Website docs update 0821

website_docs/_index.md

@@ -12,16 +12,16 @@ export data.
 
 ## Status and Releases
 
-|       | Tracing | Metrics |
-| ----- | ------- | ------- |
-| API   | GA      | Alpha   |
-| SDK   | Beta    | Alpha   |
+| Signal  | API Status  | SDK Status        |
+|---------|-------------|-------------------|
+| Trace   | Stable      | Release Candidate |
+| Metrics | Development | Development       |
+| Logs    | Roadmap     | Roadmap           |
 
 You can find release information [here](https://github.com/open-telemetry/opentelemetry-js/releases)
 
 ## Further Reading
 
 - [OpenTelemetry for JavaScript on GitHub](https://github.com/open-telemetry/opentelemetry-js)
-- [Getting Started](https://github.com/open-telemetry/opentelemetry-js/blob/main/getting-started/README.md)
-- [API Documentation](https://open-telemetry.github.io/opentelemetry-js)
-- [Getting In Touch (Gitter)](https://gitter.im/open-telemetry/opentelemetry-sdk-trace-node)
+- [API Reference](https://open-telemetry.github.io/opentelemetry-js-api)
+- [SDK Reference](https://open-telemetry.github.io/opentelemetry-js)

website_docs/exporters.md

@@ -3,11 +3,15 @@ title: "Exporters"
 weight: 3
 ---
 
-In order to visualize and analyze your traces, you will need to export them to a tracing backend such as Jaeger or Zipkin.
-OpenTelemetry JS provides exporters for some common open source tracing backends.
+In order to visualize and analyze your traces and metrics, you will need to export them to a  backend such as [Jaeger](https://www.jaegertracing.io/) or [Zipkin](https://zipkin.io/). OpenTelemetry JS provides exporters for some common open source backends.
 
 Below you will find some introductions on how to setup backends and the matching exporters.
 
+- [Jaeger](#jaeger)
+- [Zipkin](#zipkin)
+- [Prometheus](#prometheus)
+- [OpenTelemetry Collector](#opentelemetry-collector)
+
 ## Jaeger
 
 To set up Jaeger as quickly as possible, run it in a docker container:
@@ -64,6 +68,43 @@ const { BatchSpanProcessor } = require("@opentelemetry/tracing");
 provider.addSpanProcessor(new BatchSpanProcessor(new ZipkinExporter()))
 ```
 
+## Prometheus
+
+To set up Prometheus as quickly as possible, run it in a docker container.
+You will need a `prometheus.yml` to configure the backend, use the following example
+and modify it to your needs:
+
+```yml
+global:
+  scrape_interval: 15s
+  evaluation_interval: 15s
+
+scrape_configs:
+  - job_name: "prometheus"
+    static_configs:
+      - targets: ["localhost:9090"]
+```
+
+With this file you can now start the docker container:
+
+```shell
+docker run \
+    -p 9090:9090 \
+    -v ${PWD}/prometheus.yml:/etc/prometheus/prometheus.yml \
+    prom/prometheus
+```
+
+Update your opentelemetry configuration to use the exporter and to send data to your prometheus backend:
+
+```javascript
+const { PrometheusExporter } = require('@opentelemetry/exporter-prometheus');
+const { MeterProvider }  = require('@opentelemetry/metrics');
+const meter = new MeterProvider({
+  exporter: new PrometheusExporter({port: 9090}),
+  interval: 1000,
+}).getMeter('prometheus');
+```
+
 ## OpenTelemetry Collector
 
 If you are looking for a vendor-agnostic way to receive, process and export your

website_docs/getting_started/nodejs.md

@@ -15,6 +15,12 @@ This guide will show you how to get started with tracing in Node.js.
     - [Instrumentation Modules](#instrumentation-modules)
   - [Setup](#setup)
   - [Run Application](#run-application)
+- [Metrics](#metrics)
+  - [Dependencies](#dependencies-2)
+    - [Core Dependencies](#core-dependencies-1)
+    - [Exporter](#exporter-1)
+  - [Setup](#setup-1)
+  - [Run Application](#run-application-1)
 
 ## Example Application
 
@@ -220,3 +226,119 @@ Now, when you open <http://localhost:8080> in your web browser, you should see t
 ```
 
 </details>
+
+## Metrics
+
+### Dependencies
+
+The following dependencies are required to collect metrics in your Node.js application.
+
+#### Core Dependencies
+
+These dependencies are required to configure the tracing SDK and create spans.
+
+- `@opentelemetry/metrics`
+
+#### Exporter
+
+In the following example, we will use the `ConsoleMetricExporter` which prints all spans to the console.
+
+In order to visualize and analyze your metrics, you will need to export them to a metrics backend.
+Follow [these instructions](../exporters.md) for setting up a backend and exporter.
+
+### Setup
+
+You need a `Meter` to create and monitor metrics. A `Meter` in OpenTelemetry is the mechanism used to create and manage metrics, labels, and metric exporters.
+
+Create a file named `monitoring.js` and add the following code:
+
+```javascript
+/* monitoring.js */
+'use strict';
+
+const { MeterProvider, ConsoleMetricExporter } = require('@opentelemetry/metrics');
+
+const meter = new MeterProvider({
+  new ConsoleMetricExporter(),
+  interval: 1000,
+}).getMeter('your-meter-name');
+```
+
+Now you can require this file from your application code and use the `Meter` to create and manage metrics. The simplest of these metrics is a counter.
+
+Let's create and export from your `monitoring.js` file a middleware function that express can use to count all requests by route. Modify the `monitoring.js` file so it looks like this:
+
+```javascript
+/* monitoring.js */
+'use strict';
+
+const { MeterProvider, ConsoleMetricExporter } = require('@opentelemetry/metrics');
+
+const meter = new MeterProvider({
+  new ConsoleMetricExporter(),
+  interval: 1000,
+}).getMeter('your-meter-name');
+
+const requestCount = meter.createCounter("requests", {
+  description: "Count all incoming requests"
+});
+
+const boundInstruments = new Map();
+
+module.exports.countAllRequests = () => {
+  return (req, res, next) => {
+    if (!boundInstruments.has(req.path)) {
+      const labels = { route: req.path };
+      const boundCounter = requestCount.bind(labels);
+      boundInstruments.set(req.path, boundCounter);
+    }
+
+    boundInstruments.get(req.path).add(1);
+    next();
+  };
+};
+```
+
+Now import and use this middleware in your application code `app.js`:
+
+```javascript
+/* app.js */
+const express = require("express");
+const { countAllRequests } = require("./monitoring");
+const app = express();
+app.use(countAllRequests());
+/* ... */
+```
+
+Now when you make requests to your service, your meter will count all requests.
+
+**Note**: Creating a new labelSet and binding on every request is not ideal because creating the labelSet can often be an expensive operation. Therefore, the instruments are created and stored in a Map according to the route key.
+
+### Run Application
+
+First, install the dependencies as described above. Here you need to add the following:
+
+```shell
+npm install --save @opentelemetry/metrics
+```
+
+Now you can run your application:
+
+```shell
+$ node app.js
+Listening for requests on http://localhost:8080
+```
+
+Now, when you open <http://localhost:8080> in your web browser, you should see the metrics printed in the console by the `ConsoleMetricExporter`.
+
+```json
+{
+  "name": "requests",
+  "description": "Count all incoming requests",
+  "unit": "1",
+  "metricKind": 0,
+  "valueType": 1
+}
+{ "route": "/" }
+"value": "1"
+```

website_docs/instrumentation.md

@@ -5,6 +5,14 @@ weight: 3
 
 This guide will cover creating and annotating spans, creating and annotating metrics, how to pass context, and a guide to automatic instrumentation for JavaScript. This simple example works in the browser as well as with Node.JS
 
+- [Example Application](#example-application)
+- [Creating Spans](#creating-spans)
+- [Attributes](#attributes)
+  - [Semantic Attributes](#semantic-attributes)
+- [Span Status](#span-status)
+
+## Example Application
+
 In the following this guide will use the following sample app:
 
 ```javascript
@@ -161,3 +169,30 @@ function doWork(parent) {
   span.end();
 }
 ```
+
+## Span Status
+
+A status can be set on a span, to indicate if the traced operation has completed successfully (`Ok`) or with an `Error`. The default status is `Unset`.
+
+The status can be set at any time before the span is finished:
+
+```javascript
+function doWork(parent) {
+  const span = tracer.startSpan('doWork', {
+    parent,
+  });
+  span.setStatus({
+    code: opentelemetry.SpanStatusCode.OK,
+    message: 'Ok.'
+  })
+  for (let i = 0; i <= Math.floor(Math.random() * 40000000); i += 1) {
+    if(i > 10000) {
+      span.setStatus({
+        code: opentelemetry.SpanStatusCode.ERROR,
+        message: 'Error.'
+      })
+    }
+  }
+  span.end();
+}
+```