changes since a fixed start time.
|
||||
AggregationTemporality AggregationTemporality `protobuf:"varint,2,opt,name=aggregation_temporality,json=aggregationTemporality,proto3,enum=opentelemetry.AggregationTemporality" json:"aggregation_temporality,omitempty"`
|
||||
}
|
||||
|
||||
// ExponentialHistogram represents the type of a metric that is calculated by aggregating
|
||||
// as a ExponentialHistogram of all reported double measurements over a time interval.
|
||||
type ExponentialHistogram struct {
|
||||
unknownFields []byte
|
||||
|
||||
DataPoints []*ExponentialHistogramDataPoint `protobuf:"bytes,1,rep,name=data_points,json=dataPoints,proto3" json:"data_points,omitempty"`
|
||||
// aggregation_temporality describes if the aggregator reports delta changes
|
||||
// since last report time, or cumulative changes since a fixed start time.
|
||||
AggregationTemporality AggregationTemporality `protobuf:"varint,2,opt,name=aggregation_temporality,json=aggregationTemporality,proto3,enum=opentelemetry.AggregationTemporality" json:"aggregation_temporality,omitempty"`
|
||||
}
|
||||
|
||||
// Summary metric data are used to convey quantile summaries,
|
||||
// a Prometheus (see: https://prometheus.io/docs/concepts/metric_types/#summary)
|
||||
// and OpenMetrics (see: https://github.com/OpenObservability/OpenMetrics/blob/4dbf6075567ab43296eed941037c12951faafb92/protos/prometheus.proto#L45)
|
||||
// data type. These data points cannot always be merged in a meaningful way.
|
||||
// While they can be useful in some applications, histogram data points are
|
||||
// recommended for new applications.
|
||||
type Summary struct {
|
||||
unknownFields []byte
|
||||
|
||||
DataPoints []*SummaryDataPoint `protobuf:"bytes,1,rep,name=data_points,json=dataPoints,proto3" json:"data_points,omitempty"`
|
||||
}
|
||||
|
||||
// NumberDataPoint is a single data point in a timeseries that describes the
|
||||
// time-varying scalar value of a metric.
|
||||
type NumberDataPoint struct {
|
||||
unknownFields []byte
|
||||
|
||||
// The set of key/value pairs that uniquely identify the timeseries from
|
||||
// where this point belongs. The list may be empty (may contain 0 elements).
|
||||
// Attribute keys MUST be unique (it is not allowed to have more than one
|
||||
// attribute with the same key).
|
||||
Attributes []*KeyValue `protobuf:"bytes,7,rep,name=attributes,proto3" json:"attributes,omitempty"`
|
||||
// StartTimeUnixNano is optional but strongly encouraged, see the
|
||||
// the detailed comments above Metric.
|
||||
//
|
||||
// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
|
||||
// 1970.
|
||||
StartTimeUnixNano uint64 `protobuf:"fixed64,2,opt,name=start_time_unix_nano,json=startTimeUnixNano,proto3" json:"start_time_unix_nano,omitempty"`
|
||||
// TimeUnixNano is required, see the detailed comments above Metric.
|
||||
//
|
||||
// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
|
||||
// 1970.
|
||||
TimeUnixNano uint64 `protobuf:"fixed64,3,opt,name=time_unix_nano,json=timeUnixNano,proto3" json:"time_unix_nano,omitempty"`
|
||||
// The value itself. A point is considered invalid when one of the recognized
|
||||
// value fields is not present inside this oneof.
|
||||
//
|
||||
// Types that are assignable to Value:
|
||||
//
|
||||
// *NumberDataPoint_AsDouble
|
||||
// *NumberDataPoint_AsInt
|
||||
Value isNumberDataPoint_Value `protobuf_oneof:"value"`
|
||||
// (Optional) List of exemplars collected from
|
||||
// measurements that were used to form the data point
|
||||
Exemplars []*Exemplar `protobuf:"bytes,5,rep,name=exemplars,proto3" json:"exemplars,omitempty"`
|
||||
// Flags that apply to this specific data point. See DataPointFlags
|
||||
// for the available flags and their meaning.
|
||||
Flags uint32 `protobuf:"varint,8,opt,name=flags,proto3" json:"flags,omitempty"`
|
||||
}
|
||||
|
||||
type isNumberDataPoint_Value interface {
|
||||
isNumberDataPoint_Value()
|
||||
}
|
||||
|
||||
type NumberDataPoint_AsDouble struct {
|
||||
AsDouble float64 `protobuf:"fixed64,4,opt,name=as_double,json=asDouble,proto3,oneof"`
|
||||
}
|
||||
|
||||
type NumberDataPoint_AsInt struct {
|
||||
AsInt int64 `protobuf:"fixed64,6,opt,name=as_int,json=asInt,proto3,oneof"`
|
||||
}
|
||||
|
||||
func (*NumberDataPoint_AsDouble) isNumberDataPoint_Value() {}
|
||||
|
||||
func (*NumberDataPoint_AsInt) isNumberDataPoint_Value() {}
|
||||
|
||||
// HistogramDataPoint is a single data point in a timeseries that describes the
|
||||
// time-varying values of a Histogram. A Histogram contains summary statistics
|
||||
// for a population of values, it may optionally contain the distribution of
|
||||
// those values across a set of buckets.
|
||||
//
|
||||
// If the histogram contains the distribution of values, then both
|
||||
// "explicit_bounds" and "bucket counts" fields must be defined.
|
||||
// If the histogram does not contain the distribution of values, then both
|
||||
// "explicit_bounds" and "bucket_counts" must be omitted and only "count" and
|
||||
// "sum" are known.
|
||||
type HistogramDataPoint struct {
|
||||
unknownFields []byte
|
||||
|
||||
// The set of key/value pairs that uniquely identify the timeseries from
|
||||
// where this point belongs. The list may be empty (may contain 0 elements).
|
||||
// Attribute keys MUST be unique (it is not allowed to have more than one
|
||||
// attribute with the same key).
|
||||
Attributes []*KeyValue `protobuf:"bytes,9,rep,name=attributes,proto3" json:"attributes,omitempty"`
|
||||
// StartTimeUnixNano is optional but strongly encouraged, see the
|
||||
// the detailed comments above Metric.
|
||||
//
|
||||
// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
|
||||
// 1970.
|
||||
StartTimeUnixNano uint64 `protobuf:"fixed64,2,opt,name=start_time_unix_nano,json=startTimeUnixNano,proto3" json:"start_time_unix_nano,omitempty"`
|
||||
// TimeUnixNano is required, see the detailed comments above Metric.
|
||||
//
|
||||
// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
|
||||
// 1970.
|
||||
TimeUnixNano uint64 `protobuf:"fixed64,3,opt,name=time_unix_nano,json=timeUnixNano,proto3" json:"time_unix_nano,omitempty"`
|
||||
// count is the number of values in the population. Must be non-negative. This
|
||||
// value must be equal to the sum of the "count" fields in buckets if a
|
||||
// histogram is provided.
|
||||
Count uint64 `protobuf:"fixed64,4,opt,name=count,proto3" json:"count,omitempty"`
|
||||
// sum of the values in the population. If count is zero then this field
|
||||
// must be zero.
|
||||
//
|
||||
// Note: Sum should only be filled out when measuring non-negative discrete
|
||||
// events, and is assumed to be monotonic over the values of these events.
|
||||
// Negative events *can* be recorded, but sum should not be filled out when
|
||||
// doing so. This is specifically to enforce compatibility w/ OpenMetrics,
|
||||
// see: https://github.com/OpenObservability/OpenMetrics/blob/main/specification/OpenMetrics.md#histogram
|
||||
Sum *float64 `protobuf:"fixed64,5,opt,name=sum,proto3,oneof" json:"sum,omitempty"`
|
||||
// bucket_counts is an optional field contains the count values of histogram
|
||||
// for each bucket.
|
||||
//
|
||||
// The sum of the bucket_counts must equal the value in the count field.
|
||||
//
|
||||
// The number of elements in bucket_counts array must be by one greater than
|
||||
// the number of elements in explicit_bounds array.
|
||||
BucketCounts []uint64 `protobuf:"fixed64,6,rep,packed,name=bucket_counts,json=bucketCounts,proto3" json:"bucket_counts,omitempty"`
|
||||
// explicit_bounds specifies buckets with explicitly defined bounds for values.
|
||||
//
|
||||
// The boundaries for bucket at index i are:
|
||||
//
|
||||
// (-infinity, explicit_bounds[i]] for i == 0
|
||||
// (explicit_bounds[i-1], explicit_bounds[i]] for 0 < i < size(explicit_bounds)
|
||||
// (explicit_bounds[i-1], +infinity) for i == size(explicit_bounds)
|
||||
//
|
||||
// The values in the explicit_bounds array must be strictly increasing.
|
||||
//
|
||||
// Histogram buckets are inclusive of their upper boundary, except the last
|
||||
// bucket where the boundary is at infinity. This format is intentionally
|
||||
// compatible with the OpenMetrics histogram definition.
|
||||
ExplicitBounds []float64 `protobuf:"fixed64,7,rep,packed,name=explicit_bounds,json=explicitBounds,proto3" json:"explicit_bounds,omitempty"`
|
||||
// (Optional) List of exemplars collected from
|
||||
// measurements that were used to form the data point
|
||||
Exemplars []*Exemplar `protobuf:"bytes,8,rep,name=exemplars,proto3" json:"exemplars,omitempty"`
|
||||
// Flags that apply to this specific data point. See DataPointFlags
|
||||
// for the available flags and their meaning.
|
||||
Flags uint32 `protobuf:"varint,10,opt,name=flags,proto3" json:"flags,omitempty"`
|
||||
// min is the minimum value over (start_time, end_time].
|
||||
Min *float64 `protobuf:"fixed64,11,opt,name=min,proto3,oneof" json:"min,omitempty"`
|
||||
// max is the maximum value over (start_time, end_time].
|
||||
Max *float64 `protobuf:"fixed64,12,opt,name=max,proto3,oneof" json:"max,omitempty"`
|
||||
}
|
||||
|
||||
// ExponentialHistogramDataPoint is a single data point in a timeseries that describes the
|
||||
// time-varying values of a ExponentialHistogram of double values. A ExponentialHistogram contains
|
||||
// summary statistics for a population of values, it may optionally contain the
|
||||
// distribution of those values across a set of buckets.
|
||||
type ExponentialHistogramDataPoint struct {
|
||||
unknownFields []byte
|
||||
|
||||
// The set of key/value pairs that uniquely identify the timeseries from
|
||||
// where this point belongs. The list may be empty (may contain 0 elements).
|
||||
// Attribute keys MUST be unique (it is not allowed to have more than one
|
||||
// attribute with the same key).
|
||||
Attributes []*KeyValue `protobuf:"bytes,1,rep,name=attributes,proto3" json:"attributes,omitempty"`
|
||||
// StartTimeUnixNano is optional but strongly encouraged, see the
|
||||
// the detailed comments above Metric.
|
||||
//
|
||||
// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
|
||||
// 1970.
|
||||
StartTimeUnixNano uint64 `protobuf:"fixed64,2,opt,name=start_time_unix_nano,json=startTimeUnixNano,proto3" json:"start_time_unix_nano,omitempty"`
|
||||
// TimeUnixNano is required, see the detailed comments above Metric.
|
||||
//
|
||||
// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
|
||||
// 1970.
|
||||
TimeUnixNano uint64 `protobuf:"fixed64,3,opt,name=time_unix_nano,json=timeUnixNano,proto3" json:"time_unix_nano,omitempty"`
|
||||
// count is the number of values in the population. Must be
|
||||
// non-negative. This value must be equal to the sum of the "bucket_counts"
|
||||
// values in the positive and negative Buckets plus the "zero_count" field.
|
||||
Count uint64 `protobuf:"fixed64,4,opt,name=count,proto3" json:"count,omitempty"`
|
||||
// sum of the values in the population. If count is zero then this field
|
||||
// must be zero.
|
||||
//
|
||||
// Note: Sum should only be filled out when measuring non-negative discrete
|
||||
// events, and is assumed to be monotonic over the values of these events.
|
||||
// Negative events *can* be recorded, but sum should not be filled out when
|
||||
// doing so. This is specifically to enforce compatibility w/ OpenMetrics,
|
||||
// see: https://github.com/OpenObservability/OpenMetrics/blob/main/specification/OpenMetrics.md#histogram
|
||||
Sum *float64 `protobuf:"fixed64,5,opt,name=sum,proto3,oneof" json:"sum,omitempty"`
|
||||
// scale describes the resolution of the histogram. Boundaries are
|
||||
// located at powers of the base, where:
|
||||
//
|
||||
// base = (2^(2^-scale))
|
||||
//
|
||||
// The histogram bucket identified by `index`, a signed integer,
|
||||
// contains values that are greater than (base^index) and
|
||||
// less than or equal to (base^(index+1)).
|
||||
//
|
||||
// The positive and negative ranges of the histogram are expressed
|
||||
// separately. Negative values are mapped by their absolute value
|
||||
// into the negative range using the same scale as the positive range.
|
||||
//
|
||||
// scale is not restricted by the protocol, as the permissible
|
||||
// values depend on the range of the data.
|
||||
Scale int32 `protobuf:"zigzag32,6,opt,name=scale,proto3" json:"scale,omitempty"`
|
||||
// zero_count is the count of values that are either exactly zero or
|
||||
// within the region considered zero by the instrumentation at the
|
||||
// tolerated degree of precision. This bucket stores values that
|
||||
// cannot be expressed using the standard exponential formula as
|
||||
// well as values that have been rounded to zero.
|
||||
//
|
||||
// Implementations MAY consider the zero bucket to have probability
|
||||
// mass equal to (zero_count / count).
|
||||
ZeroCount uint64 `protobuf:"fixed64,7,opt,name=zero_count,json=zeroCount,proto3" json:"zero_count,omitempty"`
|
||||
// positive carries the positive range of exponential bucket counts.
|
||||
Positive *ExponentialHistogramDataPoint_Buckets `protobuf:"bytes,8,opt,name=positive,proto3" json:"positive,omitempty"`
|
||||
// negative carries the negative range of exponential bucket counts.
|
||||
Negative *ExponentialHistogramDataPoint_Buckets `protobuf:"bytes,9,opt,name=negative,proto3" json:"negative,omitempty"`
|
||||
// Flags that apply to this specific data point. See DataPointFlags
|
||||
// for the available flags and their meaning.
|
||||
Flags uint32 `protobuf:"varint,10,opt,name=flags,proto3" json:"flags,omitempty"`
|
||||
// (Optional) List of exemplars collected from
|
||||
// measurements that were used to form the data point
|
||||
Exemplars []*Exemplar `protobuf:"bytes,11,rep,name=exemplars,proto3" json:"exemplars,omitempty"`
|
||||
// min is the minimum value over (start_time, end_time].
|
||||
Min *float64 `protobuf:"fixed64,12,opt,name=min,proto3,oneof" json:"min,omitempty"`
|
||||
// max is the maximum value over (start_time, end_time].
|
||||
Max *float64 `protobuf:"fixed64,13,opt,name=max,proto3,oneof" json:"max,omitempty"`
|
||||
}
|
||||
|
||||
// SummaryDataPoint is a single data point in a timeseries that describes the
|
||||
// time-varying values of a Summary metric.
|
||||
type SummaryDataPoint struct {
|
||||
unknownFields []byte
|
||||
|
||||
// The set of key/value pairs that uniquely identify the timeseries from
|
||||
// where this point belongs. The list may be empty (may contain 0 elements).
|
||||
// Attribute keys MUST be unique (it is not allowed to have more than one
|
||||
// attribute with the same key).
|
||||
Attributes []*KeyValue `protobuf:"bytes,7,rep,name=attributes,proto3" json:"attributes,omitempty"`
|
||||
// StartTimeUnixNano is optional but strongly encouraged, see the
|
||||
// the detailed comments above Metric.
|
||||
//
|
||||
// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
|
||||
// 1970.
|
||||
StartTimeUnixNano uint64 `protobuf:"fixed64,2,opt,name=start_time_unix_nano,json=startTimeUnixNano,proto3" json:"start_time_unix_nano,omitempty"`
|
||||
// TimeUnixNano is required, see the detailed comments above Metric.
|
||||
//
|
||||
// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
|
||||
// 1970.
|
||||
TimeUnixNano uint64 `protobuf:"fixed64,3,opt,name=time_unix_nano,json=timeUnixNano,proto3" json:"time_unix_nano,omitempty"`
|
||||
// count is the number of values in the population. Must be non-negative.
|
||||
Count uint64 `protobuf:"fixed64,4,opt,name=count,proto3" json:"count,omitempty"`
|
||||
// sum of the values in the population. If count is zero then this field
|
||||
// must be zero.
|
||||
//
|
||||
// Note: Sum should only be filled out when measuring non-negative discrete
|
||||
// events, and is assumed to be monotonic over the values of these events.
|
||||
// Negative events *can* be recorded, but sum should not be filled out when
|
||||
// doing so. This is specifically to enforce compatibility w/ OpenMetrics,
|
||||
// see: https://github.com/OpenObservability/OpenMetrics/blob/main/specification/OpenMetrics.md#summary
|
||||
Sum float64 `protobuf:"fixed64,5,opt,name=sum,proto3" json:"sum,omitempty"`
|
||||
// (Optional) list of values at different quantiles of the distribution calculated
|
||||
// from the current snapshot. The quantiles must be strictly increasing.
|
||||
QuantileValues []*SummaryDataPoint_ValueAtQuantile `protobuf:"bytes,6,rep,name=quantile_values,json=quantileValues,proto3" json:"quantile_values,omitempty"`
|
||||
// Flags that apply to this specific data point. See DataPointFlags
|
||||
// for the available flags and their meaning.
|
||||
Flags uint32 `protobuf:"varint,8,opt,name=flags,proto3" json:"flags,omitempty"`
|
||||
}
|
||||
|
||||
// A representation of an exemplar, which is a sample input measurement.
|
||||
// Exemplars also hold information about the environment when the measurement
|
||||
// was recorded, for example the span and trace ID of the active span when the
|
||||
// exemplar was recorded.
|
||||
type Exemplar struct {
|
||||
unknownFields []byte
|
||||
|
||||
// The set of key/value pairs that were filtered out by the aggregator, but
|
||||
// recorded alongside the original measurement. Only key/value pairs that were
|
||||
// filtered out by the aggregator should be included
|
||||
FilteredAttributes []*KeyValue `protobuf:"bytes,7,rep,name=filtered_attributes,json=filteredAttributes,proto3" json:"filtered_attributes,omitempty"`
|
||||
// time_unix_nano is the exact time when this exemplar was recorded
|
||||
//
|
||||
// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
|
||||
// 1970.
|
||||
TimeUnixNano uint64 `protobuf:"fixed64,2,opt,name=time_unix_nano,json=timeUnixNano,proto3" json:"time_unix_nano,omitempty"`
|
||||
// The value of the measurement that was recorded. An exemplar is
|
||||
// considered invalid when one of the recognized value fields is not present
|
||||
// inside this oneof.
|
||||
//
|
||||
// Types that are assignable to Value:
|
||||
//
|
||||
// *Exemplar_AsDouble
|
||||
// *Exemplar_AsInt
|
||||
Value isExemplar_Value `protobuf_oneof:"value"`
|
||||
// (Optional) Span ID of the exemplar trace.
|
||||
// span_id may be missing if the measurement is not recorded inside a trace
|
||||
// or if the trace is not sampled.
|
||||
SpanId []byte `protobuf:"bytes,4,opt,name=span_id,json=spanId,proto3" json:"span_id,omitempty"`
|
||||
// (Optional) Trace ID of the exemplar trace.
|
||||
// trace_id may be missing if the measurement is not recorded inside a trace
|
||||
// or if the trace is not sampled.
|
||||
TraceId []byte `protobuf:"bytes,5,opt,name=trace_id,json=traceId,proto3" json:"trace_id,omitempty"`
|
||||
}
|
||||
|
||||
type isExemplar_Value interface {
|
||||
isExemplar_Value()
|
||||
}
|
||||
|
||||
type Exemplar_AsDouble struct {
|
||||
AsDouble float64 `protobuf:"fixed64,3,opt,name=as_double,json=asDouble,proto3,oneof"`
|
||||
}
|
||||
|
||||
type Exemplar_AsInt struct {
|
||||
AsInt int64 `protobuf:"fixed64,6,opt,name=as_int,json=asInt,proto3,oneof"`
|
||||
}
|
||||
|
||||
func (*Exemplar_AsDouble) isExemplar_Value() {}
|
||||
|
||||
func (*Exemplar_AsInt) isExemplar_Value() {}
|
||||
|
||||
// Buckets are a set of bucket counts, encoded in a contiguous array
|
||||
// of counts.
|
||||
type ExponentialHistogramDataPoint_Buckets struct {
|
||||
unknownFields []byte
|
||||
|
||||
// Offset is the bucket index of the first entry in the bucket_counts array.
|
||||
//
|
||||
// Note: This uses a varint encoding as a simple form of compression.
|
||||
Offset int32 `protobuf:"zigzag32,1,opt,name=offset,proto3" json:"offset,omitempty"`
|
||||
// Count is an array of counts, where count[i] carries the count
|
||||
// of the bucket at index (offset+i). count[i] is the count of
|
||||
// values greater than base^(offset+i) and less or equal to than
|
||||
// base^(offset+i+1).
|
||||
//
|
||||
// Note: By contrast, the explicit HistogramDataPoint uses
|
||||
// fixed64. This field is expected to have many buckets,
|
||||
// especially zeros, so uint64 has been selected to ensure
|
||||
// varint encoding.
|
||||
BucketCounts []uint64 `protobuf:"varint,2,rep,packed,name=bucket_counts,json=bucketCounts,proto3" json:"bucket_counts,omitempty"`
|
||||
}
|
||||
|
||||
// Represents the value at a given quantile of a distribution.
|
||||
//
|
||||
// To record Min and Max values following conventions are used:
|
||||
// - The 1.0 quantile is equivalent to the maximum value observed.
|
||||
// - The 0.0 quantile is equivalent to the minimum value observed.
|
||||
//
|
||||
// See the following issue for more context:
|
||||
// https://github.com/open-telemetry/opentelemetry-proto/issues/125
|
||||
type SummaryDataPoint_ValueAtQuantile struct {
|
||||
unknownFields []byte
|
||||
|
||||
// The quantile of a distribution. Must be in the interval
|
||||
// [0.0, 1.0].
|
||||
Quantile float64 `protobuf:"fixed64,1,opt,name=quantile,proto3" json:"quantile,omitempty"`
|
||||
// The value at the given quantile of a distribution.
|
||||
//
|
||||
// Quantile values must NOT be negative.
|
||||
Value float64 `protobuf:"fixed64,2,opt,name=value,proto3" json:"value,omitempty"`
|
||||
}
|
||||
32
lib/protoparser/opentelemetry/pb/metrics_service.pb.go
Normal file
32
lib/protoparser/opentelemetry/pb/metrics_service.pb.go
Normal file
@ -0,0 +1,32 @@
|
||||
// Copyright 2019, 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.
|
||||
|
||||
// Code generated by protoc-gen-go. DO NOT EDIT.
|
||||
// versions:
|
||||
// protoc-gen-go v1.28.1
|
||||
// protoc v3.21.12
|
||||
// source: lib/protoparser/opentelemetry/proto/metrics_service.proto
|
||||
|
||||
package pb
|
||||
|
||||
type ExportMetricsServiceRequest struct {
|
||||
unknownFields []byte
|
||||
|
||||
// An array of ResourceMetrics.
|
||||
// For data coming from a single resource this array will typically contain one
|
||||
// element. Intermediary nodes (such as OpenTelemetry Collector) that receive
|
||||
// data from multiple origins typically batch the data before forwarding further and
|
||||
// in that case this array will contain multiple elements.
|
||||
ResourceMetrics []*ResourceMetrics `protobuf:"bytes,1,rep,name=resource_metrics,json=resourceMetrics,proto3" json:"resource_metrics,omitempty"`
|
||||
}
|
||||
157
lib/protoparser/opentelemetry/pb/metrics_service_vtproto.pb.go
Normal file
157
lib/protoparser/opentelemetry/pb/metrics_service_vtproto.pb.go
Normal file
@ -0,0 +1,157 @@
|
||||
// Code generated by protoc-gen-go-vtproto. DO NOT EDIT.
|
||||
// protoc-gen-go-vtproto version: v0.4.0
|
||||
// source: lib/protoparser/opentelemetry/proto/metrics_service.proto
|
||||
|
||||
package pb
|
||||
|
||||
import (
|
||||
fmt "fmt"
|
||||
io "io"
|
||||
)
|
||||
|
||||
func (m *ExportMetricsServiceRequest) MarshalVT() (dAtA []byte, err error) {
|
||||
if m == nil {
|
||||
return nil, nil
|
||||
}
|
||||
size := m.SizeVT()
|
||||
dAtA = make([]byte, size)
|
||||
n, err := m.MarshalToSizedBufferVT(dAtA[:size])
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
return dAtA[:n], nil
|
||||
}
|
||||
|
||||
func (m *ExportMetricsServiceRequest) MarshalToVT(dAtA []byte) (int, error) {
|
||||
size := m.SizeVT()
|
||||
return m.MarshalToSizedBufferVT(dAtA[:size])
|
||||
}
|
||||
|
||||
func (m *ExportMetricsServiceRequest) MarshalToSizedBufferVT(dAtA []byte) (int, error) {
|
||||
if m == nil {
|
||||
return 0, nil
|
||||
}
|
||||
i := len(dAtA)
|
||||
_ = i
|
||||
var l int
|
||||
_ = l
|
||||
if m.unknownFields != nil {
|
||||
i -= len(m.unknownFields)
|
||||
copy(dAtA[i:], m.unknownFields)
|
||||
}
|
||||
if len(m.ResourceMetrics) > 0 {
|
||||
for iNdEx := len(m.ResourceMetrics) - 1; iNdEx >= 0; iNdEx-- {
|
||||
size, err := m.ResourceMetrics[iNdEx].MarshalToSizedBufferVT(dAtA[:i])
|
||||
if err != nil {
|
||||
return 0, err
|
||||
}
|
||||
i -= size
|
||||
i = encodeVarint(dAtA, i, uint64(size))
|
||||
i--
|
||||
dAtA[i] = 0xa
|
||||
}
|
||||
}
|
||||
return len(dAtA) - i, nil
|
||||
}
|
||||
|
||||
func (m *ExportMetricsServiceRequest) SizeVT() (n int) {
|
||||
if m == nil {
|
||||
return 0
|
||||
}
|
||||
var l int
|
||||
_ = l
|
||||
if len(m.ResourceMetrics) > 0 {
|
||||
for _, e := range m.ResourceMetrics {
|
||||
l = e.SizeVT()
|
||||
n += 1 + l + sov(uint64(l))
|
||||
}
|
||||
}
|
||||
n += len(m.unknownFields)
|
||||
return n
|
||||
}
|
||||
|
||||
func (m *ExportMetricsServiceRequest) UnmarshalVT(dAtA []byte) error {
|
||||
l := len(dAtA)
|
||||
iNdEx := 0
|
||||
for iNdEx < l {
|
||||
preIndex := iNdEx
|
||||
var wire uint64
|
||||
for shift := uint(0); ; shift += 7 {
|
||||
if shift >= 64 {
|
||||
return ErrIntOverflow
|
||||
}
|
||||
if iNdEx >= l {
|
||||
return io.ErrUnexpectedEOF
|
||||
}
|
||||
b := dAtA[iNdEx]
|
||||
iNdEx++
|
||||
wire |= uint64(b&0x7F) << shift
|
||||
if b < 0x80 {
|
||||
break
|
||||
}
|
||||
}
|
||||
fieldNum := int32(wire >> 3)
|
||||
wireType := int(wire & 0x7)
|
||||
if wireType == 4 {
|
||||
return fmt.Errorf("proto: ExportMetricsServiceRequest: wiretype end group for non-group")
|
||||
}
|
||||
if fieldNum <= 0 {
|
||||
return fmt.Errorf("proto: ExportMetricsServiceRequest: illegal tag %d (wire type %d)", fieldNum, wire)
|
||||
}
|
||||
switch fieldNum {
|
||||
case 1:
|
||||
if wireType != 2 {
|
||||
return fmt.Errorf("proto: wrong wireType = %d for field ResourceMetrics", wireType)
|
||||
}
|
||||
var msglen int
|
||||
for shift := uint(0); ; shift += 7 {
|
||||
if shift >= 64 {
|
||||
return ErrIntOverflow
|
||||
}
|
||||
if iNdEx >= l {
|
||||
return io.ErrUnexpectedEOF
|
||||
}
|
||||
b := dAtA[iNdEx]
|
||||
iNdEx++
|
||||
msglen |= int(b&0x7F) << shift
|
||||
if b < 0x80 {
|
||||
break
|
||||
}
|
||||
}
|
||||
if msglen < 0 {
|
||||
return ErrInvalidLength
|
||||
}
|
||||
postIndex := iNdEx + msglen
|
||||
if postIndex < 0 {
|
||||
return ErrInvalidLength
|
||||
}
|
||||
if postIndex > l {
|
||||
return io.ErrUnexpectedEOF
|
||||
}
|
||||
m.ResourceMetrics = append(m.ResourceMetrics, &ResourceMetrics{})
|
||||
if err := m.ResourceMetrics[len(m.ResourceMetrics)-1].UnmarshalVT(dAtA[iNdEx:postIndex]); err != nil {
|
||||
return err
|
||||
}
|
||||
iNdEx = postIndex
|
||||
default:
|
||||
iNdEx = preIndex
|
||||
skippy, err := skip(dAtA[iNdEx:])
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
if (skippy < 0) || (iNdEx+skippy) < 0 {
|
||||
return ErrInvalidLength
|
||||
}
|
||||
if (iNdEx + skippy) > l {
|
||||
return io.ErrUnexpectedEOF
|
||||
}
|
||||
m.unknownFields = append(m.unknownFields, dAtA[iNdEx:iNdEx+skippy]...)
|
||||
iNdEx += skippy
|
||||
}
|
||||
}
|
||||
|
||||
if iNdEx > l {
|
||||
return io.ErrUnexpectedEOF
|
||||
}
|
||||
return nil
|
||||
}
|
||||
4331
lib/protoparser/opentelemetry/pb/metrics_vtproto.pb.go
Normal file
4331
lib/protoparser/opentelemetry/pb/metrics_vtproto.pb.go
Normal file
File diff suppressed because it is too large
Load Diff
48
lib/protoparser/opentelemetry/pb/resource.pb.go
Normal file
48
lib/protoparser/opentelemetry/pb/resource.pb.go
Normal file
@ -0,0 +1,48 @@
|
||||
// Copyright 2019, 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.
|
||||
|
||||
// Code generated by protoc-gen-go. DO NOT EDIT.
|
||||
// versions:
|
||||
// protoc-gen-go v1.28.1
|
||||
// protoc v3.21.12
|
||||
// source: lib/protoparser/opentelemetry/proto/resource.proto
|
||||
|
||||
package pb
|
||||
|
||||
// Resource information.
|
||||
type Resource struct {
|
||||
unknownFields []byte
|
||||
|
||||
// Set of attributes that describe the resource.
|
||||
// Attribute keys MUST be unique (it is not allowed to have more than one
|
||||
// attribute with the same key).
|
||||
Attributes []*KeyValue `protobuf:"bytes,1,rep,name=attributes,proto3" json:"attributes,omitempty"`
|
||||
// dropped_attributes_count is the number of dropped attributes. If the value is 0, then
|
||||
// no attributes were dropped.
|
||||
DroppedAttributesCount uint32 `protobuf:"varint,2,opt,name=dropped_attributes_count,json=droppedAttributesCount,proto3" json:"dropped_attributes_count,omitempty"`
|
||||
}
|
||||
|
||||
func (x *Resource) GetAttributes() []*KeyValue {
|
||||
if x != nil {
|
||||
return x.Attributes
|
||||
}
|
||||
return nil
|
||||
}
|
||||
|
||||
func (x *Resource) GetDroppedAttributesCount() uint32 {
|
||||
if x != nil {
|
||||
return x.DroppedAttributesCount
|
||||
}
|
||||
return 0
|
||||
}
|
||||
184
lib/protoparser/opentelemetry/pb/resource_vtproto.pb.go
Normal file
184
lib/protoparser/opentelemetry/pb/resource_vtproto.pb.go
Normal file
@ -0,0 +1,184 @@
|
||||
// Code generated by protoc-gen-go-vtproto. DO NOT EDIT.
|
||||
// protoc-gen-go-vtproto version: v0.4.0
|
||||
// source: lib/protoparser/opentelemetry/proto/resource.proto
|
||||
|
||||
package pb
|
||||
|
||||
import (
|
||||
fmt "fmt"
|
||||
io "io"
|
||||
)
|
||||
|
||||
func (m *Resource) MarshalVT() (dAtA []byte, err error) {
|
||||
if m == nil {
|
||||
return nil, nil
|
||||
}
|
||||
size := m.SizeVT()
|
||||
dAtA = make([]byte, size)
|
||||
n, err := m.MarshalToSizedBufferVT(dAtA[:size])
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
return dAtA[:n], nil
|
||||
}
|
||||
|
||||
func (m *Resource) MarshalToVT(dAtA []byte) (int, error) {
|
||||
size := m.SizeVT()
|
||||
return m.MarshalToSizedBufferVT(dAtA[:size])
|
||||
}
|
||||
|
||||
func (m *Resource) MarshalToSizedBufferVT(dAtA []byte) (int, error) {
|
||||
if m == nil {
|
||||
return 0, nil
|
||||
}
|
||||
i := len(dAtA)
|
||||
_ = i
|
||||
var l int
|
||||
_ = l
|
||||
if m.unknownFields != nil {
|
||||
i -= len(m.unknownFields)
|
||||
copy(dAtA[i:], m.unknownFields)
|
||||
}
|
||||
if m.DroppedAttributesCount != 0 {
|
||||
i = encodeVarint(dAtA, i, uint64(m.DroppedAttributesCount))
|
||||
i--
|
||||
dAtA[i] = 0x10
|
||||
}
|
||||
if len(m.Attributes) > 0 {
|
||||
for iNdEx := len(m.Attributes) - 1; iNdEx >= 0; iNdEx-- {
|
||||
size, err := m.Attributes[iNdEx].MarshalToSizedBufferVT(dAtA[:i])
|
||||
if err != nil {
|
||||
return 0, err
|
||||
}
|
||||
i -= size
|
||||
i = encodeVarint(dAtA, i, uint64(size))
|
||||
i--
|
||||
dAtA[i] = 0xa
|
||||
}
|
||||
}
|
||||
return len(dAtA) - i, nil
|
||||
}
|
||||
|
||||
func (m *Resource) SizeVT() (n int) {
|
||||
if m == nil {
|
||||
return 0
|
||||
}
|
||||
var l int
|
||||
_ = l
|
||||
if len(m.Attributes) > 0 {
|
||||
for _, e := range m.Attributes {
|
||||
l = e.SizeVT()
|
||||
n += 1 + l + sov(uint64(l))
|
||||
}
|
||||
}
|
||||
if m.DroppedAttributesCount != 0 {
|
||||
n += 1 + sov(uint64(m.DroppedAttributesCount))
|
||||
}
|
||||
n += len(m.unknownFields)
|
||||
return n
|
||||
}
|
||||
|
||||
func (m *Resource) UnmarshalVT(dAtA []byte) error {
|
||||
l := len(dAtA)
|
||||
iNdEx := 0
|
||||
for iNdEx < l {
|
||||
preIndex := iNdEx
|
||||
var wire uint64
|
||||
for shift := uint(0); ; shift += 7 {
|
||||
if shift >= 64 {
|
||||
return ErrIntOverflow
|
||||
}
|
||||
if iNdEx >= l {
|
||||
return io.ErrUnexpectedEOF
|
||||
}
|
||||
b := dAtA[iNdEx]
|
||||
iNdEx++
|
||||
wire |= uint64(b&0x7F) << shift
|
||||
if b < 0x80 {
|
||||
break
|
||||
}
|
||||
}
|
||||
fieldNum := int32(wire >> 3)
|
||||
wireType := int(wire & 0x7)
|
||||
if wireType == 4 {
|
||||
return fmt.Errorf("proto: Resource: wiretype end group for non-group")
|
||||
}
|
||||
if fieldNum <= 0 {
|
||||
return fmt.Errorf("proto: Resource: illegal tag %d (wire type %d)", fieldNum, wire)
|
||||
}
|
||||
switch fieldNum {
|
||||
case 1:
|
||||
if wireType != 2 {
|
||||
return fmt.Errorf("proto: wrong wireType = %d for field Attributes", wireType)
|
||||
}
|
||||
var msglen int
|
||||
for shift := uint(0); ; shift += 7 {
|
||||
if shift >= 64 {
|
||||
return ErrIntOverflow
|
||||
}
|
||||
if iNdEx >= l {
|
||||
return io.ErrUnexpectedEOF
|
||||
}
|
||||
b := dAtA[iNdEx]
|
||||
iNdEx++
|
||||
msglen |= int(b&0x7F) << shift
|
||||
if b < 0x80 {
|
||||
break
|
||||
}
|
||||
}
|
||||
if msglen < 0 {
|
||||
return ErrInvalidLength
|
||||
}
|
||||
postIndex := iNdEx + msglen
|
||||
if postIndex < 0 {
|
||||
return ErrInvalidLength
|
||||
}
|
||||
if postIndex > l {
|
||||
return io.ErrUnexpectedEOF
|
||||
}
|
||||
m.Attributes = append(m.Attributes, &KeyValue{})
|
||||
if err := m.Attributes[len(m.Attributes)-1].UnmarshalVT(dAtA[iNdEx:postIndex]); err != nil {
|
||||
return err
|
||||
}
|
||||
iNdEx = postIndex
|
||||
case 2:
|
||||
if wireType != 0 {
|
||||
return fmt.Errorf("proto: wrong wireType = %d for field DroppedAttributesCount", wireType)
|
||||
}
|
||||
m.DroppedAttributesCount = 0
|
||||
for shift := uint(0); ; shift += 7 {
|
||||
if shift >= 64 {
|
||||
return ErrIntOverflow
|
||||
}
|
||||
if iNdEx >= l {
|
||||
return io.ErrUnexpectedEOF
|
||||
}
|
||||
b := dAtA[iNdEx]
|
||||
iNdEx++
|
||||
m.DroppedAttributesCount |= uint32(b&0x7F) << shift
|
||||
if b < 0x80 {
|
||||
break
|
||||
}
|
||||
}
|
||||
default:
|
||||
iNdEx = preIndex
|
||||
skippy, err := skip(dAtA[iNdEx:])
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
if (skippy < 0) || (iNdEx+skippy) < 0 {
|
||||
return ErrInvalidLength
|
||||
}
|
||||
if (iNdEx + skippy) > l {
|
||||
return io.ErrUnexpectedEOF
|
||||
}
|
||||
m.unknownFields = append(m.unknownFields, dAtA[iNdEx:iNdEx+skippy]...)
|
||||
iNdEx += skippy
|
||||
}
|
||||
}
|
||||
|
||||
if iNdEx > l {
|
||||
return io.ErrUnexpectedEOF
|
||||
}
|
||||
return nil
|
||||
}
|
||||
32
lib/protoparser/opentelemetry/proto/README.md
Normal file
32
lib/protoparser/opentelemetry/proto/README.md
Normal file
@ -0,0 +1,32 @@
|
||||
# Opentelemetry proto files
|
||||
|
||||
Content copied from https://github.com/open-telemetry/opentelemetry-proto/tree/main/opentelemetry/proto
|
||||
|
||||
## Requirements
|
||||
- protoc binary [link](http://google.github.io/proto-lens/installing-protoc.html)
|
||||
- golang-proto-gen[link](https://developers.google.com/protocol-buffers/docs/reference/go-generated)
|
||||
- custom marshaller [link](https://github.com/planetscale/vtprotobuf)
|
||||
|
||||
## Modifications
|
||||
|
||||
Original proto files were modified:
|
||||
1) changed package name for `package opentelemetry`.
|
||||
2) changed import paths - changed directory names.
|
||||
3) changed go_package for `opentelemetry/pb`.
|
||||
|
||||
|
||||
## How to generate pbs
|
||||
|
||||
run command:
|
||||
```bash
|
||||
export GOBIN=~/go/bin protoc
|
||||
protoc -I=. --go_out=./lib/protoparser/opentelemetry --go-vtproto_out=./lib/protoparser/opentelemetry --plugin protoc-gen-go-vtproto="$GOBIN/protoc-gen-go-vtproto" --go-vtproto_opt=features=marshal+unmarshal+size lib/protoparser/opentelemetry/proto/*.proto
|
||||
```
|
||||
|
||||
Generated code will be at `lib/protoparser/opentelemetry/opentelemetry/`
|
||||
|
||||
manually edit it:
|
||||
|
||||
1) remove all external imports
|
||||
2) remove all unneeded methods
|
||||
3) replace `unknownFields` with `unknownFields []byte`
|
||||
67
lib/protoparser/opentelemetry/proto/common.proto
Normal file
67
lib/protoparser/opentelemetry/proto/common.proto
Normal file
@ -0,0 +1,67 @@
|
||||
// Copyright 2019, 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.
|
||||
|
||||
syntax = "proto3";
|
||||
|
||||
package opentelemetry;
|
||||
|
||||
option csharp_namespace = "OpenTelemetry.Proto.Common.V1";
|
||||
option java_multiple_files = true;
|
||||
option java_package = "io.opentelemetry.proto.common.v1";
|
||||
option java_outer_classname = "CommonProto";
|
||||
option go_package = "opentelemetry/pb";
|
||||
|
||||
// AnyValue is used to represent any type of attribute value. AnyValue may contain a
|
||||
// primitive value such as a string or integer or it may contain an arbitrary nested
|
||||
// object containing arrays, key-value lists and primitives.
|
||||
message AnyValue {
|
||||
// The value is one of the listed fields. It is valid for all values to be unspecified
|
||||
// in which case this AnyValue is considered to be "empty".
|
||||
oneof value {
|
||||
string string_value = 1;
|
||||
bool bool_value = 2;
|
||||
int64 int_value = 3;
|
||||
double double_value = 4;
|
||||
ArrayValue array_value = 5;
|
||||
KeyValueList kvlist_value = 6;
|
||||
bytes bytes_value = 7;
|
||||
}
|
||||
}
|
||||
|
||||
// ArrayValue is a list of AnyValue messages. We need ArrayValue as a message
|
||||
// since oneof in AnyValue does not allow repeated fields.
|
||||
message ArrayValue {
|
||||
// Array of values. The array may be empty (contain 0 elements).
|
||||
repeated AnyValue values = 1;
|
||||
}
|
||||
|
||||
// KeyValueList is a list of KeyValue messages. We need KeyValueList as a message
|
||||
// since `oneof` in AnyValue does not allow repeated fields. Everywhere else where we need
|
||||
// a list of KeyValue messages (e.g. in Span) we use `repeated KeyValue` directly to
|
||||
// avoid unnecessary extra wrapping (which slows down the protocol). The 2 approaches
|
||||
// are semantically equivalent.
|
||||
message KeyValueList {
|
||||
// A collection of key/value pairs of key-value pairs. The list may be empty (may
|
||||
// contain 0 elements).
|
||||
// The keys MUST be unique (it is not allowed to have more than one
|
||||
// value with the same key).
|
||||
repeated KeyValue values = 1;
|
||||
}
|
||||
|
||||
// KeyValue is a key-value pair that is used to store Span attributes, Link
|
||||
// attributes, etc.
|
||||
message KeyValue {
|
||||
string key = 1;
|
||||
AnyValue value = 2;
|
||||
}
|
||||
661
lib/protoparser/opentelemetry/proto/metrics.proto
Normal file
661
lib/protoparser/opentelemetry/proto/metrics.proto
Normal file
@ -0,0 +1,661 @@
|
||||
// Copyright 2019, 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.
|
||||
|
||||
syntax = "proto3";
|
||||
|
||||
package opentelemetry;
|
||||
|
||||
import "lib/protoparser/opentelemetry/proto/common.proto";
|
||||
import "lib/protoparser/opentelemetry/proto/resource.proto";
|
||||
|
||||
option csharp_namespace = "OpenTelemetry.Proto.Metrics.V1";
|
||||
option java_multiple_files = true;
|
||||
option java_package = "io.opentelemetry.proto.metrics.v1";
|
||||
option java_outer_classname = "MetricsProto";
|
||||
option go_package = "opentelemetry/pb";
|
||||
|
||||
// MetricsData represents the metrics data that can be stored in a persistent
|
||||
// storage, OR can be embedded by other protocols that transfer OTLP metrics
|
||||
// data but do not implement the OTLP protocol.
|
||||
//
|
||||
// The main difference between this message and collector protocol is that
|
||||
// in this message there will not be any "control" or "metadata" specific to
|
||||
// OTLP protocol.
|
||||
//
|
||||
// When new fields are added into this message, the OTLP request MUST be updated
|
||||
// as well.
|
||||
message MetricsData {
|
||||
// An array of ResourceMetrics.
|
||||
// For data coming from a single resource this array will typically contain
|
||||
// one element. Intermediary nodes that receive data from multiple origins
|
||||
// typically batch the data before forwarding further and in that case this
|
||||
// array will contain multiple elements.
|
||||
repeated ResourceMetrics resource_metrics = 1;
|
||||
}
|
||||
|
||||
// A collection of ScopeMetrics from a Resource.
|
||||
message ResourceMetrics {
|
||||
reserved 1000;
|
||||
|
||||
// The resource for the metrics in this message.
|
||||
// If this field is not set then no resource info is known.
|
||||
Resource resource = 1;
|
||||
|
||||
// A list of metrics that originate from a resource.
|
||||
repeated ScopeMetrics scope_metrics = 2;
|
||||
|
||||
// This schema_url applies to the data in the "resource" field. It does not apply
|
||||
// to the data in the "scope_metrics" field which have their own schema_url field.
|
||||
string schema_url = 3;
|
||||
}
|
||||
|
||||
// A collection of Metrics produced by an Scope.
|
||||
message ScopeMetrics {
|
||||
// A list of metrics that originate from an instrumentation library.
|
||||
repeated Metric metrics = 2;
|
||||
|
||||
// This schema_url applies to all metrics in the "metrics" field.
|
||||
string schema_url = 3;
|
||||
}
|
||||
|
||||
// Defines a Metric which has one or more timeseries. The following is a
|
||||
// brief summary of the Metric data model. For more details, see:
|
||||
//
|
||||
// https://github.com/open-telemetry/opentelemetry-specification/blob/main/specification/metrics/data-model.md
|
||||
//
|
||||
//
|
||||
// The data model and relation between entities is shown in the
|
||||
// diagram below. Here, "DataPoint" is the term used to refer to any
|
||||
// one of the specific data point value types, and "points" is the term used
|
||||
// to refer to any one of the lists of points contained in the Metric.
|
||||
//
|
||||
// - Metric is composed of a metadata and data.
|
||||
// - Metadata part contains a name, description, unit.
|
||||
// - Data is one of the possible types (Sum, Gauge, Histogram, Summary).
|
||||
// - DataPoint contains timestamps, attributes, and one of the possible value type
|
||||
// fields.
|
||||
//
|
||||
// Metric
|
||||
// +------------+
|
||||
// |name |
|
||||
// |description |
|
||||
// |unit | +------------------------------------+
|
||||
// |data |---> |Gauge, Sum, Histogram, Summary, ... |
|
||||
// +------------+ +------------------------------------+
|
||||
//
|
||||
// Data [One of Gauge, Sum, Histogram, Summary, ...]
|
||||
// +-----------+
|
||||
// |... | // Metadata about the Data.
|
||||
// |points |--+
|
||||
// +-----------+ |
|
||||
// | +---------------------------+
|
||||
// | |DataPoint 1 |
|
||||
// v |+------+------+ +------+ |
|
||||
// +-----+ ||label |label |...|label | |
|
||||
// | 1 |-->||value1|value2|...|valueN| |
|
||||
// +-----+ |+------+------+ +------+ |
|
||||
// | . | |+-----+ |
|
||||
// | . | ||value| |
|
||||
// | . | |+-----+ |
|
||||
// | . | +---------------------------+
|
||||
// | . | .
|
||||
// | . | .
|
||||
// | . | .
|
||||
// | . | +---------------------------+
|
||||
// | . | |DataPoint M |
|
||||
// +-----+ |+------+------+ +------+ |
|
||||
// | M |-->||label |label |...|label | |
|
||||
// +-----+ ||value1|value2|...|valueN| |
|
||||
// |+------+------+ +------+ |
|
||||
// |+-----+ |
|
||||
// ||value| |
|
||||
// |+-----+ |
|
||||
// +---------------------------+
|
||||
//
|
||||
// Each distinct type of DataPoint represents the output of a specific
|
||||
// aggregation function, the result of applying the DataPoint's
|
||||
// associated function of to one or more measurements.
|
||||
//
|
||||
// All DataPoint types have three common fields:
|
||||
// - Attributes includes key-value pairs associated with the data point
|
||||
// - TimeUnixNano is required, set to the end time of the aggregation
|
||||
// - StartTimeUnixNano is optional, but strongly encouraged for DataPoints
|
||||
// having an AggregationTemporality field, as discussed below.
|
||||
//
|
||||
// Both TimeUnixNano and StartTimeUnixNano values are expressed as
|
||||
// UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January 1970.
|
||||
//
|
||||
// # TimeUnixNano
|
||||
//
|
||||
// This field is required, having consistent interpretation across
|
||||
// DataPoint types. TimeUnixNano is the moment corresponding to when
|
||||
// the data point's aggregate value was captured.
|
||||
//
|
||||
// Data points with the 0 value for TimeUnixNano SHOULD be rejected
|
||||
// by consumers.
|
||||
//
|
||||
// # StartTimeUnixNano
|
||||
//
|
||||
// StartTimeUnixNano in general allows detecting when a sequence of
|
||||
// observations is unbroken. This field indicates to consumers the
|
||||
// start time for points with cumulative and delta
|
||||
// AggregationTemporality, and it should be included whenever possible
|
||||
// to support correct rate calculation. Although it may be omitted
|
||||
// when the start time is truly unknown, setting StartTimeUnixNano is
|
||||
// strongly encouraged.
|
||||
message Metric {
|
||||
reserved 4, 6, 8;
|
||||
|
||||
// name of the metric, including its DNS name prefix. It must be unique.
|
||||
string name = 1;
|
||||
|
||||
// description of the metric, which can be used in documentation.
|
||||
string description = 2;
|
||||
|
||||
// unit in which the metric value is reported. Follows the format
|
||||
// described by http://unitsofmeasure.org/ucum.html.
|
||||
string unit = 3;
|
||||
|
||||
// Data determines the aggregation type (if any) of the metric, what is the
|
||||
// reported value type for the data points, as well as the relatationship to
|
||||
// the time interval over which they are reported.
|
||||
oneof data {
|
||||
Gauge gauge = 5;
|
||||
Sum sum = 7;
|
||||
Histogram histogram = 9;
|
||||
ExponentialHistogram exponential_histogram = 10;
|
||||
Summary summary = 11;
|
||||
}
|
||||
}
|
||||
|
||||
// Gauge represents the type of a scalar metric that always exports the
|
||||
// "current value" for every data point. It should be used for an "unknown"
|
||||
// aggregation.
|
||||
//
|
||||
// A Gauge does not support different aggregation temporalities. Given the
|
||||
// aggregation is unknown, points cannot be combined using the same
|
||||
// aggregation, regardless of aggregation temporalities. Therefore,
|
||||
// AggregationTemporality is not included. Consequently, this also means
|
||||
// "StartTimeUnixNano" is ignored for all data points.
|
||||
message Gauge {
|
||||
repeated NumberDataPoint data_points = 1;
|
||||
}
|
||||
|
||||
// Sum represents the type of a scalar metric that is calculated as a sum of all
|
||||
// reported measurements over a time interval.
|
||||
message Sum {
|
||||
repeated NumberDataPoint data_points = 1;
|
||||
|
||||
// aggregation_temporality describes if the aggregator reports delta changes
|
||||
// since last report time, or cumulative changes since a fixed start time.
|
||||
AggregationTemporality aggregation_temporality = 2;
|
||||
|
||||
// If "true" means that the sum is monotonic.
|
||||
bool is_monotonic = 3;
|
||||
}
|
||||
|
||||
// Histogram represents the type of a metric that is calculated by aggregating
|
||||
// as a Histogram of all reported measurements over a time interval.
|
||||
message Histogram {
|
||||
repeated HistogramDataPoint data_points = 1;
|
||||
|
||||
// aggregation_temporality describes if the aggregator reports delta changes
|
||||
// since last report time, or cumulative changes since a fixed start time.
|
||||
AggregationTemporality aggregation_temporality = 2;
|
||||
}
|
||||
|
||||
// ExponentialHistogram represents the type of a metric that is calculated by aggregating
|
||||
// as a ExponentialHistogram of all reported double measurements over a time interval.
|
||||
message ExponentialHistogram {
|
||||
repeated ExponentialHistogramDataPoint data_points = 1;
|
||||
|
||||
// aggregation_temporality describes if the aggregator reports delta changes
|
||||
// since last report time, or cumulative changes since a fixed start time.
|
||||
AggregationTemporality aggregation_temporality = 2;
|
||||
}
|
||||
|
||||
// Summary metric data are used to convey quantile summaries,
|
||||
// a Prometheus (see: https://prometheus.io/docs/concepts/metric_types/#summary)
|
||||
// and OpenMetrics (see: https://github.com/OpenObservability/OpenMetrics/blob/4dbf6075567ab43296eed941037c12951faafb92/protos/prometheus.proto#L45)
|
||||
// data type. These data points cannot always be merged in a meaningful way.
|
||||
// While they can be useful in some applications, histogram data points are
|
||||
// recommended for new applications.
|
||||
message Summary {
|
||||
repeated SummaryDataPoint data_points = 1;
|
||||
}
|
||||
|
||||
// AggregationTemporality defines how a metric aggregator reports aggregated
|
||||
// values. It describes how those values relate to the time interval over
|
||||
// which they are aggregated.
|
||||
enum AggregationTemporality {
|
||||
// UNSPECIFIED is the default AggregationTemporality, it MUST not be used.
|
||||
AGGREGATION_TEMPORALITY_UNSPECIFIED = 0;
|
||||
|
||||
// DELTA is an AggregationTemporality for a metric aggregator which reports
|
||||
// changes since last report time. Successive metrics contain aggregation of
|
||||
// values from continuous and non-overlapping intervals.
|
||||
//
|
||||
// The values for a DELTA metric are based only on the time interval
|
||||
// associated with one measurement cycle. There is no dependency on
|
||||
// previous measurements like is the case for CUMULATIVE metrics.
|
||||
//
|
||||
// For example, consider a system measuring the number of requests that
|
||||
// it receives and reports the sum of these requests every second as a
|
||||
// DELTA metric:
|
||||
//
|
||||
// 1. The system starts receiving at time=t_0.
|
||||
// 2. A request is received, the system measures 1 request.
|
||||
// 3. A request is received, the system measures 1 request.
|
||||
// 4. A request is received, the system measures 1 request.
|
||||
// 5. The 1 second collection cycle ends. A metric is exported for the
|
||||
// number of requests received over the interval of time t_0 to
|
||||
// t_0+1 with a value of 3.
|
||||
// 6. A request is received, the system measures 1 request.
|
||||
// 7. A request is received, the system measures 1 request.
|
||||
// 8. The 1 second collection cycle ends. A metric is exported for the
|
||||
// number of requests received over the interval of time t_0+1 to
|
||||
// t_0+2 with a value of 2.
|
||||
AGGREGATION_TEMPORALITY_DELTA = 1;
|
||||
|
||||
// CUMULATIVE is an AggregationTemporality for a metric aggregator which
|
||||
// reports changes since a fixed start time. This means that current values
|
||||
// of a CUMULATIVE metric depend on all previous measurements since the
|
||||
// start time. Because of this, the sender is required to retain this state
|
||||
// in some form. If this state is lost or invalidated, the CUMULATIVE metric
|
||||
// values MUST be reset and a new fixed start time following the last
|
||||
// reported measurement time sent MUST be used.
|
||||
//
|
||||
// For example, consider a system measuring the number of requests that
|
||||
// it receives and reports the sum of these requests every second as a
|
||||
// CUMULATIVE metric:
|
||||
//
|
||||
// 1. The system starts receiving at time=t_0.
|
||||
// 2. A request is received, the system measures 1 request.
|
||||
// 3. A request is received, the system measures 1 request.
|
||||
// 4. A request is received, the system measures 1 request.
|
||||
// 5. The 1 second collection cycle ends. A metric is exported for the
|
||||
// number of requests received over the interval of time t_0 to
|
||||
// t_0+1 with a value of 3.
|
||||
// 6. A request is received, the system measures 1 request.
|
||||
// 7. A request is received, the system measures 1 request.
|
||||
// 8. The 1 second collection cycle ends. A metric is exported for the
|
||||
// number of requests received over the interval of time t_0 to
|
||||
// t_0+2 with a value of 5.
|
||||
// 9. The system experiences a fault and loses state.
|
||||
// 10. The system recovers and resumes receiving at time=t_1.
|
||||
// 11. A request is received, the system measures 1 request.
|
||||
// 12. The 1 second collection cycle ends. A metric is exported for the
|
||||
// number of requests received over the interval of time t_1 to
|
||||
// t_0+1 with a value of 1.
|
||||
//
|
||||
// Note: Even though, when reporting changes since last report time, using
|
||||
// CUMULATIVE is valid, it is not recommended. This may cause problems for
|
||||
// systems that do not use start_time to determine when the aggregation
|
||||
// value was reset (e.g. Prometheus).
|
||||
AGGREGATION_TEMPORALITY_CUMULATIVE = 2;
|
||||
}
|
||||
|
||||
// DataPointFlags is defined as a protobuf 'uint32' type and is to be used as a
|
||||
// bit-field representing 32 distinct boolean flags. Each flag defined in this
|
||||
// enum is a bit-mask. To test the presence of a single flag in the flags of
|
||||
// a data point, for example, use an expression like:
|
||||
//
|
||||
// (point.flags & FLAG_NO_RECORDED_VALUE) == FLAG_NO_RECORDED_VALUE
|
||||
//
|
||||
enum DataPointFlags {
|
||||
FLAG_NONE = 0;
|
||||
|
||||
// This DataPoint is valid but has no recorded value. This value
|
||||
// SHOULD be used to reflect explicitly missing data in a series, as
|
||||
// for an equivalent to the Prometheus "staleness marker".
|
||||
FLAG_NO_RECORDED_VALUE = 1;
|
||||
|
||||
// Bits 2-31 are reserved for future use.
|
||||
}
|
||||
|
||||
// NumberDataPoint is a single data point in a timeseries that describes the
|
||||
// time-varying scalar value of a metric.
|
||||
message NumberDataPoint {
|
||||
reserved 1;
|
||||
|
||||
// The set of key/value pairs that uniquely identify the timeseries from
|
||||
// where this point belongs. The list may be empty (may contain 0 elements).
|
||||
// Attribute keys MUST be unique (it is not allowed to have more than one
|
||||
// attribute with the same key).
|
||||
repeated KeyValue attributes = 7;
|
||||
|
||||
// StartTimeUnixNano is optional but strongly encouraged, see the
|
||||
// the detailed comments above Metric.
|
||||
//
|
||||
// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
|
||||
// 1970.
|
||||
fixed64 start_time_unix_nano = 2;
|
||||
|
||||
// TimeUnixNano is required, see the detailed comments above Metric.
|
||||
//
|
||||
// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
|
||||
// 1970.
|
||||
fixed64 time_unix_nano = 3;
|
||||
|
||||
// The value itself. A point is considered invalid when one of the recognized
|
||||
// value fields is not present inside this oneof.
|
||||
oneof value {
|
||||
double as_double = 4;
|
||||
sfixed64 as_int = 6;
|
||||
}
|
||||
|
||||
// (Optional) List of exemplars collected from
|
||||
// measurements that were used to form the data point
|
||||
repeated Exemplar exemplars = 5;
|
||||
|
||||
// Flags that apply to this specific data point. See DataPointFlags
|
||||
// for the available flags and their meaning.
|
||||
uint32 flags = 8;
|
||||
}
|
||||
|
||||
// HistogramDataPoint is a single data point in a timeseries that describes the
|
||||
// time-varying values of a Histogram. A Histogram contains summary statistics
|
||||
// for a population of values, it may optionally contain the distribution of
|
||||
// those values across a set of buckets.
|
||||
//
|
||||
// If the histogram contains the distribution of values, then both
|
||||
// "explicit_bounds" and "bucket counts" fields must be defined.
|
||||
// If the histogram does not contain the distribution of values, then both
|
||||
// "explicit_bounds" and "bucket_counts" must be omitted and only "count" and
|
||||
// "sum" are known.
|
||||
message HistogramDataPoint {
|
||||
reserved 1;
|
||||
|
||||
// The set of key/value pairs that uniquely identify the timeseries from
|
||||
// where this point belongs. The list may be empty (may contain 0 elements).
|
||||
// Attribute keys MUST be unique (it is not allowed to have more than one
|
||||
// attribute with the same key).
|
||||
repeated KeyValue attributes = 9;
|
||||
|
||||
// StartTimeUnixNano is optional but strongly encouraged, see the
|
||||
// the detailed comments above Metric.
|
||||
//
|
||||
// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
|
||||
// 1970.
|
||||
fixed64 start_time_unix_nano = 2;
|
||||
|
||||
// TimeUnixNano is required, see the detailed comments above Metric.
|
||||
//
|
||||
// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
|
||||
// 1970.
|
||||
fixed64 time_unix_nano = 3;
|
||||
|
||||
// count is the number of values in the population. Must be non-negative. This
|
||||
// value must be equal to the sum of the "count" fields in buckets if a
|
||||
// histogram is provided.
|
||||
fixed64 count = 4;
|
||||
|
||||
// sum of the values in the population. If count is zero then this field
|
||||
// must be zero.
|
||||
//
|
||||
// Note: Sum should only be filled out when measuring non-negative discrete
|
||||
// events, and is assumed to be monotonic over the values of these events.
|
||||
// Negative events *can* be recorded, but sum should not be filled out when
|
||||
// doing so. This is specifically to enforce compatibility w/ OpenMetrics,
|
||||
// see: https://github.com/OpenObservability/OpenMetrics/blob/main/specification/OpenMetrics.md#histogram
|
||||
optional double sum = 5;
|
||||
|
||||
// bucket_counts is an optional field contains the count values of histogram
|
||||
// for each bucket.
|
||||
//
|
||||
// The sum of the bucket_counts must equal the value in the count field.
|
||||
//
|
||||
// The number of elements in bucket_counts array must be by one greater than
|
||||
// the number of elements in explicit_bounds array.
|
||||
repeated fixed64 bucket_counts = 6;
|
||||
|
||||
// explicit_bounds specifies buckets with explicitly defined bounds for values.
|
||||
//
|
||||
// The boundaries for bucket at index i are:
|
||||
//
|
||||
// (-infinity, explicit_bounds[i]] for i == 0
|
||||
// (explicit_bounds[i-1], explicit_bounds[i]] for 0 < i < size(explicit_bounds)
|
||||
// (explicit_bounds[i-1], +infinity) for i == size(explicit_bounds)
|
||||
//
|
||||
// The values in the explicit_bounds array must be strictly increasing.
|
||||
//
|
||||
// Histogram buckets are inclusive of their upper boundary, except the last
|
||||
// bucket where the boundary is at infinity. This format is intentionally
|
||||
// compatible with the OpenMetrics histogram definition.
|
||||
repeated double explicit_bounds = 7;
|
||||
|
||||
// (Optional) List of exemplars collected from
|
||||
// measurements that were used to form the data point
|
||||
repeated Exemplar exemplars = 8;
|
||||
|
||||
// Flags that apply to this specific data point. See DataPointFlags
|
||||
// for the available flags and their meaning.
|
||||
uint32 flags = 10;
|
||||
|
||||
// min is the minimum value over (start_time, end_time].
|
||||
optional double min = 11;
|
||||
|
||||
// max is the maximum value over (start_time, end_time].
|
||||
optional double max = 12;
|
||||
}
|
||||
|
||||
// ExponentialHistogramDataPoint is a single data point in a timeseries that describes the
|
||||
// time-varying values of a ExponentialHistogram of double values. A ExponentialHistogram contains
|
||||
// summary statistics for a population of values, it may optionally contain the
|
||||
// distribution of those values across a set of buckets.
|
||||
//
|
||||
message ExponentialHistogramDataPoint {
|
||||
// The set of key/value pairs that uniquely identify the timeseries from
|
||||
// where this point belongs. The list may be empty (may contain 0 elements).
|
||||
// Attribute keys MUST be unique (it is not allowed to have more than one
|
||||
// attribute with the same key).
|
||||
repeated KeyValue attributes = 1;
|
||||
|
||||
// StartTimeUnixNano is optional but strongly encouraged, see the
|
||||
// the detailed comments above Metric.
|
||||
//
|
||||
// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
|
||||
// 1970.
|
||||
fixed64 start_time_unix_nano = 2;
|
||||
|
||||
// TimeUnixNano is required, see the detailed comments above Metric.
|
||||
//
|
||||
// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
|
||||
// 1970.
|
||||
fixed64 time_unix_nano = 3;
|
||||
|
||||
// count is the number of values in the population. Must be
|
||||
// non-negative. This value must be equal to the sum of the "bucket_counts"
|
||||
// values in the positive and negative Buckets plus the "zero_count" field.
|
||||
fixed64 count = 4;
|
||||
|
||||
// sum of the values in the population. If count is zero then this field
|
||||
// must be zero.
|
||||
//
|
||||
// Note: Sum should only be filled out when measuring non-negative discrete
|
||||
// events, and is assumed to be monotonic over the values of these events.
|
||||
// Negative events *can* be recorded, but sum should not be filled out when
|
||||
// doing so. This is specifically to enforce compatibility w/ OpenMetrics,
|
||||
// see: https://github.com/OpenObservability/OpenMetrics/blob/main/specification/OpenMetrics.md#histogram
|
||||
optional double sum = 5;
|
||||
|
||||
// scale describes the resolution of the histogram. Boundaries are
|
||||
// located at powers of the base, where:
|
||||
//
|
||||
// base = (2^(2^-scale))
|
||||
//
|
||||
// The histogram bucket identified by `index`, a signed integer,
|
||||
// contains values that are greater than (base^index) and
|
||||
// less than or equal to (base^(index+1)).
|
||||
//
|
||||
// The positive and negative ranges of the histogram are expressed
|
||||
// separately. Negative values are mapped by their absolute value
|
||||
// into the negative range using the same scale as the positive range.
|
||||
//
|
||||
// scale is not restricted by the protocol, as the permissible
|
||||
// values depend on the range of the data.
|
||||
sint32 scale = 6;
|
||||
|
||||
// zero_count is the count of values that are either exactly zero or
|
||||
// within the region considered zero by the instrumentation at the
|
||||
// tolerated degree of precision. This bucket stores values that
|
||||
// cannot be expressed using the standard exponential formula as
|
||||
// well as values that have been rounded to zero.
|
||||
//
|
||||
// Implementations MAY consider the zero bucket to have probability
|
||||
// mass equal to (zero_count / count).
|
||||
fixed64 zero_count = 7;
|
||||
|
||||
// positive carries the positive range of exponential bucket counts.
|
||||
Buckets positive = 8;
|
||||
|
||||
// negative carries the negative range of exponential bucket counts.
|
||||
Buckets negative = 9;
|
||||
|
||||
// Buckets are a set of bucket counts, encoded in a contiguous array
|
||||
// of counts.
|
||||
message Buckets {
|
||||
// Offset is the bucket index of the first entry in the bucket_counts array.
|
||||
//
|
||||
// Note: This uses a varint encoding as a simple form of compression.
|
||||
sint32 offset = 1;
|
||||
|
||||
// Count is an array of counts, where count[i] carries the count
|
||||
// of the bucket at index (offset+i). count[i] is the count of
|
||||
// values greater than base^(offset+i) and less or equal to than
|
||||
// base^(offset+i+1).
|
||||
//
|
||||
// Note: By contrast, the explicit HistogramDataPoint uses
|
||||
// fixed64. This field is expected to have many buckets,
|
||||
// especially zeros, so uint64 has been selected to ensure
|
||||
// varint encoding.
|
||||
repeated uint64 bucket_counts = 2;
|
||||
}
|
||||
|
||||
// Flags that apply to this specific data point. See DataPointFlags
|
||||
// for the available flags and their meaning.
|
||||
uint32 flags = 10;
|
||||
|
||||
// (Optional) List of exemplars collected from
|
||||
// measurements that were used to form the data point
|
||||
repeated Exemplar exemplars = 11;
|
||||
|
||||
// min is the minimum value over (start_time, end_time].
|
||||
optional double min = 12;
|
||||
|
||||
// max is the maximum value over (start_time, end_time].
|
||||
optional double max = 13;
|
||||
}
|
||||
|
||||
// SummaryDataPoint is a single data point in a timeseries that describes the
|
||||
// time-varying values of a Summary metric.
|
||||
message SummaryDataPoint {
|
||||
reserved 1;
|
||||
|
||||
// The set of key/value pairs that uniquely identify the timeseries from
|
||||
// where this point belongs. The list may be empty (may contain 0 elements).
|
||||
// Attribute keys MUST be unique (it is not allowed to have more than one
|
||||
// attribute with the same key).
|
||||
repeated KeyValue attributes = 7;
|
||||
|
||||
// StartTimeUnixNano is optional but strongly encouraged, see the
|
||||
// the detailed comments above Metric.
|
||||
//
|
||||
// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
|
||||
// 1970.
|
||||
fixed64 start_time_unix_nano = 2;
|
||||
|
||||
// TimeUnixNano is required, see the detailed comments above Metric.
|
||||
//
|
||||
// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
|
||||
// 1970.
|
||||
fixed64 time_unix_nano = 3;
|
||||
|
||||
// count is the number of values in the population. Must be non-negative.
|
||||
fixed64 count = 4;
|
||||
|
||||
// sum of the values in the population. If count is zero then this field
|
||||
// must be zero.
|
||||
//
|
||||
// Note: Sum should only be filled out when measuring non-negative discrete
|
||||
// events, and is assumed to be monotonic over the values of these events.
|
||||
// Negative events *can* be recorded, but sum should not be filled out when
|
||||
// doing so. This is specifically to enforce compatibility w/ OpenMetrics,
|
||||
// see: https://github.com/OpenObservability/OpenMetrics/blob/main/specification/OpenMetrics.md#summary
|
||||
double sum = 5;
|
||||
|
||||
// Represents the value at a given quantile of a distribution.
|
||||
//
|
||||
// To record Min and Max values following conventions are used:
|
||||
// - The 1.0 quantile is equivalent to the maximum value observed.
|
||||
// - The 0.0 quantile is equivalent to the minimum value observed.
|
||||
//
|
||||
// See the following issue for more context:
|
||||
// https://github.com/open-telemetry/opentelemetry-proto/issues/125
|
||||
message ValueAtQuantile {
|
||||
// The quantile of a distribution. Must be in the interval
|
||||
// [0.0, 1.0].
|
||||
double quantile = 1;
|
||||
|
||||
// The value at the given quantile of a distribution.
|
||||
//
|
||||
// Quantile values must NOT be negative.
|
||||
double value = 2;
|
||||
}
|
||||
|
||||
// (Optional) list of values at different quantiles of the distribution calculated
|
||||
// from the current snapshot. The quantiles must be strictly increasing.
|
||||
repeated ValueAtQuantile quantile_values = 6;
|
||||
|
||||
// Flags that apply to this specific data point. See DataPointFlags
|
||||
// for the available flags and their meaning.
|
||||
uint32 flags = 8;
|
||||
}
|
||||
|
||||
// A representation of an exemplar, which is a sample input measurement.
|
||||
// Exemplars also hold information about the environment when the measurement
|
||||
// was recorded, for example the span and trace ID of the active span when the
|
||||
// exemplar was recorded.
|
||||
message Exemplar {
|
||||
reserved 1;
|
||||
|
||||
// The set of key/value pairs that were filtered out by the aggregator, but
|
||||
// recorded alongside the original measurement. Only key/value pairs that were
|
||||
// filtered out by the aggregator should be included
|
||||
repeated KeyValue filtered_attributes = 7;
|
||||
|
||||
// time_unix_nano is the exact time when this exemplar was recorded
|
||||
//
|
||||
// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
|
||||
// 1970.
|
||||
fixed64 time_unix_nano = 2;
|
||||
|
||||
// The value of the measurement that was recorded. An exemplar is
|
||||
// considered invalid when one of the recognized value fields is not present
|
||||
// inside this oneof.
|
||||
oneof value {
|
||||
double as_double = 3;
|
||||
sfixed64 as_int = 6;
|
||||
}
|
||||
|
||||
// (Optional) Span ID of the exemplar trace.
|
||||
// span_id may be missing if the measurement is not recorded inside a trace
|
||||
// or if the trace is not sampled.
|
||||
bytes span_id = 4;
|
||||
|
||||
// (Optional) Trace ID of the exemplar trace.
|
||||
// trace_id may be missing if the measurement is not recorded inside a trace
|
||||
// or if the trace is not sampled.
|
||||
bytes trace_id = 5;
|
||||
}
|
||||
30
lib/protoparser/opentelemetry/proto/metrics_service.proto
Normal file
30
lib/protoparser/opentelemetry/proto/metrics_service.proto
Normal file
@ -0,0 +1,30 @@
|
||||
// Copyright 2019, 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.
|
||||
|
||||
syntax = "proto3";
|
||||
|
||||
package opentelemetry;
|
||||
|
||||
import "lib/protoparser/opentelemetry/proto/metrics.proto";
|
||||
|
||||
option go_package = "opentelemetry/pb";
|
||||
|
||||
message ExportMetricsServiceRequest {
|
||||
// An array of ResourceMetrics.
|
||||
// For data coming from a single resource this array will typically contain one
|
||||
// element. Intermediary nodes (such as OpenTelemetry Collector) that receive
|
||||
// data from multiple origins typically batch the data before forwarding further and
|
||||
// in that case this array will contain multiple elements.
|
||||
repeated ResourceMetrics resource_metrics = 1;
|
||||
}
|
||||
37
lib/protoparser/opentelemetry/proto/resource.proto
Normal file
37
lib/protoparser/opentelemetry/proto/resource.proto
Normal file
@ -0,0 +1,37 @@
|
||||
// Copyright 2019, 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.
|
||||
|
||||
syntax = "proto3";
|
||||
|
||||
package opentelemetry;
|
||||
|
||||
import "lib/protoparser/opentelemetry/proto/common.proto";
|
||||
|
||||
option csharp_namespace = "OpenTelemetry.Proto.Resource.V1";
|
||||
option java_multiple_files = true;
|
||||
option java_package = "io.opentelemetry.proto.resource.v1";
|
||||
option java_outer_classname = "ResourceProto";
|
||||
option go_package = "opentelemetry/pb";
|
||||
|
||||
// Resource information.
|
||||
message Resource {
|
||||
// Set of attributes that describe the resource.
|
||||
// Attribute keys MUST be unique (it is not allowed to have more than one
|
||||
// attribute with the same key).
|
||||
repeated KeyValue attributes = 1;
|
||||
|
||||
// dropped_attributes_count is the number of dropped attributes. If the value is 0, then
|
||||
// no attributes were dropped.
|
||||
uint32 dropped_attributes_count = 2;
|
||||
}
|
||||
298
lib/protoparser/opentelemetry/stream/streamparser.go
Normal file
298
lib/protoparser/opentelemetry/stream/streamparser.go
Normal file
@ -0,0 +1,298 @@
|
||||
package stream
|
||||
|
||||
import (
|
||||
"fmt"
|
||||
"io"
|
||||
"strconv"
|
||||
"sync"
|
||||
|
||||
"github.com/VictoriaMetrics/VictoriaMetrics/lib/bytesutil"
|
||||
"github.com/VictoriaMetrics/VictoriaMetrics/lib/decimal"
|
||||
"github.com/VictoriaMetrics/VictoriaMetrics/lib/fasttime"
|
||||
"github.com/VictoriaMetrics/VictoriaMetrics/lib/logger"
|
||||
"github.com/VictoriaMetrics/VictoriaMetrics/lib/prompbmarshal"
|
||||
"github.com/VictoriaMetrics/VictoriaMetrics/lib/protoparser/common"
|
||||
"github.com/VictoriaMetrics/VictoriaMetrics/lib/protoparser/opentelemetry/pb"
|
||||
"github.com/VictoriaMetrics/VictoriaMetrics/lib/writeconcurrencylimiter"
|
||||
"github.com/VictoriaMetrics/metrics"
|
||||
)
|
||||
|
||||
// ParseStream parses OpenTelemetry protobuf or json data from r and calls callback for the parsed rows.
|
||||
//
|
||||
// callback shouldn't hold tss items after returning.
|
||||
func ParseStream(r io.Reader, isGzipped bool, callback func(tss []prompbmarshal.TimeSeries) error) error {
|
||||
wcr := writeconcurrencylimiter.GetReader(r)
|
||||
defer writeconcurrencylimiter.PutReader(wcr)
|
||||
r = wcr
|
||||
|
||||
if isGzipped {
|
||||
zr, err := common.GetGzipReader(r)
|
||||
if err != nil {
|
||||
return fmt.Errorf("cannot read gzip-compressed OpenTelemetry protocol data: %w", err)
|
||||
}
|
||||
defer common.PutGzipReader(zr)
|
||||
r = zr
|
||||
}
|
||||
|
||||
wr := getWriteContext()
|
||||
defer putWriteContext(wr)
|
||||
req, err := wr.readAndUnpackRequest(r)
|
||||
if err != nil {
|
||||
return fmt.Errorf("cannot unpack OpenTelemetry metrics: %w", err)
|
||||
}
|
||||
wr.parseRequestToTss(req)
|
||||
|
||||
if err := callback(wr.tss); err != nil {
|
||||
return fmt.Errorf("error when processing OpenTelemetry samples: %w", err)
|
||||
}
|
||||
|
||||
return nil
|
||||
}
|
||||
|
||||
func (wr *writeContext) appendSamplesFromScopeMetrics(sc *pb.ScopeMetrics) {
|
||||
for _, m := range sc.Metrics {
|
||||
if len(m.Name) == 0 {
|
||||
// skip metrics without names
|
||||
continue
|
||||
}
|
||||
switch t := m.Data.(type) {
|
||||
case *pb.Metric_Gauge:
|
||||
for _, p := range t.Gauge.DataPoints {
|
||||
wr.appendSampleFromNumericPoint(m.Name, p)
|
||||
}
|
||||
case *pb.Metric_Sum:
|
||||
if t.Sum.AggregationTemporality != pb.AggregationTemporality_AGGREGATION_TEMPORALITY_CUMULATIVE {
|
||||
rowsDroppedUnsupportedSum.Inc()
|
||||
continue
|
||||
}
|
||||
for _, p := range t.Sum.DataPoints {
|
||||
wr.appendSampleFromNumericPoint(m.Name, p)
|
||||
}
|
||||
case *pb.Metric_Summary:
|
||||
for _, p := range t.Summary.DataPoints {
|
||||
wr.appendSamplesFromSummary(m.Name, p)
|
||||
}
|
||||
case *pb.Metric_Histogram:
|
||||
if t.Histogram.AggregationTemporality != pb.AggregationTemporality_AGGREGATION_TEMPORALITY_CUMULATIVE {
|
||||
rowsDroppedUnsupportedHistogram.Inc()
|
||||
continue
|
||||
}
|
||||
for _, p := range t.Histogram.DataPoints {
|
||||
wr.appendSamplesFromHistogram(m.Name, p)
|
||||
}
|
||||
default:
|
||||
rowsDroppedUnsupportedMetricType.Inc()
|
||||
logger.Warnf("unsupported type %T for metric %q", t, m.Name)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// appendSampleFromNumericPoint appends p to wr.tss
|
||||
func (wr *writeContext) appendSampleFromNumericPoint(metricName string, p *pb.NumberDataPoint) {
|
||||
var v float64
|
||||
switch t := p.Value.(type) {
|
||||
case *pb.NumberDataPoint_AsInt:
|
||||
v = float64(t.AsInt)
|
||||
case *pb.NumberDataPoint_AsDouble:
|
||||
v = t.AsDouble
|
||||
}
|
||||
|
||||
t := int64(p.TimeUnixNano / 1e6)
|
||||
isStale := (p.Flags)&uint32(1) != 0
|
||||
wr.pointLabels = appendAttributesToPromLabels(wr.pointLabels[:0], p.Attributes)
|
||||
|
||||
wr.appendSample(metricName, t, v, isStale)
|
||||
}
|
||||
|
||||
// appendSamplesFromSummary appends summary p to wr.tss
|
||||
func (wr *writeContext) appendSamplesFromSummary(metricName string, p *pb.SummaryDataPoint) {
|
||||
t := int64(p.TimeUnixNano / 1e6)
|
||||
isStale := (p.Flags)&uint32(1) != 0
|
||||
wr.pointLabels = appendAttributesToPromLabels(wr.pointLabels[:0], p.Attributes)
|
||||
|
||||
wr.appendSample(metricName+"_sum", t, p.Sum, isStale)
|
||||
wr.appendSample(metricName+"_count", t, float64(p.Count), isStale)
|
||||
for _, q := range p.QuantileValues {
|
||||
qValue := strconv.FormatFloat(q.Quantile, 'f', -1, 64)
|
||||
wr.appendSampleWithExtraLabel(metricName, "quantile", qValue, t, q.Value, isStale)
|
||||
}
|
||||
}
|
||||
|
||||
// appendSamplesFromHistogram appends histogram p to wr.tss
|
||||
func (wr *writeContext) appendSamplesFromHistogram(metricName string, p *pb.HistogramDataPoint) {
|
||||
if len(p.BucketCounts) == 0 {
|
||||
// nothing to append
|
||||
return
|
||||
}
|
||||
if len(p.BucketCounts) != len(p.ExplicitBounds)+1 {
|
||||
// fast path, broken data format
|
||||
logger.Warnf("opentelemetry bad histogram format: %q, size of buckets: %d, size of bounds: %d", metricName, len(p.BucketCounts), len(p.ExplicitBounds))
|
||||
return
|
||||
}
|
||||
|
||||
t := int64(p.TimeUnixNano / 1e6)
|
||||
isStale := (p.Flags)&uint32(1) != 0
|
||||
wr.pointLabels = appendAttributesToPromLabels(wr.pointLabels[:0], p.Attributes)
|
||||
|
||||
wr.appendSample(metricName+"_sum", t, *p.Sum, isStale)
|
||||
wr.appendSample(metricName+"_count", t, float64(p.Count), isStale)
|
||||
|
||||
var cumulative uint64
|
||||
for index, bound := range p.ExplicitBounds {
|
||||
cumulative += p.BucketCounts[index]
|
||||
boundLabelValue := strconv.FormatFloat(bound, 'f', -1, 64)
|
||||
wr.appendSampleWithExtraLabel(metricName+"_bucket", "le", boundLabelValue, t, float64(cumulative), isStale)
|
||||
}
|
||||
cumulative += p.BucketCounts[len(p.BucketCounts)-1]
|
||||
wr.appendSampleWithExtraLabel(metricName+"_bucket", "le", "+Inf", t, float64(cumulative), isStale)
|
||||
}
|
||||
|
||||
// appendSample appends sample with the given metricName to wr.tss
|
||||
func (wr *writeContext) appendSample(metricName string, t int64, v float64, isStale bool) {
|
||||
wr.appendSampleWithExtraLabel(metricName, "", "", t, v, isStale)
|
||||
}
|
||||
|
||||
// appendSampleWithExtraLabel appends sample with the given metricName and the given (labelName=labelValue) extra label to wr.tss
|
||||
func (wr *writeContext) appendSampleWithExtraLabel(metricName, labelName, labelValue string, t int64, v float64, isStale bool) {
|
||||
if isStale {
|
||||
v = decimal.StaleNaN
|
||||
}
|
||||
if t <= 0 {
|
||||
// Set the current timestamp if t isn't set.
|
||||
t = int64(fasttime.UnixTimestamp()) * 1000
|
||||
}
|
||||
|
||||
labelsPool := wr.labelsPool
|
||||
labelsLen := len(labelsPool)
|
||||
labelsPool = append(labelsPool, prompbmarshal.Label{
|
||||
Name: "__name__",
|
||||
Value: metricName,
|
||||
})
|
||||
labelsPool = append(labelsPool, wr.baseLabels...)
|
||||
labelsPool = append(labelsPool, wr.pointLabels...)
|
||||
if labelName != "" && labelValue != "" {
|
||||
labelsPool = append(labelsPool, prompbmarshal.Label{
|
||||
Name: labelName,
|
||||
Value: labelValue,
|
||||
})
|
||||
}
|
||||
|
||||
samplesPool := wr.samplesPool
|
||||
samplesLen := len(samplesPool)
|
||||
samplesPool = append(samplesPool, prompbmarshal.Sample{
|
||||
Timestamp: t,
|
||||
Value: v,
|
||||
})
|
||||
|
||||
wr.tss = append(wr.tss, prompbmarshal.TimeSeries{
|
||||
Labels: labelsPool[labelsLen:],
|
||||
Samples: samplesPool[samplesLen:],
|
||||
})
|
||||
|
||||
wr.labelsPool = labelsPool
|
||||
wr.samplesPool = samplesPool
|
||||
|
||||
rowsRead.Inc()
|
||||
}
|
||||
|
||||
// appendAttributesToPromLabels appends attributes to dst and returns the result.
|
||||
func appendAttributesToPromLabels(dst []prompbmarshal.Label, attributes []*pb.KeyValue) []prompbmarshal.Label {
|
||||
for _, at := range attributes {
|
||||
dst = append(dst, prompbmarshal.Label{
|
||||
Name: at.Key,
|
||||
Value: at.Value.FormatString(),
|
||||
})
|
||||
}
|
||||
return dst
|
||||
}
|
||||
|
||||
type writeContext struct {
|
||||
// bb holds the original data (json or protobuf), which must be parsed.
|
||||
bb bytesutil.ByteBuffer
|
||||
|
||||
// tss holds parsed time series
|
||||
tss []prompbmarshal.TimeSeries
|
||||
|
||||
// baseLabels are labels, which must be added to all the ingested samples
|
||||
baseLabels []prompbmarshal.Label
|
||||
|
||||
// pointLabels are labels, which must be added to the ingested OpenTelemetry points
|
||||
pointLabels []prompbmarshal.Label
|
||||
|
||||
// pools are used for reducing memory allocations when parsing time series
|
||||
labelsPool []prompbmarshal.Label
|
||||
samplesPool []prompbmarshal.Sample
|
||||
}
|
||||
|
||||
func (wr *writeContext) reset() {
|
||||
wr.bb.Reset()
|
||||
|
||||
tss := wr.tss
|
||||
for i := range tss {
|
||||
ts := &tss[i]
|
||||
ts.Labels = nil
|
||||
ts.Samples = nil
|
||||
}
|
||||
wr.tss = tss[:0]
|
||||
|
||||
wr.baseLabels = resetLabels(wr.baseLabels)
|
||||
wr.pointLabels = resetLabels(wr.pointLabels)
|
||||
|
||||
wr.labelsPool = resetLabels(wr.labelsPool)
|
||||
wr.samplesPool = wr.samplesPool[:0]
|
||||
}
|
||||
|
||||
func resetLabels(labels []prompbmarshal.Label) []prompbmarshal.Label {
|
||||
for i := range labels {
|
||||
label := &labels[i]
|
||||
label.Name = ""
|
||||
label.Value = ""
|
||||
}
|
||||
return labels[:0]
|
||||
}
|
||||
|
||||
func (wr *writeContext) readAndUnpackRequest(r io.Reader) (*pb.ExportMetricsServiceRequest, error) {
|
||||
if _, err := wr.bb.ReadFrom(r); err != nil {
|
||||
return nil, fmt.Errorf("cannot read request: %w", err)
|
||||
}
|
||||
var req pb.ExportMetricsServiceRequest
|
||||
if err := req.UnmarshalVT(wr.bb.B); err != nil {
|
||||
return nil, fmt.Errorf("cannot unmarshal request from %d bytes: %w", len(wr.bb.B), err)
|
||||
}
|
||||
return &req, nil
|
||||
}
|
||||
|
||||
func (wr *writeContext) parseRequestToTss(req *pb.ExportMetricsServiceRequest) {
|
||||
for _, rm := range req.ResourceMetrics {
|
||||
if rm.Resource == nil {
|
||||
// skip metrics without resource part.
|
||||
continue
|
||||
}
|
||||
wr.baseLabels = appendAttributesToPromLabels(wr.baseLabels[:0], rm.Resource.Attributes)
|
||||
for _, sc := range rm.ScopeMetrics {
|
||||
wr.appendSamplesFromScopeMetrics(sc)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
var wrPool sync.Pool
|
||||
|
||||
func getWriteContext() *writeContext {
|
||||
v := wrPool.Get()
|
||||
if v == nil {
|
||||
return &writeContext{}
|
||||
}
|
||||
return v.(*writeContext)
|
||||
}
|
||||
|
||||
func putWriteContext(wr *writeContext) {
|
||||
wr.reset()
|
||||
wrPool.Put(wr)
|
||||
}
|
||||
|
||||
var (
|
||||
rowsRead = metrics.NewCounter(`vm_protoparser_rows_read_total{type="opentelemetry"}`)
|
||||
rowsDroppedUnsupportedHistogram = metrics.NewCounter(`vm_protoparser_rows_dropped_total{type="opentelemetry",reason="unsupported_histogram_aggregation"}`)
|
||||
rowsDroppedUnsupportedSum = metrics.NewCounter(`vm_protoparser_rows_dropped_total{type="opentelemetry",reason="unsupported_sum_aggregation"}`)
|
||||
rowsDroppedUnsupportedMetricType = metrics.NewCounter(`vm_protoparser_rows_dropped_total{type="opentelemetry",reason="unsupported_metric_type"}`)
|
||||
)
|
||||
317
lib/protoparser/opentelemetry/stream/streamparser_test.go
Normal file
317
lib/protoparser/opentelemetry/stream/streamparser_test.go
Normal file
@ -0,0 +1,317 @@
|
||||
package stream
|
||||
|
||||
import (
|
||||
"bytes"
|
||||
"compress/gzip"
|
||||
"fmt"
|
||||
"reflect"
|
||||
"sort"
|
||||
"testing"
|
||||
"time"
|
||||
|
||||
"github.com/VictoriaMetrics/VictoriaMetrics/lib/fasttime"
|
||||
"github.com/VictoriaMetrics/VictoriaMetrics/lib/prompbmarshal"
|
||||
"github.com/VictoriaMetrics/VictoriaMetrics/lib/protoparser/opentelemetry/pb"
|
||||
)
|
||||
|
||||
func TestParseStream(t *testing.T) {
|
||||
f := func(samples []*pb.Metric, tssExpected []prompbmarshal.TimeSeries) {
|
||||
t.Helper()
|
||||
|
||||
checkSeries := func(tss []prompbmarshal.TimeSeries) error {
|
||||
if len(tss) != len(tssExpected) {
|
||||
return fmt.Errorf("not expected tss count, got: %d, want: %d", len(tss), len(tssExpected))
|
||||
}
|
||||
sortByMetricName(tss)
|
||||
sortByMetricName(tssExpected)
|
||||
for i := 0; i < len(tss); i++ {
|
||||
ts := tss[i]
|
||||
tsExpected := tssExpected[i]
|
||||
if len(ts.Labels) != len(tsExpected.Labels) {
|
||||
return fmt.Errorf("idx: %d, not expected labels count, got: %d, want: %d", i, len(ts.Labels), len(tsExpected.Labels))
|
||||
}
|
||||
sortLabels(ts.Labels)
|
||||
sortLabels(tsExpected.Labels)
|
||||
for j, label := range ts.Labels {
|
||||
labelExpected := tsExpected.Labels[j]
|
||||
if !reflect.DeepEqual(label, labelExpected) {
|
||||
return fmt.Errorf("idx: %d, label idx: %d, not equal label pairs, \ngot: \n%s, \nwant: \n%s",
|
||||
i, j, prettifyLabel(label), prettifyLabel(labelExpected))
|
||||
}
|
||||
}
|
||||
if len(ts.Samples) != len(tsExpected.Samples) {
|
||||
return fmt.Errorf("idx: %d, not expected samples count, got: %d, want: %d", i, len(ts.Samples), len(tsExpected.Samples))
|
||||
}
|
||||
for j, sample := range ts.Samples {
|
||||
sampleExpected := tsExpected.Samples[j]
|
||||
if !reflect.DeepEqual(sample, sampleExpected) {
|
||||
return fmt.Errorf("idx: %d, label idx: %d, not equal sample pairs, \ngot: \n%s,\nwant: \n%s",
|
||||
i, j, prettifySample(sample), prettifySample(sampleExpected))
|
||||
}
|
||||
}
|
||||
}
|
||||
return nil
|
||||
}
|
||||
|
||||
req := &pb.ExportMetricsServiceRequest{
|
||||
ResourceMetrics: []*pb.ResourceMetrics{
|
||||
generateOTLPSamples(samples),
|
||||
},
|
||||
}
|
||||
|
||||
// Verify protobuf parsing
|
||||
pbData, err := req.MarshalVT()
|
||||
if err != nil {
|
||||
t.Fatalf("cannot marshal to protobuf: %s", err)
|
||||
}
|
||||
if err := checkParseStream(pbData, checkSeries); err != nil {
|
||||
t.Fatalf("cannot parse protobuf: %s", err)
|
||||
}
|
||||
}
|
||||
|
||||
jobLabelValue := prompbmarshal.Label{
|
||||
Name: "job",
|
||||
Value: "vm",
|
||||
}
|
||||
leLabel := func(value string) prompbmarshal.Label {
|
||||
return prompbmarshal.Label{
|
||||
Name: "le",
|
||||
Value: value,
|
||||
}
|
||||
}
|
||||
kvLabel := func(k, v string) prompbmarshal.Label {
|
||||
return prompbmarshal.Label{
|
||||
Name: k,
|
||||
Value: v,
|
||||
}
|
||||
}
|
||||
|
||||
// Test all metric types
|
||||
f(
|
||||
[]*pb.Metric{
|
||||
generateGauge("my-gauge"),
|
||||
generateHistogram("my-histogram"),
|
||||
generateSum("my-sum"),
|
||||
generateSummary("my-summary"),
|
||||
},
|
||||
[]prompbmarshal.TimeSeries{
|
||||
newPromPBTs("my-gauge", 15000, 15.0, jobLabelValue, kvLabel("label1", "value1")),
|
||||
newPromPBTs("my-histogram_count", 30000, 15.0, jobLabelValue, kvLabel("label2", "value2")),
|
||||
newPromPBTs("my-histogram_sum", 30000, 30.0, jobLabelValue, kvLabel("label2", "value2")),
|
||||
newPromPBTs("my-histogram_bucket", 30000, 0.0, jobLabelValue, kvLabel("label2", "value2"), leLabel("0.1")),
|
||||
newPromPBTs("my-histogram_bucket", 30000, 5.0, jobLabelValue, kvLabel("label2", "value2"), leLabel("0.5")),
|
||||
newPromPBTs("my-histogram_bucket", 30000, 15.0, jobLabelValue, kvLabel("label2", "value2"), leLabel("1")),
|
||||
newPromPBTs("my-histogram_bucket", 30000, 15.0, jobLabelValue, kvLabel("label2", "value2"), leLabel("5")),
|
||||
newPromPBTs("my-histogram_bucket", 30000, 15.0, jobLabelValue, kvLabel("label2", "value2"), leLabel("+Inf")),
|
||||
newPromPBTs("my-sum", 150000, 15.5, jobLabelValue, kvLabel("label5", "value5")),
|
||||
newPromPBTs("my-summary_sum", 35000, 32.5, jobLabelValue, kvLabel("label6", "value6")),
|
||||
newPromPBTs("my-summary_count", 35000, 5.0, jobLabelValue, kvLabel("label6", "value6")),
|
||||
newPromPBTs("my-summary", 35000, 7.5, jobLabelValue, kvLabel("label6", "value6"), kvLabel("quantile", "0.1")),
|
||||
newPromPBTs("my-summary", 35000, 10.0, jobLabelValue, kvLabel("label6", "value6"), kvLabel("quantile", "0.5")),
|
||||
newPromPBTs("my-summary", 35000, 15.0, jobLabelValue, kvLabel("label6", "value6"), kvLabel("quantile", "1")),
|
||||
})
|
||||
|
||||
// Test gauge
|
||||
f(
|
||||
[]*pb.Metric{
|
||||
generateGauge("my-gauge"),
|
||||
},
|
||||
[]prompbmarshal.TimeSeries{
|
||||
newPromPBTs("my-gauge", 15000, 15.0, jobLabelValue, kvLabel("label1", "value1")),
|
||||
},
|
||||
)
|
||||
}
|
||||
|
||||
func checkParseStream(data []byte, checkSeries func(tss []prompbmarshal.TimeSeries) error) error {
|
||||
// Verify parsing without compression
|
||||
if err := ParseStream(bytes.NewBuffer(data), false, checkSeries); err != nil {
|
||||
return fmt.Errorf("error when parsing data: %w", err)
|
||||
}
|
||||
|
||||
// Verify parsing with compression
|
||||
var bb bytes.Buffer
|
||||
zw := gzip.NewWriter(&bb)
|
||||
if _, err := zw.Write(data); err != nil {
|
||||
return fmt.Errorf("cannot compress data: %s", err)
|
||||
}
|
||||
if err := zw.Close(); err != nil {
|
||||
return fmt.Errorf("cannot close gzip writer: %s", err)
|
||||
}
|
||||
if err := ParseStream(&bb, true, checkSeries); err != nil {
|
||||
return fmt.Errorf("error when parsing compressed data: %w", err)
|
||||
}
|
||||
|
||||
return nil
|
||||
}
|
||||
|
||||
func attributesFromKV(k, v string) []*pb.KeyValue {
|
||||
return []*pb.KeyValue{
|
||||
{
|
||||
Key: k,
|
||||
Value: &pb.AnyValue{
|
||||
Value: &pb.AnyValue_StringValue{
|
||||
StringValue: v,
|
||||
},
|
||||
},
|
||||
},
|
||||
}
|
||||
}
|
||||
|
||||
func generateGauge(name string) *pb.Metric {
|
||||
points := []*pb.NumberDataPoint{
|
||||
{
|
||||
Attributes: attributesFromKV("label1", "value1"),
|
||||
Value: &pb.NumberDataPoint_AsInt{AsInt: 15},
|
||||
TimeUnixNano: uint64(15 * time.Second),
|
||||
},
|
||||
}
|
||||
return &pb.Metric{
|
||||
Name: name,
|
||||
Data: &pb.Metric_Gauge{
|
||||
Gauge: &pb.Gauge{
|
||||
DataPoints: points,
|
||||
},
|
||||
},
|
||||
}
|
||||
}
|
||||
|
||||
func generateHistogram(name string) *pb.Metric {
|
||||
points := []*pb.HistogramDataPoint{
|
||||
{
|
||||
|
||||
Attributes: attributesFromKV("label2", "value2"),
|
||||
Count: 15,
|
||||
Sum: func() *float64 { v := 30.0; return &v }(),
|
||||
ExplicitBounds: []float64{0.1, 0.5, 1.0, 5.0},
|
||||
BucketCounts: []uint64{0, 5, 10, 0, 0},
|
||||
TimeUnixNano: uint64(30 * time.Second),
|
||||
},
|
||||
}
|
||||
return &pb.Metric{
|
||||
Name: name,
|
||||
Data: &pb.Metric_Histogram{
|
||||
Histogram: &pb.Histogram{
|
||||
AggregationTemporality: pb.AggregationTemporality_AGGREGATION_TEMPORALITY_CUMULATIVE,
|
||||
DataPoints: points,
|
||||
},
|
||||
},
|
||||
}
|
||||
}
|
||||
|
||||
func generateSum(name string) *pb.Metric {
|
||||
points := []*pb.NumberDataPoint{
|
||||
{
|
||||
Attributes: attributesFromKV("label5", "value5"),
|
||||
Value: &pb.NumberDataPoint_AsDouble{AsDouble: 15.5},
|
||||
TimeUnixNano: uint64(150 * time.Second),
|
||||
},
|
||||
}
|
||||
return &pb.Metric{
|
||||
Name: name,
|
||||
Data: &pb.Metric_Sum{
|
||||
Sum: &pb.Sum{
|
||||
AggregationTemporality: pb.AggregationTemporality_AGGREGATION_TEMPORALITY_CUMULATIVE,
|
||||
DataPoints: points,
|
||||
},
|
||||
},
|
||||
}
|
||||
}
|
||||
|
||||
func generateSummary(name string) *pb.Metric {
|
||||
points := []*pb.SummaryDataPoint{
|
||||
{
|
||||
Attributes: attributesFromKV("label6", "value6"),
|
||||
TimeUnixNano: uint64(35 * time.Second),
|
||||
Sum: 32.5,
|
||||
Count: 5,
|
||||
QuantileValues: []*pb.SummaryDataPoint_ValueAtQuantile{
|
||||
{
|
||||
Quantile: 0.1,
|
||||
Value: 7.5,
|
||||
},
|
||||
{
|
||||
Quantile: 0.5,
|
||||
Value: 10.0,
|
||||
},
|
||||
{
|
||||
Quantile: 1.0,
|
||||
Value: 15.0,
|
||||
},
|
||||
},
|
||||
},
|
||||
}
|
||||
return &pb.Metric{
|
||||
Name: name,
|
||||
Data: &pb.Metric_Summary{
|
||||
Summary: &pb.Summary{
|
||||
DataPoints: points,
|
||||
},
|
||||
},
|
||||
}
|
||||
}
|
||||
|
||||
func generateOTLPSamples(srcs []*pb.Metric) *pb.ResourceMetrics {
|
||||
otlpMetrics := &pb.ResourceMetrics{
|
||||
Resource: &pb.Resource{
|
||||
Attributes: attributesFromKV("job", "vm"),
|
||||
},
|
||||
}
|
||||
otlpMetrics.ScopeMetrics = []*pb.ScopeMetrics{
|
||||
{
|
||||
Metrics: append([]*pb.Metric{}, srcs...),
|
||||
},
|
||||
}
|
||||
return otlpMetrics
|
||||
}
|
||||
|
||||
func newPromPBTs(metricName string, t int64, v float64, extraLabels ...prompbmarshal.Label) prompbmarshal.TimeSeries {
|
||||
if t <= 0 {
|
||||
// Set the current timestamp if t isn't set.
|
||||
t = int64(fasttime.UnixTimestamp()) * 1000
|
||||
}
|
||||
ts := prompbmarshal.TimeSeries{
|
||||
Labels: []prompbmarshal.Label{
|
||||
{
|
||||
Name: "__name__",
|
||||
Value: metricName,
|
||||
},
|
||||
},
|
||||
Samples: []prompbmarshal.Sample{
|
||||
{
|
||||
Value: v,
|
||||
Timestamp: t,
|
||||
},
|
||||
},
|
||||
}
|
||||
ts.Labels = append(ts.Labels, extraLabels...)
|
||||
return ts
|
||||
}
|
||||
|
||||
func prettifyLabel(label prompbmarshal.Label) string {
|
||||
return fmt.Sprintf("name=%q value=%q", label.Name, label.Value)
|
||||
}
|
||||
|
||||
func prettifySample(sample prompbmarshal.Sample) string {
|
||||
return fmt.Sprintf("sample=%f timestamp: %d", sample.Value, sample.Timestamp)
|
||||
}
|
||||
|
||||
func sortByMetricName(tss []prompbmarshal.TimeSeries) {
|
||||
sort.Slice(tss, func(i, j int) bool {
|
||||
return getMetricName(tss[i].Labels) < getMetricName(tss[j].Labels)
|
||||
})
|
||||
}
|
||||
|
||||
func getMetricName(labels []prompbmarshal.Label) string {
|
||||
for _, l := range labels {
|
||||
if l.Name == "__name__" {
|
||||
return l.Value
|
||||
}
|
||||
}
|
||||
return ""
|
||||
}
|
||||
|
||||
func sortLabels(labels []prompbmarshal.Label) {
|
||||
sort.Slice(labels, func(i, j int) bool {
|
||||
return labels[i].Name < labels[j].Name
|
||||
})
|
||||
}
|
||||
@ -0,0 +1,39 @@
|
||||
package stream
|
||||
|
||||
import (
|
||||
"bytes"
|
||||
"testing"
|
||||
|
||||
"github.com/VictoriaMetrics/VictoriaMetrics/lib/prompbmarshal"
|
||||
"github.com/VictoriaMetrics/VictoriaMetrics/lib/protoparser/opentelemetry/pb"
|
||||
)
|
||||
|
||||
func BenchmarkParseStream(b *testing.B) {
|
||||
samples := []*pb.Metric{
|
||||
generateGauge("my-gauge"),
|
||||
generateHistogram("my-histogram"),
|
||||
generateSum("my-sum"),
|
||||
generateSummary("my-summary"),
|
||||
}
|
||||
b.SetBytes(1)
|
||||
b.ReportAllocs()
|
||||
b.RunParallel(func(p *testing.PB) {
|
||||
pbRequest := pb.ExportMetricsServiceRequest{
|
||||
ResourceMetrics: []*pb.ResourceMetrics{generateOTLPSamples(samples)},
|
||||
}
|
||||
data, err := pbRequest.MarshalVT()
|
||||
if err != nil {
|
||||
b.Fatalf("cannot marshal data: %s", err)
|
||||
}
|
||||
|
||||
for p.Next() {
|
||||
err := ParseStream(bytes.NewBuffer(data), false, func(tss []prompbmarshal.TimeSeries) error {
|
||||
return nil
|
||||
})
|
||||
if err != nil {
|
||||
b.Fatalf("cannot parse stream: %s", err)
|
||||
}
|
||||
}
|
||||
})
|
||||
|
||||
}
|
||||
Loading…
Reference in New Issue
Block a user