VictoriaMetrics/docs/guides/getting-started-with-opentelemetry.md

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5	How to use OpenTelemetry metrics with VictoriaMetrics	docs parent weight guides 5

VictoriaMetrics supports metrics ingestion with OpenTelemetry metrics format. This guide covers data ingestion via opentelemetry-collector and direct metrics push from application.

Pre-Requirements

• kubernetes cluster
• kubectl
• helm

Install VictoriaMetrics single-server via helm chart

Install single-server version:

helm repo add vm https://victoriametrics.github.io/helm-charts/
helm repo update 
helm install victoria-metrics vm/victoria-metrics-single

Verify it's up and running:

kubectl get pods
# victoria-metrics-victoria-metrics-single-server-0   1/1     Running   0          3m1s

Helm chart provides the following urls for reading and writing data:

Write url inside the kubernetes cluster:
   http://victoria-metrics-victoria-metrics-single-server.default.svc.cluster.local:8428

Read Data:
 The following url can be used as the datasource url in Grafana:
   http://victoria-metrics-victoria-metrics-single-server.default.svc.cluster.local:8428

Using opentelemetry-collector with VictoriaMetrics

Deploy opentelemetry-collector and configure metrics forwarding

helm repo add open-telemetry https://open-telemetry.github.io/opentelemetry-helm-charts
helm repo update 

# add values
cat << EOF > values.yaml
presets:
  clusterMetrics:
    enabled: true
config:
  exporters:
   prometheusremotewrite:
     endpoint: "http://victoria-metrics-victoria-metrics-single-server.default.svc.cluster.local:8428/api/v1/write" 
  service:
      pipelines:
        metrics:
          receivers: [otlp]
          processors: []
          exporters: [prometheusremotewrite] 
EOF

# install helm chart
helm upgrade -i otl-collector open-telemetry/opentelemetry-collector --set mode=deployment -f values.yaml

# check if pod is healthy
kubectl get pod
NAME                                                    READY   STATUS    RESTARTS   AGE
otl-colletor-opentelemetry-collector-7467bbb559-2pq2n   1/1     Running   0          23m

# forward port to local machine to verify metrics are ingested
kubectl port-forward victoria-metrics-victoria-metrics-single-server-0 8428

# check metric `k8s_container_ready` via browser http://localhost:8428/vmui/#/?g0.expr=k8s_container_ready

The full version of possible configuration options could be found in OpenTelemetry docs.

Direct metrics push

Metrics could be ingested into VictoriaMetrics directly with HTTP requests. You can use any compatible OpenTelemetry instrumentation clients. In our example, we'll create a WEB server in Golang and instrument it with metrics.

Building the Go application instrumented with metrics

See the full source code of the example here.

The list of OpenTelemetry dependencies for go.mod is the following:

go 1.20

require (
	go.opentelemetry.io/otel v1.7.0
	go.opentelemetry.io/otel/exporters/otlp/otlpmetric v0.30.0
	go.opentelemetry.io/otel/exporters/otlp/otlpmetric/otlpmetrichttp v0.30.0
	go.opentelemetry.io/otel/metric v0.30.0
	go.opentelemetry.io/otel/sdk v1.7.0
	go.opentelemetry.io/otel/sdk/metric v0.30.0
)

Let's create a new file main.go with basic implementation of the WEB server:

package main

func main() {
  mux := http.NewServeMux()
  mux.HandleFunc("/api/fast", func(writer http.ResponseWriter, request *http.Request) {
    writer.WriteHeader(http.StatusOK)
    writer.Write([]byte(`fast ok`))
  })
  mux.HandleFunc("/api/slow", func(writer http.ResponseWriter, request *http.Request) {
    time.Sleep(time.Second * 2)
    writer.WriteHeader(http.StatusOK)
    writer.Write([]byte(`slow ok`))
  })

  mw, err := newMetricsMiddleware(mux)
  if err != nil {
    panic(fmt.Sprintf("cannot build metricMiddleWare: %q", err))
  }

  go func() {
    http.ListenAndServe("localhost:8081", mw)
  }()
}

In the code above, we used newMetricsMiddleware function to create a handler for our server. Let's define it below:

type metricMiddleWare struct {
	h               http.Handler
	requestsCount   syncint64.Counter
	requestsLatency syncfloat64.Histogram
	activeRequests  int64
}

func newMetricsMiddleware(h http.Handler) (*metricMiddleWare, error) {
	mw := &metricMiddleWare{h: h}
	mc, err := newMetricsController(ctx)
	if err != nil {
		return nil, fmt.Errorf("cannot build metrics collector: %w", err)
	}
	global.SetMeterProvider(mc)

	prov := mc.Meter("")

	mw.requestsLatency, err = prov.SyncFloat64().Histogram("http_request_latency_seconds")
	if err != nil {
		return nil, fmt.Errorf("cannot create histogram: %w", err)
	}
	mw.requestsCount, err = prov.SyncInt64().Counter("http_requests_total")
	if err != nil {
		return nil, fmt.Errorf("cannot create syncInt64 counter: %w", err)
	}
	ar, err := prov.AsyncInt64().Gauge("http_active_requests")
	if err != nil {
		return nil, fmt.Errorf("cannot create AsyncInt64 gauge: %w", err)
	}
	if err := prov.RegisterCallback([]instrument.Asynchronous{ar}, func(ctx context.Context) {
		ar.Observe(ctx, atomic.LoadInt64(&mw.activeRequests))
	}); err != nil {
		return nil, fmt.Errorf("cannot Register int64 gauge: %w", err)
	}

	return mw, nil
}

The new type metricMiddleWare is instrumented with 3 metrics initialized in newMetricsMiddleware method:

• counter http_requests_total
• histogram http_request_latency_seconds
• gauge http_active_requests

Let's implement http.Handler interface for metricMiddleWare by adding ServeHTTP method:

func (m *metricMiddleWare) ServeHTTP(w http.ResponseWriter, r *http.Request) {
	t := time.Now()
	path := r.URL.Path
	m.requestsCount.Add(nil, 1, attribute.String("path", path))
	atomic.AddInt64(&m.activeRequests, 1)
	defer func() {
		atomic.AddInt64(&m.activeRequests, -1)
		m.requestsLatency.Record(nil, time.Since(t).Seconds(), attribute.String("path", path))
	}()
	m.h.ServeHTTP(w, r)
}

In method above, our middleware processes received HTTP requests and updates metrics with each new request. But for these metrics to be shipped we need to add a new method newMetricsController to organize metrics collection:

func newMetricsController(ctx context.Context) (*controller.Controller, error) {
	options := []otlpmetrichttp.Option{
		otlpmetrichttp.WithEndpoint("<VictoriaMetrics endpoint - host:port>"),
		otlpmetrichttp.WithURLPath("/opentelemetry/api/v1/push"),
	}

	metricExporter, err := otlpmetrichttp.New(ctx, options...)
	if err != nil {
		return nil, fmt.Errorf("cannot create otlphttp exporter: %w", err)
	}

	resourceConfig, err := resource.New(ctx, resource.WithAttributes(attribute.String("job", "otlp"), attribute.String("instance", "localhost")))
	if err != nil {
		return nil, fmt.Errorf("cannot create meter resource: %w", err)
	}
	meterController := controller.New(
		processor.NewFactory(
			selector.NewWithHistogramDistribution(
				histogram.WithExplicitBoundaries([]float64{0.01, 0.05, 0.1, 0.5, 0.9, 1.0, 5.0, 10.0, 100.0}),
			),
			aggregation.CumulativeTemporalitySelector(),
			processor.WithMemory(true),
		),
		controller.WithExporter(metricExporter),
		controller.WithCollectPeriod(time.Second * 10),
		controller.WithResource(resourceConfig),
	)
	if err := meterController.Start(ctx); err != nil {
		return nil, fmt.Errorf("cannot start meter controller: %w", err)
	}
	return meterController, nil
}

This controller will collect and push collected metrics to VictoriaMetrics address with interval of 10s.

See the full source code of the example here.

Test metrics ingestion

For metrics from our WEB server to be shipped to VictoriaMetrics we need make it available for ingestion. In previous steps we already deployed a single-server VictoriaMetrics, so let's make it available locally:

# port-forward victoriametrics to ingest metrics
kubectl port-forward victoria-metrics-victoria-metrics-single-server-0 8428

Now let's run our WEB server and call its APIs:

# build and run the app
go run main.go 
2024/03/25 19:27:41 Starting web server...
2024/03/25 19:27:41 web server started at localhost:8081.

# execute few queries with curl
curl http://localhost:8081/api/fast
curl http://localhost:8081/api/slow

Open vmui and query http_requests_total or http_active_requests with metricsql.

Limitations

• VictoriaMetrics doesn't support experimental JSON encoding format.
• VictoriaMetrics supports only AggregationTemporalityCumulative type for histogram and summary