{"id":43,"date":"2013-11-22T05:14:06","date_gmt":"2013-11-22T05:14:06","guid":{"rendered":"http:\/\/blogs.nd.edu\/devops\/?p=43"},"modified":"2013-11-22T05:26:32","modified_gmt":"2013-11-22T05:26:32","slug":"scripting-aws-with-boto","status":"publish","type":"post","link":"https:\/\/sites.nd.edu\/devops\/2013\/11\/22\/scripting-aws-with-boto\/","title":{"rendered":"Scripting AWS with Boto"},"content":{"rendered":"

It’s pretty easy to get yourself an Amazon Web Services account, log into the web console, and start firing up instances left and right. \u00a0It feels awesome, and it should, because you are doing a lot of cool things with just a few mouse clicks. \u00a0Soon, however, that buzz is going to wear off, because working this way is not sustainable at scale, and it is not easily repeatable. \u00a0If you want to get to #DevOps nirvana, creating and destroying instances automatically with each branch commit, you are going to have to abandon that GUI and get to the command line.\u00a0
\n<\/em><\/p>\n

So you google up “aws command line,” and behold: AWS Command Line Interface.<\/a>\u00a0 These tools are great, and probably worth a blog post in themselves. \u00a0They are an attempt to provide a unified CLI to replace prior offerings that were unique to each service (e.g., an ec2 tool, a CloudFormation tool), and they let you do quite a bit from the command line. But wait, because if you want to control everything in AWS while also leveraging the power of a mature scripting language, you want\u00a0Boto for Python<\/a>.<\/p>\n

First, we’ll need python. \u00a0Mac and Linux users are good to go; Windows users will need to install it first<\/a>. \u00a0We’re also going to need the python package manager, called pip. \u00a0For some reason it doesn’t come with python, but there’s a python tool that’ll fetch it for us. \u00a0This worked on my mac:<\/p>\n

$ sudo easy_install pip\r\n\r\n<\/pre>\n
Okay, now you’d better\u00a0learn some basic Python syntax<\/a>. Go ahead; I’ll wait.<\/p>\n
Good. \u00a0Now we’re ready. \u00a0Install the boto SDK with pip:<\/p>\n
$ pip install boto\r\n\r\n<\/pre>\n
Then create a file called .boto in your home directory with the following contents:<\/p>\n
[Credentials]\r\naws_access_key_id = YOUR_ACCESS_KEY_ID\r\naws_secret_access_key = YOUR_SECRET_ACCESS_KEY\r\n\r\n<\/pre>\n
Where to get those credentials? \u00a0I’ll let this guy tell you<\/a>.<\/p>\n
Now we’re ready for some examples. \u00a0Readers in the OIT can check out the full scripts here<\/a>. \u00a0Let’s start by making a Virtual Private Cloud, aka a virtual data center. \u00a0VPCs are constructs that, despite their relative importance in a cloud infrastructure, are quite simple to create. \u00a0From create_vpc.py:<\/p>\n
#!\/usr\/bin\/python\r\nimport boto\r\nfrom boto.vpc import VPCConnection\r\n\r\n<\/pre>\n
You’ve got the typical shebang directive, which invokes the python interpreter and lets us execute the script directly. \u00a0Then the important part: importing boto. \u00a0The first import is really all you need, but if you want to be able to reference parts of the boto library without fully qualifying them, you’ll want to do something like line 3 there. \u00a0This lets us reference “VPCConnection” instead of having to say “boto.vpc.VPCConnection.”<\/p>\n
The parameters for creating a VPC are…<\/p>\n