This will walk you through the basics of putting data into seriesly and visualizing it with cubism.

You will end up with this in your browser:

Install seriesly

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go get -u -v -t github.com/dustin/seriesly

Run seriesly

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seriesly -flushDelay=1s -root=/tmp/seriesly-data

and leave it running in the background.

Create a db

In another shell:

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curl -X PUT http://localhost:3133/testdb

Write docs to db

This script will write json docs with random values for the purpose of visualization.

Copy the following to add_seriesly_docs.rb

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#!/usr/bin/env ruby

6000.times do |count|
  randomNumber = rand() # random number between 0 and 1
  cmd = "curl -X POST -d '{\"index\":#{randomNumber}}' http://localhost:3133/testdb"
  puts cmd
  system(cmd)
  system("sleep 1")
end

and then run it

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chmod +x add_seriesly_docs.rb && ./add_seriesly_docs.rb

and let it continue running in the background.

Create a webserver

Create a directory:

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mkdir /tmp/seriesly-http/
cd /tmp/seriesly-http/

Create fileserver.go:

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package main
import "net/http"
func main() {
        panic(http.ListenAndServe(":8080", http.FileServer(http.Dir("/tmp/seriesly-http/"))))
}

Run webserver:

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go run fileserver.go

Download seriesly.html file

This is a file I wrote which uses seriesly as a metric data source for cubism.

It’s a quick hack, since I couldn’t manage to get seriesism.js working.

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cd /tmp/seriesly-http/
wget https://gist.githubusercontent.com/tleyden/ec0c9be5786e0c0bd9ba/raw/1c08ea13b8ce46e08a49df19ad44c8e6a0ade896/seriesly.html

Open seriesly.html

In your browser, point to http://localhost:8080/seriesly.html

At this point, you should see the screenshot at the beginning of the blog post.

References

• seriesly
• seriesly blog post
• The simplest example of cubism
• perfrunner-visualizer