Exporters
Send telemetry to the OpenTelemetry Collector to make sure it’s exported correctly. Using the Collector in production environments is a best practice. To visualize your telemetry, export it to a backend such as Jaeger, Zipkin, Prometheus, or a vendor-specific backend.
Available exporters
The registry contains a list of exporters for JavaScript.
Among exporters, OpenTelemetry Protocol (OTLP) exporters are designed with the OpenTelemetry data model in mind, emitting OTel data without any loss of information. Furthermore, many tools that operate on telemetry data support OTLP (such as Prometheus, Jaeger, and most vendors), providing you with a high degree of flexibility when you need it. To learn more about OTLP, see OTLP Specification.
This page covers the main OpenTelemetry JavaScript exporters and how to set them up.
Note
If you use automatic instrumentation you can learn how to setup exporters following the Configuration Guide.
OTLP
Collector Setup
Note
If you have a OTLP collector or backend already set up, you can skip this section and setup the OTLP exporter dependencies for your application.
To try out and verify your OTLP exporters, you can run the collector in a docker container that writes telemetry directly to the console.
In an empty directory, create a file called collector-config.yaml with the
following content:
receivers:
otlp:
protocols:
grpc:
endpoint: 0.0.0.0:4317
http:
endpoint: 0.0.0.0:4318
exporters:
debug:
verbosity: detailed
service:
pipelines:
traces:
receivers: [otlp]
exporters: [debug]
metrics:
receivers: [otlp]
exporters: [debug]
logs:
receivers: [otlp]
exporters: [debug]
Now run the collector in a docker container:
docker run -p 4317:4317 -p 4318:4318 --rm -v $(pwd)/collector-config.yaml:/etc/otelcol/config.yaml otel/opentelemetry-collector
This collector is now able to accept telemetry via OTLP. Later you may want to configure the collector to send your telemetry to your observability backend.
Dependencies
If you want to send telemetry data to an OTLP endpoint (like the OpenTelemetry Collector, Jaeger or Prometheus), you can choose between three different protocols to transport your data:
Start by installing the respective exporter packages as a dependency for your project:
npm install --save @opentelemetry/exporter-trace-otlp-proto \
@opentelemetry/exporter-metrics-otlp-proto
npm install --save @opentelemetry/exporter-trace-otlp-http \
@opentelemetry/exporter-metrics-otlp-http
npm install --save @opentelemetry/exporter-trace-otlp-grpc \
@opentelemetry/exporter-metrics-otlp-grpc
Usage with Node.js
Next, configure the exporter to point at an OTLP endpoint. For example you can
update the file instrumentation.ts (or instrumentation.js if you use
JavaScript) from the
Getting Started like the following
to export traces and metrics via OTLP (http/protobuf) :
/*instrumentation.ts*/
import * as opentelemetry from '@opentelemetry/sdk-node';
import { getNodeAutoInstrumentations } from '@opentelemetry/auto-instrumentations-node';
import { OTLPTraceExporter } from '@opentelemetry/exporter-trace-otlp-proto';
import { OTLPMetricExporter } from '@opentelemetry/exporter-metrics-otlp-proto';
import { PeriodicExportingMetricReader } from '@opentelemetry/sdk-metrics';
const sdk = new opentelemetry.NodeSDK({
traceExporter: new OTLPTraceExporter({
// optional - default url is http://localhost:4318/v1/traces
url: '<your-otlp-endpoint>/v1/traces',
// optional - collection of custom headers to be sent with each request, empty by default
headers: {},
}),
metricReader: new PeriodicExportingMetricReader({
exporter: new OTLPMetricExporter({
url: '<your-otlp-endpoint>/v1/metrics', // url is optional and can be omitted - default is http://localhost:4318/v1/metrics
headers: {}, // an optional object containing custom headers to be sent with each request
}),
}),
instrumentations: [getNodeAutoInstrumentations()],
});
sdk.start();
/*instrumentation.js*/
const opentelemetry = require('@opentelemetry/sdk-node');
const {
getNodeAutoInstrumentations,
} = require('@opentelemetry/auto-instrumentations-node');
const {
OTLPTraceExporter,
} = require('@opentelemetry/exporter-trace-otlp-proto');
const {
OTLPMetricExporter,
} = require('@opentelemetry/exporter-metrics-otlp-proto');
const { PeriodicExportingMetricReader } = require('@opentelemetry/sdk-metrics');
const sdk = new opentelemetry.NodeSDK({
traceExporter: new OTLPTraceExporter({
// optional - default url is http://localhost:4318/v1/traces
url: '<your-otlp-endpoint>/v1/traces',
// optional - collection of custom headers to be sent with each request, empty by default
headers: {},
}),
metricReader: new PeriodicExportingMetricReader({
exporter: new OTLPMetricExporter({
url: '<your-otlp-endpoint>/v1/metrics', // url is optional and can be omitted - default is http://localhost:4318/v1/metrics
headers: {}, // an optional object containing custom headers to be sent with each request
concurrencyLimit: 1, // an optional limit on pending requests
}),
}),
instrumentations: [getNodeAutoInstrumentations()],
});
sdk.start();
Usage in the Browser
When you use the OTLP exporter in a browser-based application, you need to note that:
- Using gRPC for exporting is not supported
- Content Security Policies (CSPs) of your website might block your exports
- Cross-Origin Resource Sharing (CORS) headers might not allow your exports to be sent
- You might need to expose your collector to the public internet
Below you will find instructions to use the right exporter, to configure your CSPs and CORS headers and what precautions you have to take when exposing your collector.
Use OTLP exporter with HTTP/JSON or HTTP/protobuf
OpenTelemetry Collector Exporter with gRPC works only with Node.js, therefore you are limited to use the OpenTelemetry Collector Exporter with HTTP/JSON or OpenTelemetry Collector Exporter with HTTP/protobuf.
Make sure that the receiving end of your exporter (collector or observability
backend) accepts http/json if you are using OpenTelemetry Collector Exporter
with HTTP/JSON, and that you are exporting your data to the right endpoint
with your port set to 4318.
Configure CSPs
If your website is making use of Content Security Policies (CSPs), make sure
that the domain of your OTLP endpoint is included. If your collector endpoint is
https://collector.example.com:4318/v1/traces, add the following directive:
connect-src collector.example.com:4318/v1/traces
If your CSP is not including the OTLP endpoint, you will see an error message, stating that the request to your endpoint is violating the CSP directive.
Configure CORS headers
If your website and collector are hosted at a different origin, your browser might block the requests going out to your collector. You need to configure special headers for Cross-Origin Resource Sharing (CORS).
The OpenTelemetry Collector provides a feature for http-based receivers to add the required headers to allow the receiver to accept traces from a web browser:
receivers:
otlp:
protocols:
http:
include_metadata: true
cors:
allowed_origins:
- https://foo.bar.com
- https://*.test.com
allowed_headers:
- Example-Header
max_age: 7200
Securely expose your collector
To receive telemetry from a web application you need to allow the browsers of your end-users to send data to your collector. If your web application is accessible from the public internet, you also have to make your collector accessible for everyone.
It is recommended that you do not expose your collector directly, but that you put a reverse proxy (NGINX, Apache HTTP Server, …) in front of it. The reverse proxy can take care of SSL-offloading, setting the right CORS headers, and many other features specific to web applications.
Below you will find a configuration for the popular NGINX web server to get you started:
server {
listen 80 default_server;
server_name _;
location / {
# Take care of preflight requests
if ($request_method = 'OPTIONS') {
add_header 'Access-Control-Max-Age' 1728000;
add_header 'Access-Control-Allow-Origin' 'name.of.your.website.example.com' always;
add_header 'Access-Control-Allow-Headers' 'Accept,Accept-Language,Content-Language,Content-Type' always;
add_header 'Access-Control-Allow-Credentials' 'true' always;
add_header 'Content-Type' 'text/plain charset=UTF-8';
add_header 'Content-Length' 0;
return 204;
}
add_header 'Access-Control-Allow-Origin' 'name.of.your.website.example.com' always;
add_header 'Access-Control-Allow-Credentials' 'true' always;
add_header 'Access-Control-Allow-Headers' 'Accept,Accept-Language,Content-Language,Content-Type' always;
proxy_http_version 1.1;
proxy_set_header Host $host;
proxy_set_header X-Real-IP $remote_addr;
proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
proxy_pass http://collector:4318;
}
}
Console
To debug your instrumentation or see the values locally in development, you can use exporters writing telemetry data to the console (stdout).
If you followed the Getting Started or Manual Instrumentation guides, you already have the console exporter installed.
The ConsoleSpanExporter is included in the
@opentelemetry/sdk-trace-node
package and the ConsoleMetricExporter is included in the
@opentelemetry/sdk-metrics
package:
Jaeger
Jaeger natively supports OTLP to receive trace data. You can run Jaeger in a docker container with the UI accessible on port 16686 and OTLP enabled on ports 4317 and 4318:
docker run --rm \
-e COLLECTOR_ZIPKIN_HOST_PORT=:9411 \
-p 16686:16686 \
-p 4317:4317 \
-p 4318:4318 \
-p 9411:9411 \
jaegertracing/all-in-one:latest
Now following the instruction to setup the OTLP exporters.
Prometheus
To send your metric data to Prometheus, you can either
enable Prometheus’ OTLP Receiver
and use the OTLP exporter or you can use the
PrometheusHttpServer,
a MetricReader, that starts an HTTP server that will collect metrics and
serialize to Prometheus text format on request.
Backend Setup
Note
If you have Prometheus or a Prometheus-compatible backend already set up, you can skip this section and setup the Prometheus or OTLP exporter dependencies for your application.
You can run Prometheus in a docker container,
accessible on port 9090 by following these instructions:
Create a file called prometheus.yml with the following content:
scrape_configs:
- job_name: dice-service
scrape_interval: 5s
static_configs:
- targets: [host.docker.internal:9464]
Run Prometheus in a docker container with the UI accessible on port 9090:
docker run --rm -v ${PWD}/prometheus.yml:/prometheus/prometheus.yml -p 9090:9090 prom/prometheus --enable-feature=otlp-write-receive
Note
When using Prometheus’ OTLP Receiver, make sure that you set the OTLP endpoint
for metrics in your application to http://localhost:9090/api/v1/otlp.
Not all docker environments support host.docker.internal. In some cases you
may need to replace host.docker.internal with localhost or the IP address of
your machine.
Dependencies
Install the exporter package as a dependency for your application:
npm install --save @opentelemetry/exporter-prometheus
Update your OpenTelemetry configuration to use the exporter and to send data to your Prometheus backend:
import * as opentelemetry from '@opentelemetry/sdk-node';
import { getNodeAutoInstrumentations } from '@opentelemetry/auto-instrumentations-node';
import { PrometheusExporter } from '@opentelemetry/exporter-prometheus';
const sdk = new opentelemetry.NodeSDK({
metricReader: new PrometheusExporter({
port: 9464, // optional - default is 9464
}),
instrumentations: [getNodeAutoInstrumentations()],
});
sdk.start();
const opentelemetry = require('@opentelemetry/sdk-node');
const {
getNodeAutoInstrumentations,
} = require('@opentelemetry/auto-instrumentations-node');
const { PrometheusExporter } = require('@opentelemetry/exporter-prometheus');
const { PeriodicExportingMetricReader } = require('@opentelemetry/sdk-metrics');
const sdk = new opentelemetry.NodeSDK({
metricReader: new PrometheusExporter({
port: 9464, // optional - default is 9464
}),
instrumentations: [getNodeAutoInstrumentations()],
});
sdk.start();
With the above you can access your metrics at http://localhost:9464/metrics. Prometheus or an OpenTelemetry Collector with the Prometheus receiver can scrape the metrics from this endpoint.
Zipkin
Backend Setup
Note
If you have Zipkin or a Zipkin-compatible backend already set up, you can skip this section and setup the Zipkin exporter dependencies for your application.
You can run Zipkin on in a Docker container by executing the following command:
docker run --rm -d -p 9411:9411 --name zipkin openzipkin/zipkin
Dependencies
To send your trace data to Zipkin, you can use the
ZipkinExporter.
Install the exporter package as a dependency for your application:
npm install --save @opentelemetry/exporter-zipkin
Update your OpenTelemetry configuration to use the exporter and to send data to your Zipkin backend:
import * as opentelemetry from '@opentelemetry/sdk-node';
import { getNodeAutoInstrumentations } from '@opentelemetry/auto-instrumentations-node';
import { ZipkinExporter } from '@opentelemetry/exporter-zipkin';
const sdk = new opentelemetry.NodeSDK({
traceExporter: new ZipkinExporter({}),
instrumentations: [getNodeAutoInstrumentations()],
});
sdk.start();
const opentelemetry = require('@opentelemetry/sdk-node');
const {
getNodeAutoInstrumentations,
} = require('@opentelemetry/auto-instrumentations-node');
const { ZipkinExporter } = require('@opentelemetry/exporter-zipkin');
const sdk = new opentelemetry.NodeSDK({
traceExporter: new ZipkinExporter({}),
instrumentations: [getNodeAutoInstrumentations()],
});
Other available exporters
There are many other exporters available. For a list of available exporters, see the registry.
Finally, you can also write your own exporter. For more information, see the SpanExporter Interface in the API documentation.
Batching span and log records
The OpenTelemetry SDK provides a set of default span and log record processors, that allow you to either emit spans one-by-on (“simple”) or batched. Using batching is recommended, but if you do not want to batch your spans or log records, you can use a simple processor instead as follows:
/*instrumentation.ts*/
import * as opentelemetry from '@opentelemetry/sdk-node';
import { getNodeAutoInstrumentations } from '@opentelemetry/auto-instrumentations-node';
const sdk = new NodeSDK({
spanProcessor: new SimpleSpanProcessor(exporter),
instrumentations: [getNodeAutoInstrumentations()],
});
sdk.start();
/*instrumentation.js*/
const opentelemetry = require('@opentelemetry/sdk-node');
const {
getNodeAutoInstrumentations,
} = require('@opentelemetry/auto-instrumentations-node');
const sdk = new opentelemetry.NodeSDK({
spanProcessor: new SimpleSpanProcessor(exporter)
instrumentations: [getNodeAutoInstrumentations()],
});
sdk.start();