Fabric: a System Administrator's Best Friend

Adrian Hannah — Tue, 09 Apr 2013 19:09:40 +0000

Do you routinely make changes to more than a dozen machines at a time? Read this article to find out about a tool to make that task much easier.

I'll be honest. Even though this library is fully five years old, I hadn't heard of Fabric until about six months ago. Now I can't imagine not having it in my digital tool belt. Fabric is a Python library/tool that is designed to use SSH to execute system administration and deployment tasks on one or more remote machines. No more running the same task, machine by machine, to make one change across the board. It is a simple fire-and-forget tool that will make your life so much simpler. Not only can you run simple tasks via SSH on multiple machines, but since you're using Python code to execute items, you can combine it with any arbitrary Python code to make robust, complex, elegant applications for deployment or administration tasks.

Installation

Fabric requires Python 2.5 or later, the setuptools packaging/installation library, the ssh Python library, and SSH and its dependencies. For the most part, you won't have to worry about any of this, because Fabric can be installed easily through various package managers. The easiest, and most prolific way to install Fabric is using pip (or easy_install). On most systems, you can use your systems package manager (apt-get, install, and so on) to install it (the package either will be fabric or python-fabric). If you're feeling froggy, you can check out the git repository and hack away at the source code.

Once installed, you will have access to the fab script from the command line.

Operations

The Fabric library is composed of nine separate operations that can be used in conjunction to achieve your desired effect. Simply insert these functions into your fabfile and off you go:

get(remote_path, local_path=None) — get allows you to pull files from the remote machine to your local machine. This is like using rsync or scp to copy a file or files from many machines. This is super effective for systematically collecting log files or backups in a central location. The remote path is the path of the file on the remote machine that you are grabbing, and the local path is the path to which you want to save the file on the local machine. If the local path is omitted, Fabric assumes you are saving the file to the working directory.
local(command, capture=False) — the local function allows you to take action on the local host in a similar fashion to the Python subprocess module (in fact, local is a simplistic wrapper that sits on top of the subprocess module). Simply supply the command to run and, if needed, whether you want to capture the output. If you specify capture=True, the output will be returned as a string from local, otherwise it will be output to STDOUT.

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