Pierre-Yves Perif

Create the appropriate VPC that your application is going to live in. Create subnets for each availability zone you want to use.
Create VPC security group(s) for your auto-scaling instances. For example, if you're going to auto-scale web servers, create a "web" VPC security group.
Go into AWS console and create an ELB. Easy wizard. Select HTTP and (if needed) HTTPS. Make sure it's associated with the VPC you created in step 1.
Create an auto-scaling launch configuration from the CLI. The launch configuration has the AMI, size, and security group from step #2. The security group must be by ID not name ("sg-12345"):
```
   as-create-launch-config web --image-id ami-2e31bf1e --instance-type m1.medium \
```

-g sg-7619041a --key root

A curated list of AWS resources to prepare for the AWS Certifications

A curated list of awesome AWS resources you need to prepare for the all 5 AWS Certifications. This gist will include: open source repos, blogs & blogposts, ebooks, PDF, whitepapers, video courses, free lecture, slides, sample test and many other resources.

For more about AWS and AWS Certifications and updates to this Gist you should follow me @leonardofed

A curated list of AWS resources to prepare for the AWS Certifications

A curated list of awesome AWS resources you need to prepare for the all 5 AWS Certifications. This gist will include: open source repos, blogs & blogposts, ebooks, PDF, whitepapers, video courses, free lecture, slides, sample test and many other resources.

For more about AWS and AWS Certifications and updates to this Gist you should follow me @leonardofed

A curated list of AWS resources to prepare for the AWS Certifications

A curated list of awesome AWS resources you need to prepare for the all 5 AWS Certifications. This gist will include: open source repos, blogs & blogposts, ebooks, PDF, whitepapers, video courses, free lecture, slides, sample test and many other resources.

For more about AWS and AWS Certifications and updates to this Gist you should follow me @leonardofed

	# Use it on output : https://raw.githubusercontent.com/moby/moby/master/contrib/check-config.sh

	import re

	section = '^([A-Z][a-zA-Z0-9_ ]+)+(?:)'
	subsection = '"([^"]*)"'
	category = '([A-Z0-9_]+[A-Z]+)'

	fname='test.txt'
	with open(fname) as f:

	import pickle as pkl
	import matplotlib.pyplot as plt
	import matplotlib
	import numpy as np
	from sklearn import preprocessing
	from mpl_toolkits.axes_grid1 import make_axes_locatable
	from skimage import filters


	discriminate = True

	import pickle as pkl
	import numpy as np
	import seaborn as sns

	# load data
	scores = pkl.load(open('y_scores_20.pkl','rb'))

	# create bins
	bins = np.linspace(0, 1, 157) # 157 is determined arbitrarily
	digitized = np.digitize(scores, bins)

	import java.io._

	@SerialVersionUID(15L)
	class Animal(name: String, age: Int) extends Serializable {
	override def toString = s"Animal($name, $age)"
	}

	case class Person(name: String)

	// or fork := true in sbt

	require 'rubygems'
	require 'mechanize'

	FIRST_NAME = 'FIRST_NAME'
	LAST_NAME = 'LAST_NAME'
	PHONE = 'PHONE'
	EMAIL = '[email protected]'

	PARTY_SIZE = 2
	SCHEDULE_RANGE = { :start_time => '19:00', :end_time => '20:30' }

	asciinema rec myfile.json
	docker run --rm -v $PWD:/data asciinema/asciicast2gif -s 2 myfile.json myfile.gif
	ffmpeg -f gif -i myfile.gif myfile.mp4