This guide will step you through setting up a Python-based virtualenv, configuring it correctly, and running your first baseline and difference against an autoscaling group (ASG). This guide assumes you’re operating on a freshly-installed Ubuntu 16.04 instance. Commands may differ in your environment.

Clone the repo:

$ git clone git@github.com:Netflix-Skunkworks/diffy.git && cd diffy

Install a virtualenv there:

$ virtualenv venv

Activate the virtualenv:

$ source venv/bin/activate

Install the required “dev” packages into the virtualenv:

$ pip install -r dev-requirements.txt

Install the local Diffy package:

$ pip install -e .

Invoke the command line client with default options, to create a new functional baseline. In the command below, replace the <asg> placeholder with the name of your autoscaling group (a concept particular to AWS):

$ diffy new baseline <asg>

You’ll find a JSON file in your current directory. This file contains the observations collected as the baseline.

Next, run an analysis across all members of that autoscaling group, to locate outliers:

$ diffy new analysis <asg>

When done, deactivate your virtualenv:

$ deactivate