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 firstname.lastname@example.org: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: