Node.js package for Rotel.
This package provides an embedded lightweight agent that can collect OpenTelemetry data, built on Rotel. When started, it spawns a background daemon that accepts OpenTelemetry metrics, traces, and logs. Designed for minimal overhead, Rotel reduces resource consumption while simplifying telemetry collection and processing in Node.js applications—without requiring additional sidecar containers.
| Telemetry Type | Support |
|---|---|
| Metrics | Alpha |
| Traces | Alpha |
| Logs | Alpha |
By default, the Rotel agent listens for OpenTelemetry data over gRPC (port 4317) and HTTP (port 4318) on localhost. It efficiently batches telemetry signals and forwards them to a configurable OpenTelemetry protocol (OTLP) compatible endpoint.
In your application, you use the OpenTelemetry Javascript SDK to add instrumentation for traces, metrics, and logs. The SDK by default will communicate over ports 4317 or 4318 on localhost to the Rotel agent. You can now ship your instrumented application and efficiently export OpenTelemetry data to your vendor or observability tool of choice with a single deployment artifact.
Future updates will introduce support for filtering data, transforming telemetry, and exporting to different vendors and tools.
Add the rotel npm package to your project's dependencies. There are two approaches to configuring rotel:
- Typescript or Javascript
- Environment variables
In the startup section of your index.js or index.ts add the following code block. Replace the endpoint with the endpoint of your OpenTelemetry vendor and any required API KEY headers.
const { Rotel,Config } = require("@streamfold/rotel");
const { Client } require("@streamfold/rotel/client");
const rotel = new Rotel({
enabled: true,
exporters: {
"otlp" : Config.otlp_exporter({
endpoint: "https://foo.example.com",
headers: {
"x-api-key": "xxxxx",
},
}),
},
exporters_traces: ["otlp"],
exporters_metrics: ["otlp"],
exporters_logs: ["otlp"],
})
rotel.start()You can also configure rotel entirely with environment variables. In your application startup, insert:
const { Rotel } = require("@streamfold/rotel");
new Rotel().start();In your application deployment configuration, set the following environment variables. These match the typed configuration above:
ROTEL_ENABLED=trueROTEL_EXPORTERS=otlpROTEL_EXPORTER_OTLP_ENDPOINT=https://foo.example.comROTEL_EXPORTER_OTLP_CUSTOM_HEADERS=x-api-key={API_KEY}ROTEL_EXPORTERS_TRACES=otlpROTEL_EXPORTERS_METRICS=otlpROTEL_EXPORTERS_LOGS=otlp
Any typed configuration options will override environment variables of the same name.
See the Configuration section for the full list of options.
Once the Rotel agent is running, you may need to configure your application's instrumentation. If you are using the default rotel endpoints of localhost:4317 and localhost:4318, then you should not need to change anything.
To set the endpoint the OpenTelemetry SDK will use, set the following environment variable:
OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:4317
This is the full list of options and their environment variable alternatives. Any defaults left blank in the table are either False or None.
| Option Name | Type | Environ | Default | Options |
|---|---|---|---|---|
| enabled | boolean | ROTEL_ENABLED | ||
| pid_file | string | ROTEL_PID_FILE | /tmp/rotel-agent.pid | |
| log_file | string | ROTEL_LOG_FILE | /tmp/rotel-agent.log | |
| log_format | string | ROTEL_LOG_FORMAT | text | json, text |
| debug_log | string[] | ROTEL_DEBUG_LOG | traces, metrics | |
| otlp_grpc_endpoint | string | ROTEL_OTLP_GRPC_ENDPOINT | localhost:4317 | |
| otlp_http_endpoint | string | ROTEL_OTLP_HTTP_ENDPOINT | localhost:4318 | |
| otlp_receiver_traces_disabled | boolean | ROTEL_OTLP_RECEIVER_TRACES_DISABLED | ||
| otlp_receiver_metrics_disabled | boolean | ROTEL_OTLP_RECEIVER_METRICS_DISABLED | ||
| otlp_receiver_logs_disabled | boolean | ROTEL_OTLP_RECEIVER_LOGS_DISABLED | ||
| exporters | Map<string, Exporter> | |||
| exporters_traces | string[] | ROTEL_EXPORTERS_TRACES | ||
| exporters_metrics | string[] | ROTEL_EXPORTERS_METRICS | ||
| exporters_logs | string[] | ROTEL_EXPORTERS_LOGS |
For each exporter you would like to use, see the configuration options below. Exporters should be assigned to the exporters object with a custom name.
To construct an OTLP exporter, use the method Config.otlp_exporter() with the following options.
| Option Name | Type | Default | Options |
|---|---|---|---|
| endpoint | string | ||
| protocol | string | grpc | grpc or http |
| headers | Map<string, string> | ||
| compression | string | gzip | gzip or none |
| request_timeout | string | 5s | |
| retry_initial_backoff | string | 5s | |
| retry_max_backoff | string | 30s | |
| retry_max_elapsed_time | string | 300s | |
| batch_max_size | number | 8192 | |
| batch_timeout | string | 200ms | |
| tls_cert_file | string | ||
| tls_key_file | string | ||
| tls_ca_file | string | ||
| tls_skip_verify | boolean |
Rotel provides an experimental Datadog exporter that supports traces at the moment. Construct a Datadog exporter with the method Config.datadog_exporter() using the following options.
| Option Name | Type | Default | Options |
|---|---|---|---|
| region | string | us1 | us1, us3, us5, eu, ap1 |
| custom_endpoint | string | ||
| api_key | string |
Rotel provides a ClickHouse exporter with support for metrics, logs, and traces. Construct a ClickHouse exporter with the method Config.clickhouse_exporter() using the following options.
| Option Name | Type | Default | Options |
|---|---|---|---|
| endpoint | string | ||
| database | string | otel | |
| table_prefix | string | otel | |
| compression | string | lz4 | |
| async_insert | boolean | true | |
| user | string | ||
| password | string | ||
| enable_json | boolean | ||
| json_underscore | boolean |
Rotel provides a Kafka exporter with support for metrics, logs, and traces. Construct a Kafka exporter with the method Config.kafka_exporter() using the following options.
| Option Name | Type | Default | Options |
|---|---|---|---|
| brokers | string[] | localhost:9092 | |
| traces_topic | string | otlp_traces | |
| logs_topic | string | otlp_logs | |
| metrics_topic | string | otlp_metrics | |
| format | string | protobuf | json, protobuf |
| compression | string | none | gzip, snappy, lz4, zstd, none |
| acks | string | one | all, one, none |
| client_id | string | rotel | |
| max_message_bytes | number | 1000000 | |
| linger_ms | number | 5 | |
| retries | number | 2147483647 | |
| retry_backoff_ms | number | 100 | |
| retry_backoff_max_ms | number | 1000 | |
| message_timeout_ms | number | 300000 | |
| request_timeout_ms | number | 30000 | |
| batch_size | number | 1000000 | |
| partitioner | string | consistent-random | consistent, consistent-random, murmur2-random, murmur2, fnv1a, fnv1a-random |
| partition_metrics_by_resource_attributes | boolean | ||
| partition_logs_by_resource_attributes | boolean | ||
| custom_config | string | ||
| sasl_username | string | ||
| sasl_password | string | ||
| sasl_mechanism | string | ||
| security_protocol | string | PLAINTEXT | PLAINTEXT, SSL, SASL_PLAINTEXT, SASL_SSL |
The Blackhole exporter is useful for testing purposes. It accepts telemetry data but does not forward it anywhere. Construct a Blackhole exporter with the method Config.blackhole_exporter(). This exporter has no configuration options.
Rotel supports multiple exporters, allowing you to send data to different destinations per telemetry type. Just set the exporters entry to an object of exporter definitions and then configure the exporters per telemetry type. For example, this will send metrics and logs to an OTLP endpoint while sending traces to Datadog:
const { Rotel, Config } = require("@streamfold/rotel");
const rotel = new Rotel({
enabled: true,
exporters: {
"logs_and_metrics": Config.otlp_exporter({
endpoint: "https://foo.example.com",
headers: {
"x-api-key": process.env.API_KEY,
"x-data-set": "testing"
}
}),
"tracing": Config.datadog_exporter({
api_key: "1234abcd",
}),
},
// Define exporters per telemetry type
exporters_traces: ["tracing"],
exporters_metrics: ["logs_and_metrics"],
exporters_logs: ["logs_and_metrics"]
});
rotel.start();When using the OTLP exporter over HTTP, the exporter will append /v1/traces, /v1/metrics, or /v1/logs to the endpoint URL for traces, metrics, and logs respectively. If the service you are exporting telemetry data to does not support these standard URL paths, you can individually override them for traces, metrics, and logs.
For example, to override the endpoint for traces and metrics you can do the following:
const { Rotel, Config } = require("@streamfold/rotel");
const rotel = new Rotel({
enabled: true,
exporters: {
"otlp": Config.otlp_exporter({
headers: {
"x-api-key": "xxxxx",
},
traces: {
endpoint: "http://foo.example.com:4318/api/otlp/traces",
},
metrics: {
endpoint: "http://foo.example.com:4318/api/otlp/metrics",
}
})
},
exporters_traces: ["otlp"],
exporters_metrics: ["otlp"],
exporters_logs: ["otlp"]
});
rotel.start();Or, you can override the endpoints using environment variables:
ROTEL_OTLP_EXPORTER_TRACES_ENDPOINT=http://foo.example.com:4318/api/otlp/tracesROTEL_OTLP_EXPORTER_METRICS_ENDPOINT=http://foo.example.com:4318/api/otlp/metricsROTEL_OTLP_EXPORTER_METRICS_ENDPOINT=http://foo.example.com:4318/api/otlp/logs
All the OTLP exporter settings can be overridden per endpoint type (traces, metrics, logs). Any value that is not overridden will fall back to the top-level exporter configuration or the default.
You can override the default request timeout of 5 seconds for the OTLP Exporter with the exporter setting:
request_timeout: Takes a string time duration, so"250ms"for 250 milliseconds,"3s"for 3 seconds, etc.
Requests will be retried if they match retryable error codes like 429 (Too Many Requests) or timeout. You can control the behavior with the following exporter options:
retry_initial_backoff: Initial backoff durationretry_max_backoff: Maximum backoff intervalretry_max_elapsed_time: Maximum wall time a request will be retried for until it is marked as permanent failure
All options should be represented as string time durations.
To illustrate this further, here's a full example of how to use Rotel to send trace spans to Axiom from an application instrumented with OpenTelemetry.
The code sample depends on the following environment variables:
ROTEL_ENABLED=true: Turn on or off based on the deployment environmentAXIOM_DATASET: Name of an Axiom datasetAXIOM_API_TOKEN: Set to an API token that has access to the Axiom dataset
const { Rotel, Config } = require("@streamfold/rotel");
const { NodeTracerProvider } = require('@opentelemetry/sdk-trace-node');
const { OTLPTraceExporter } = require('@opentelemetry/exporter-trace-otlp-grpc');
const { trace } = require('@opentelemetry/api');
const { SimpleSpanProcessor } = require('@opentelemetry/sdk-trace-base');
const { ATTR_SERVICE_NAME } = require ('@opentelemetry/semantic-conventions');
const { resourceFromAttributes } = require('@opentelemetry/resources');
function initRotel() {
const rotel = new Rotel({
enabled: true,
exporters: {
"axiom": Config.otlp_exporter({
endpoint: "https://api.axiom.co",
protocol: "http",
headers: {
"Authorization": "Bearer " + process.env.AXIOM_API_TOKEN,
"X-Axiom-Dataset": process.env.AXIOM_DATASET
}
})
},
exporters_traces: ["axiom"],
exporters_metrics: ["axiom"],
exporters_logs: ["axiom"]
})
return rotel;
}
function initOtel() {
const exporter = new OTLPTraceExporter({
url: 'http://127.0.0.1:4317', // points to out local Rotel
});
// Initialize the tracer provider
const provider = new NodeTracerProvider({
resource: resourceFromAttributes({
[ATTR_SERVICE_NAME]: 'rotel-nodejs-service',
}),
spanProcessors: [
new SimpleSpanProcessor(exporter)
],
});
// Register the provider as the global tracer provider
provider.register();
return provider;
}
async function sleep(ms) {
return new Promise(resolve => setTimeout(resolve, ms));
}
// Main routine
async function main() {
const rotel = initRotel();
const provider = initOtel();
rotel.start();
console.log("Hello from example");
const tracer = trace.getTracer('rotel-node-js-hello-world');
console.log("starting main span");
const mainSpan = tracer.startSpan('main');
// sleep for a second to simulate span start/end time
await sleep(1000);
mainSpan.end();
console.log("main span ended, flushing")
await provider.forceFlush();
await provider.shutdown();
rotel.stop();
console.log("goodbye")
}
main();For the complete example, see the hello world application.
If you set the option debug_log to ["traces"], or the environment variable ROTEL_DEBUG_LOG=traces, then rotel will log a summary to the log file /tmp/rotel-agent.log each time it processes trace spans. You can add also specify metrics to debug metrics and logs to debug logs.
In most deployment environments you do not need to call rotel.stop() and it is generally recommended that you don't. Calling rotel.stop() will
terminate the running agent on a host, so any further export calls from OTEL instrumentation will fail. In a multiprocess environment, such as
clusters of node.js processes, terminating the Rotel agent from one process will terminate it for all other processes. On ephemeral deployment platforms, it is
usually fine to leave the agent running until the compute instance, VM/container/isolate, terminate.
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See the DEVELOPING.md doc for building and development instructions.