Monthly Downloads: 40
Programming language: Haskell
License: MIT License
Tags: Control     Web     Monad    
Latest version: v0.2.2.0

monad-metrics alternatives and similar packages

Based on the "monad" category.
Alternatively, view monad-metrics alternatives based on common mentions on social networks and blogs.

Do you think we are missing an alternative of monad-metrics or a related project?

Add another 'monad' Package



Build Status

This library defines a convenient wrapper and API for using EKG metrics in your application. It's heavily inspired by the metrics code that Taylor Fausak used in his Haskell application blunt.


This README is an executable literate Haskell file. If you have stack installed, then you can run the file with:


We'll need to start with the import/pragma boilerplate:

{-# LANGUAGE OverloadedStrings #-}
{-# LANGUAGE FlexibleInstances #-}
{-# LANGUAGE NoMonomorphismRestriction #-}

import qualified Control.Monad.Metrics as Metrics
import           Control.Monad.Metrics (Metrics, Resolution(..), MonadMetrics(..))
import           Control.Monad.Reader
import qualified System.Metrics        as EKG

The Control.Monad.Metrics module is designed to be imported qualified.


First, you need to initialize the Metrics data type. You can do so using initialize (to create a new EKG store) or initializeWith if you want to pass a preexisting store.

initializing :: Bool -> EKG.Store -> IO Metrics
initializing True store = Metrics.initializeWith store
initializing False _    = Metrics.initialize


The next step is to implement an instance of the class MonadMetrics for your monad transformer stack. This library has explicitly decided not to provide a concrete monad transformer to reduce the dependency footprint. Fortunately, it's pretty easy!

Suppose you've got the following stack:

type App = ReaderT Config IO

data Config = Config { configMetrics :: Metrics }

then you can easily get the required instance with:

instance MonadMetrics (ReaderT Config IO) where
    getMetrics = asks configMetrics

Now, you're off to the races! Let's record some metrics.

If you're after a really simple embedding, you can use run or run':

simple :: Int -> IO ()
simple i = 
    Metrics.run $ do
        metrics <- Metrics.getMetrics
        Metrics.gauge "Simple" i
        forM_ [1..i] $ \_ -> do
            Metrics.increment "Count!"

gettingThere :: IO ()
gettingThere = 
    Metrics.run' (\metrics -> Config metrics) $ do
        liftIO $ putStrLn "it accepts a constructor"


Once your application has the required instance, you can use EKG's metrics (counters, gauges, labels, distributions).

For detailed descriptions of the various metric types, see the corresponding EKG documentation:

Generally, the library provides "sane default" functions which accept the name of the metric to work with and the value to contribute to that metric.

w = Metrics.label "Foo" "Bar"
x = Metrics.counter "MetricName" 6
y = Metrics.distribution "Distribute" 3.4
z = Metrics.gauge "Gauge" 7

Generalized versions of these functions are available with an apostrophe. Labels accept any Showable value, while gauges and counters accept any Integral value.

a = Metrics.label' "List" [1,2,3]
b = Metrics.counter' "Count" (3 :: Integer)

You can time actions with timed, which has a resolution of seconds. You can use timed' which accepts a Resolution argument to provide a different scale.

timedProcess :: App Int
timedProcess = 
    Metrics.timed "summing1" $ do
        pure $! sum [1 .. 100000]

timedInMilliseconds :: App Int
timedInMilliseconds = 
    Metrics.timed' Microseconds "summing2" $ do
        pure $! sum [1..100]

A demonstration

main :: IO ()
main = do
    metrics <- Metrics.initialize
    flip runReaderT (Config metrics) $ do
        Metrics.label "ProgramName" "README"
        forM_ [1..10] $ \_ -> do
            Metrics.increment "up-to-ten"
        Metrics.timed' Nanoseconds "Whatever" $ do
            liftIO $ putStrLn "Hello World!"