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ENV['LANGUAGE'] = ENV['LANG'] = ENV['LC_ALL'] = "en_US.UTF-8"
include_recipe "apt"
include_recipe "ruby_build"
include_recipe "rbenv::user"
include_recipe "rbenv::vagrant"
include_recipe "postgresql::server"
include_recipe "docker::default"
include_recipe "docker::upstart"
include_recipe "redisio::install"
@odewahn
odewahn / circles.html
Created January 13, 2014 21:47
circles.html from "Scattered to Scatterplot"
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8">
<title>D3: Data-driven circles</title>
<script type="text/javascript" src="d3.v3.js"></script>
<style type="text/css">
body {
background-color: gray;
@odewahn
odewahn / pandas-jvdp.ipynb
Created June 2, 2015 10:18
Pandas Recipe by Jake BanderPlas
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# Set up a working ipython environment
The simplest way to do this is to install Anaconda:
http://docs.continuum.io/anaconda/install.html
# Install IPython3

Network Notes

Set up a Docker of Vagrant-based lab where you set up your own network and topologies to learn, with a final case study on setting up a secure (!) VPC on AWS.

tcp/ip on Linux

  • IP addresses
  • sub-nets and CIDR
  • IPv6
  • Ports
export TOKEN=$( head -c 30 /dev/urandom | xxd -p )
export POOL_SIZE=5
export OVERPROVISION_FACTOR=2
export CPU_SHARES=$(( (1024*${OVERPROVISION_FACTOR})/${POOL_SIZE} ))
export TMPNB_NODE=bb0f0ccc-2dcb-410b-94cf-808c99324ab6-n1
export DOCKER_HOST=tcp://104.130.0.25:2376
docker run -d \
-P \
-p 80 \
export TOKEN=$( head -c 30 /dev/urandom | xxd -p )
export POOL_SIZE=5
export OVERPROVISION_FACTOR=2
export CPU_SHARES=$(( (1024*${OVERPROVISION_FACTOR})/${POOL_SIZE} ))
export TMPNB_NODE=6df651e0-4701-411d-b11c-3cbfe73b86d7-n1
export DOCKER_HOST=tcp://104.130.0.38:2376
docker run -d \
-P \
-h spark.tmpnb-oreilly.com \
package main
import (
"fmt"
"os/exec"
"strings"
)
func runCmd(cmdArgs []string) ([]string, error) {
cmdName := "docker-machine"
package main
import (
"crypto/rand"
"fmt"
"log"
"github.com/fsouza/go-dockerclient"
)