Clever Cloud Metrics is still in beta.

In addition to logs, you can have access to metrics to know how your application behaves. By default, system metrics like CPU and RAM use are available, as well as application-level metrics when available (apache or nginx status for instance).

Publish your own metrics

We currently support two ways to push / collect your metrics: the statsd protocol and Prometheus.

The statsd server listens on port 8125. You can send metrics using regular statsd protocol or using an advanced one as described here.

We also support Prometheus metrics collection. Our agent collects exposed metrics on localhost:9100/metrics. You currently have no way to customize the port or the path but if that's something you need, please ping our support team.

Display metrics

For each application, there is a Metrics tab in the console.

Overview pane

To get a quick overview of the current state of your scalers, the overview pane displays the current CPU, RAM, Disk and Network activity. On supported platforms, you can also have access to requests / second, and GC statistics.

Advanced pane

Advanced metrics allow you to access all gathered metrics, on a specified time range.

Custom queries

All metrics are stored in Warp10, so you explore data directly with the quantum interface, with WarpScript. For instance, you can derive metrics over time, do custom aggregations or combine metrics.

Custom metrics

You can expose custom metrics via statsd. These metrics will be gathered and displayed in advanced view as well. On some platforms, standard metrics published over statsd are even integrated on the overview pane.

Metrics published over statsd are prefixed with statsd.

statsd socket

To publish custom metrics, configure to use your client to push to localhost:8125 (it's the default host and port, so it should work with default settings as well).

NodeJS example

You can use node-statsd to publish metrics

// npm install node-statsd

const StatsD = require('node-statsd'),
      client = new StatsD();

// Increment: Increments a stat by a value (default is 1)

// Gauge: Gauge a stat by a specified amount
client.gauge('my_gauge', 123.45);

Haskell example

In Haskell, metrics are usually gathered with EKG. The package ekg-statsd allows to push EKG metrics over statsd.

If you're using warp, you can use wai-middleware-metrics to report request distributions (request count, responses count aggregated by status code, responses latency distribution).

EKG allows you to have access to GC metrics, make sure you compile your application with "-with-rtsopts=-T -N" to enable profiling.

{-# LANGUAGE OverloadedStrings #-}

-- you need the following packages
-- ekg-core
-- ekg-statsd
-- scotty
-- wai-middleware-metrics

import           Control.Monad                   (when)
import           Network.Wai.Metrics             (WaiMetrics, metrics,
import           System.Metrics                  (newStore, registerGcMetrics)
import           System.Remote.Monitoring.Statsd (defaultStatsdOptions,
import           Web.Scotty

handleMetrics :: IO WaiMetrics
handleMetrics = do
  store <- newStore
  registerGcMetrics store
  waiMetrics <- registerWaiMetrics store
  sendMetrics <- maybe False (== "true") <$> lookupEnv "ENABLE_METRICS"
  when sendMetrics $ do
    putStrLn "statsd reporting enabled"
    forkStatsd defaultStatsdOptions store
    return ()
  return waiMetrics

main = do
  waiMetrics <- handleMetrics
  scotty 8080 $ do
     middleware $ metrics waiMetrics
     get "/" $
       html $ "Hello world"
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