The ekg-push package

[ Tags: bsd3, library, system ] [ Propose Tags ]

This library lets you push metric samples to a broadcast channel. Consumers can then persist the samples as they wish.

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Versions 0.0.2, 0.0.3
Change log
Dependencies base (>=4.5 && <4.9), bytestring (<1.0), ekg-core (==0.1.*), ekg-push (==0.0.3), text (<1.3), time (<1.5), unordered-containers (<0.3) [details]
License BSD3[multiple license files]
Author Andrew Darqui
Category System
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Source repo head: git clone
Uploaded Sat Jun 6 18:34:26 UTC 2015 by adarqui
Distributions NixOS:0.0.3
Executables basic
Downloads 577 total (8 in the last 30 days)
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Status Docs available [build log]
Last success reported on 2015-06-09 [all 1 reports]
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build the example program


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Maintainer's Corner

For package maintainers and hackage trustees

Readme for ekg-push-0.0.3

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Modifications of ekg-statsd by Johan Tibell to provide a generic "push" framework.

You will notice this is almost identical to ekg-statsd. It's just me trying to abstract away the basic functionality found in ekg-statsd, so not to have to duplicate this code anywhere else. Eventually I may try to clean up this "abstraction" and create a PR in ekg-core.

TODO: Soon

So, the idea of ekg-push is to create a simple framework so that I can create agents such as:

  • ekg-push-redis
  • ekg-push-file
  • ekg-push-statsd
  • ekg-push-uberlog


Push agents simply 'subscribe' to the push handle returned by forkPush. Once subscribed, agents call consume and handle the Metric.Sample data how they want.


You can just type 'make' to install ekg-push into a local sandbox. Or you can use cabal:

cabal install ekg-push

Getting started

make examples

See examples/basic.hs

main :: IO ()
main = do
    store <- newStore
    registerGcMetrics store
    iters <- createCounter "iterations" store
    push <- forkPush defaultPushOptions { prefix = "pfx", suffix = "sfx" } store

    ch1 <- subscribe push
    _ <- forkIO $ forever $ do
            msg <- consume ch1
            putStrLn $ "subscription #1: " ++ show  msg

    let loop n = do
            evaluate $ mean [1..n]
            threadDelay 2000
            loop n

    loop 1000000

-- adarqui