@uswitch/koa-prometheus

🌡️ A configurable Prometheus data collector with Koa middleware

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🌡️ Koa Prometheus

A configurable <b>Prometheus</b> data collector with <b>Koa</b> middleware


Overview | Usage | Api | Configuration | Contributors



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Overview

This package is a thin wrapper around prom-client & metrics, to provide prometheus formatted metrics for Koa applications.
It provides the following types of metric;
  • 📊 Histogram - Raw number counts, bucketed
  • 📈 Summary - Percentile calculated buckets
  • ⏱ Meter - an EWMA decaying gauge for counting over time
  • 🌡 Gauge - A counter that can go both up and down
  • ğŸŽš Counter - Count number of times something happens
  • 🏷 Labelling - Labelling to enable powerful Prometheus querying

It will also provide you with a /metrics endpoint to expose these metrics to prometheus

Usage

koa-prometheus is purely config based and configurable, but you can attach it to your Koa service using default metrics with the following;
import Koa from 'koa'
import Meter from '@uswitch/koa-prometheus'

const app = new Koa()
const meters = Meter({ /* Config */ }, { loadDefaults: true })

app.use(meters.middleware)   // The middleware that makes the meters available

app.get('/metrics', (ctx) => (ctx.body = meters.print()))

app.on(eventAccess, (ctx) => meters.automark(ctx))
app.on(eventError, () => meters.errorRate.mark(1))

app.listen(3000, () => signal.start(Listening on port 3000))

N.B. See koa-core

Purely config

The main philsophy of Koa prometheus is to provide a way to configure the metrics, and how to collect them, in pure JSON.
To do this, you can create a config file that contains a list of metrics, .e.g
[
  // A manually invoked meter
  { 
    "name": "namespace_metric_name",
    "help": "A description of the metric",
    "type": "Counter"
  },
  // An `automark` meter
  {
    "name": "namespace_autocollected_metric",
    "help": "A description of the metric",
    "type": "Histogram",
    "labelNames": [
      { "key": "method", "path": ["path", "to", "method"] },
      { "key": "status", "path": ["path", "to", "status"] }
    ],
    "mark": { 
      "method": "observe",
      "path": [ "path","to","value" ]
    }
  }
]

See the schema or the defaults for a more detailed look at how they are configured.

API

You get back the configured meter when you instantiate it, and you will get

Manually marking a meter

If you have a manual meter it will be available on the meters object. If you want to add labels to the meter, you must add them in the order they are defined in the config, i.e.
// "labelName": [ "a", "b", "c" ]

meter
  .myMeter
  .labels("value for a", "value for b", "value for c")
  .inc(1)

NodeJS metrics & GC Metrics

This library also utilises prom-client's collectDefaultMetrics & node-prometheus-gc-stats to collect CPU & Garbage Collection stats

Service standard metrics

To comply with Uswitch service standard() monitoring, enable service standards:
const meters = Meter({ /* Config */ }, { loadStandards: true })

These will overwrite the http_request_duration_seconds, http_requests_total and errors_total metrics. The first two are automarked by @uswitch/koa-access. Mark the errors_total metric manually:
// Directly
app.on('error', (err, ctx) => {
  meters.errorsTotal.labels(err.name).inc(1)
})
// Or with @uswitch/koa-tracer
app.on(eventError, (err, ctx) => {
  meters.errorsTotal.labels(err.name).inc(1)
})

Contributors

Thanks goes to these wonderful people (emoji key):
|
Dom Charlesworth

📖 💻 🤔 🔌 |
David Annez

💻 🤔 🔌 | | :---: | :---: |
This project follows the all-contributors specification. Contributions of any kind welcome!