Javascript (Node.JS and Browser)

NodeJS Metrics Instrumentation
Instrumenting your app
Please follow the steps outlined in the following documents:
﻿Node prom-client﻿
﻿Example implementation﻿
Setting the POD annotations
Once your application is emitting metrics, your POD in K8s will need to be annotated to enable the agent to scrape the metrics. Following are the relevant annotations:
YAML
prometheus.io/scrape: 'true'
prometheus.io/path: '/data/metrics'   # (If the metrics are served on a path other than /metrics)
prometheus.io/port: '80' # (if the metrics are served on a port other than the container port)
prometheus.io/scrape: 'true'
prometheus.io/path: '/data/metrics'   # (If the metrics are served on a path other than /metrics)
prometheus.io/port: '80' # (if the metrics are served on a port other than the container port)
﻿
Node.JS Tracing Instrumentation
OpenTelemetry is the recommended approach to instrument for tracing. Please follow the instructions in the following document to instrument your Node application:
﻿OpenTelemetry Node.JS Instrumentation﻿
When your tracing.js file (from above) is created, make sure to edit the traceExporter: to export using the Zipkin exporter to this location:
JS
  ...
+ const { ZipkinExporter } = require('@opentelemetry/exporter-zipkin');
  ...
- traceExporter: new opentelemetry.tracing.ConsoleSpanExporter(),
+ traceExporter: new ZipkinExporter({
+   serviceName: 'my-cool-app',
+   url: 'http://otel-collector.devopsnow.svc.cluster.local:9411',
+ }),
  ...
+ const { ZipkinExporter } = require('@opentelemetry/exporter-zipkin');
  ...
- traceExporter: new opentelemetry.tracing.ConsoleSpanExporter(),
+ traceExporter: new ZipkinExporter({
+   serviceName: 'my-cool-app',
+   url: 'http://otel-collector.devopsnow.svc.cluster.local:9411',
+ }),
﻿
The Zipkin URL above (http://otel collector.devopsnow.svc.cluster.local:9411) is available on all your clusters to which you installed the OpsVerse agent
This will allow the Node app to emit spans which will be collected by the OpenTelemetry collector installed as part of the OpsVerse agent and forwarded to the tracing backend.
Trace context (TraceId, SpanId and TraceFlags) injection into logs
It is very simple to configure traceId, spanId, and trace flags data injection into user logs in JavaScript applications. Based on the logging framework that is in use, follow the below mentioned steps to print the trace_id to the logs:
Winston
The following steps can be followed to to inject trace context with winston logger with OpenTelemetry instrumentation:
Step 1: Install the following dependency.
Shell
npm install --save @opentelemetry/instrumentation-winston
npm install --save @opentelemetry/instrumentation-winston
﻿
Step 2: Add the following block of code where OpenTelemetry JS instrumentation is configured (usually tracing.js file).
JS
const { WinstonInstrumentation } = require('@opentelemetry/instrumentation-winston');

registerInstrumentations({
instrumentations: [
   new WinstonInstrumentation(),
   // other instrumentations
],
});
const { WinstonInstrumentation } = require('@opentelemetry/instrumentation-winston');

registerInstrumentations({
instrumentations: [
   new WinstonInstrumentation(),
   // other instrumentations
],
});
﻿
The examples below apply to OpenTelemetry JS instrumentation version 0.23.0 or above.
More information available here.
Bunyan
The following steps can be followed to to inject trace context with bunyan logger with OpenTelemetry instrumentation:
Step 1: Install the following dependency.
Shell
npm install --save @opentelemetry/instrumentation-bunyan
npm install --save @opentelemetry/instrumentation-bunyan
﻿
Step 2: Add the following block of code where OpenTelemetry JS instrumentation is configured (usually tracing.js file).
JS
const { BunyanInstrumentation } = require('@opentelemetry/instrumentation-bunyan');

registerInstrumentations({
instrumentations: [
   new BunyanInstrumentation(),
   // other instrumentations
],
});
const { BunyanInstrumentation } = require('@opentelemetry/instrumentation-bunyan');

registerInstrumentations({
instrumentations: [
   new BunyanInstrumentation(),
   // other instrumentations
],
});
﻿
Pino
The following steps can be followed to to inject trace context with pino logger with OpenTelemetry instrumentation:
Step 1: Install the following dependency.
Shell
npm install --save @opentelemetry/instrumentation-pino
npm install --save @opentelemetry/instrumentation-pino
﻿
Step 2: Add the following block of code where OpenTelemetry JS instrumentation is configured (usually tracing.js file).
Text
const { PinoInstrumentation } = require('@opentelemetry/instrumentation-pino');

registerInstrumentations({
instrumentations: [
   new PinoInstrumentation(),
   // other instrumentations
],
});
const { PinoInstrumentation } = require('@opentelemetry/instrumentation-pino');

registerInstrumentations({
instrumentations: [
   new PinoInstrumentation(),
   // other instrumentations
],
});
﻿
Custom logger
In the case of custom loggers, the most important thing is to know how to obtain the traceId, spanId, and trace flag. Follow the steps below:
Step 1: Install the following dependency.
Shell
npm install --save @opentelemetry/api
npm install --save @opentelemetry/api
﻿
Step 2: Extract the trace context (traceId, spanId, and trace flag) using the following snippet:
JS
# Import the dependency which helps us to extract trace context
const api = require('@opentelemetry/api');

# Get the current span.
let current_span = api.trace.getSpan(api.context.active());

# Obtain trace_id, span_id and trace flag.
let trace_id = current_span.spanContext().traceId;
let span_id = current_span.spanContext().spanId;
let trace_flags = current_span.spanContext().traceFlags;
# Import the dependency which helps us to extract trace context
const api = require('@opentelemetry/api');

# Get the current span.
let current_span = api.trace.getSpan(api.context.active());

# Obtain trace_id, span_id and trace flag.
let trace_id = current_span.spanContext().traceId;
let span_id = current_span.spanContext().spanId;
let trace_flags = current_span.spanContext().traceFlags;
﻿
Example usage:
JS
console.log(`Sample log trace_id:”${trace_id}” span_id:”${span_id}” trace_flags:”${trace_flags}”`);
console.log(`Sample log trace_id:”${trace_id}” span_id:”${span_id}” trace_flags:”${trace_flags}”`);
﻿
Browser Tracing Instrumentation
OpenTelemetry is the recommended approach to instrument for tracing. Please follow the instructions in the following document to instrument your HTML/JS browser application:
﻿OpenTelemetry HTML and JS Instrumentation﻿
To start emitting spans to your observability backend, your document-load.js file (from above) should look like the following to export in Zipkin format to a TBA trace proxy host:
Text
import { ConsoleSpanExporter, SimpleSpanProcessor } from '@opentelemetry/sdk-trace-base';
import { WebTracerProvider } from '@opentelemetry/sdk-trace-web';
import { DocumentLoadInstrumentation } from '@opentelemetry/instrumentation-document-load';
import { ZoneContextManager } from '@opentelemetry/context-zone';
import { registerInstrumentations } from '@opentelemetry/instrumentation';

const provider = new WebTracerProvider();
provider.addSpanProcessor(new SimpleSpanProcessor(new ConsoleSpanExporter()));

const { ZipkinExporter } = require('@opentelemetry/exporter-zipkin');
const { BatchSpanProcessor } = require("@opentelemetry/tracing");

// You can also define your custom headers which will be added automatically.
const options = {
  // the opentelemetry collector 
  url: 'http://<jaeger-collector-proxy>',
}
const exporter = new ZipkinExporter(options);

provider.addSpanProcessor(new BatchSpanProcessor(new ZipkinExporter(options)));

provider.register({
  // Changing default contextManager to use ZoneContextManager - supports asynchronous operations - optional
  contextManager: new ZoneContextManager(),
});

// Registering instrumentations
registerInstrumentations({
  instrumentations: [
    new DocumentLoadInstrumentation(),
  ],
});
import { ConsoleSpanExporter, SimpleSpanProcessor } from '@opentelemetry/sdk-trace-base';
import { WebTracerProvider } from '@opentelemetry/sdk-trace-web';
import { DocumentLoadInstrumentation } from '@opentelemetry/instrumentation-document-load';
import { ZoneContextManager } from '@opentelemetry/context-zone';
import { registerInstrumentations } from '@opentelemetry/instrumentation';

const provider = new WebTracerProvider();
provider.addSpanProcessor(new SimpleSpanProcessor(new ConsoleSpanExporter()));

const { ZipkinExporter } = require('@opentelemetry/exporter-zipkin');
const { BatchSpanProcessor } = require("@opentelemetry/tracing");

// You can also define your custom headers which will be added automatically.
const options = {
  // the opentelemetry collector 
  url: 'http://<jaeger-collector-proxy>',
}
const exporter = new ZipkinExporter(options);

provider.addSpanProcessor(new BatchSpanProcessor(new ZipkinExporter(options)));

provider.register({
  // Changing default contextManager to use ZoneContextManager - supports asynchronous operations - optional
  contextManager: new ZoneContextManager(),
});

// Registering instrumentations
registerInstrumentations({
  instrumentations: [
    new DocumentLoadInstrumentation(),
  ],
});
﻿
This will allow your browser app to emit events to a proxy collector (which validates events are coming from your whitelisted URLs) directly to your Jaeger collector (https://<jaeger-collector-host>/api/v2/spans). There are processors running on the collector that will generate the RUM metrics.
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