Using prom-client Library for NodeJS

Importing the library & requiring it

1. Move into the forethought directory:

    cd forethought

2. Install the prom-client via npm, Node.js’s package manager:

    npm install prom-client --save

3. Open the index.js file, where we’ll be adding all of our metrics code:

    vim index.js

4. Require the use of the prom-client by adding it to our variable list:

    var express = require('express');
    var bodyParser = require('body-parser');
    var app = express();
    const prom = require('prom-client');

   With prom being the name we’ll use when calling the client library.

5. Enable default metrics scraping:

    const collectDefaultMetrics = prom.collectDefaultMetrics;
    collectDefaultMetrics({ prefix: 'forethought' });

6. Use Express to create the /metrics endpoint and call in the Prometheus data:

    app.get('/metrics', function (req, res) {
      res.set('Content-Type', prom.register.contentType);
      res.end(prom.register.metrics());
    });

Counters

1. Open up the index.js file:

    cd forethought
    $EDITOR index.js

2. Define a new metric called forethought_number_of_todos_total that works as a counter:

    // Prometheus metric definitions
    const todocounter = new prom.Counter({
      name: 'forethought_number_of_todos_total',
      help: 'The number of items added to the to-do list, total'
    });

3. Call the new metric in the addtask post function so it increases by one every time the function is called while adding a task:

    // add a task
    app.post("/addtask", function(req, res) {
      var newTask = req.body.newtask;
      task.push(newTask);
      res.redirect("/");
      todocounter.inc();
    });

   Save and exit.

4. Test the application:

    node index.js

5. While the application is running, visit MYLABSERVER:8080 and add a few tasks to the to-do list.
6. Visit MYLABSERVER:8080/metrics to view your newly created metric!

Gauges

1. Define the new gauge metric for tracking tasks added and completed:

   const todogauge = new prom.Gauge ({
     name: 'forethought_current_todos',
     help: 'Amount of incomplete tasks'
   });

2. Add a gauge .inc() to the /addtask method:

   // add a task
   app.post("/addtask", function(req, res) {
     var newTask = req.body.newtask;
     task.push(newTask);
     res.redirect("/");
     todocounter.inc();
     todogauge.inc();
   });

3. Add a gauge dec() to the /removetask method:

   // remove a task
   app.post("/removetask", function(req, res) {
     var completeTask = req.body.check;
     if (typeof completeTask === "string") {
       complete.push(completeTask);
       task.splice(task.indexOf(completeTask), 1);
     }
     else if (typeof completeTask === "object") {
       for (var i = 0; i < completeTask.length; i++) {
         complete.push(completeTask[i]);
         task.splice(task.indexOf(completeTask[i]), 1);
         todogauge.dec();
       }
     }
     res.redirect("/");
   });

   Save and exit the file.

4. Test the application:

   node index.js

5. While the application is running, visit MYLABSERVER:8080 and add a few tasks to the to-do list.
6. Visit MYLABSERVER:8080/metrics to view your newly created metric!

Summaries and Histograms

1. Move into the forethought directory:

    cd forethought

2. Install the Node.js module response-time:

    npm install response-time --save

3. Open the index.js file:

    $EDITOR index.js

4. Define both the summary and histogram metrics:

    const tasksumm = new prom.Summary ({
      name: 'forethought_requests_summ',
      help: 'Latency in percentiles',
    });
    const taskhisto = new prom.Histogram ({
      name: 'forethought_requests_hist',
      help: 'Latency in history form',
    });

5. Call the response-time module with the other variables:

    var responseTime = require('response-time');

6. Around where we define our website code, add the response-time function, calling the time parameter within our .observe metrics:

    app.use(responseTime(function (req, res, time) {
      tasksumm.observe(time);
      taskhisto.observe(time);
    }));

7. Save and exit the file.
8. Run the demo application:

    node index.js

9. View the demo application on port 8080, and add the tasks to generate metrics.
10. View the /metrics endpoint. Notice how our response times are automatically sorted into percentiles for our summary. Also notice how we’re not using all of our buckets in the histogram.
11. Return to the command line and use CTRL+C to close the demo application.
12. Reopen the index.js file:

    $EDITOR index.js

13. Add the buckets parameter to the histogram definition. We’re going to adjust our buckets based on the response times collected:

    const taskhisto = new prom.Histogram ({
      name: 'forethought_requests_hist',
      help: 'Latency in history form',
      buckets: [0.1, 0.25, 0.5, 1, 2.5, 5, 10]
    });

14. Save and exit. Run node index.js again to test.