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.
- IP addresses
- sub-nets and CIDR
- IPv6
- Ports
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" |
<!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; |
# 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 |
https://github.com/rackerlabs/carina/releases
$ mv carina-darwin-amd64 /usr/local/bin/carina
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" | |
) |