ijsung/webperf

Performance visualization

Webperf: a performance visualization tool

What is this

Webperf is a simple web application that renders a time series of performance measurements and render it using MetricGraphics. It contains a static frontend, and a backend (based on Django REST framework) that runs on your localhost.

Installation

Because the frontend is static, we host it on Github Pages. We do still need you to install the backend on your local machine.

This document contains current recommended steps required to try out the performance visualization backend which is still WIP. After following the steps, you would have the backend up and running on localhost at port 8000 rendering one benchmark. This backend can be accessed by either the API interface directly (shown later), or via a visualization frontend currently hosted on Github Pages (http://ijsung.github.io/webperf)

There is strictly no security means set up yet, so you should make sure your local machine is well isolated behind a firewall from the Internet.

This tutorial has been verified on an OS X El Capitan machine, but should work with systems that Python, Django and SQLite run on.

Prerequisites

• Python 2.7+

Preparation

It is generally a good idea to virtualze the environment with virtualenv and/or pyenv.

• Install pip
• Install virtualenv via pip

pip install virtualenv

There are multiple ways of doing so, and what I tried was installing a slightly newer Python and pip both from homebrew.

Checkout the web-backend code

git clone https://github.com/ijsung/webperf.git

Setup python packages needed, inside virtualenv

cd webperf
# Create a virtualenv to isolate our package dependencies locally
virtualenv env
source env/bin/activate  # On Windows use `env\Scripts\activate`


# Install Django and Django REST framework into the virtualenv
pip install django
pip install djangorestframework
# Install CORS headers so that we can request JSON from the frontend on a different machine
pip install django-cors-headers
pip install django-taggit six
pip install django-taggit-serializer

Migrate or initialize the database

# Need these two commands when there’s any change to Models
python manage.py makemigrations backend
python manage.py migrate

Perform regression tests (optional)

python manage.py test
# the following steps require “pip install coverage==3.6” in the virtualenv
coverage run manage.py test -v 2 # optional. run coverage testing
coverage html #optional. generate coverage report in HTML

Run the backend locally at 127.0.0.1:8000

python manage.py runserver

Add benchmark, measurements, and visualize the results

Add a benchmark

Open your browser, go to http://localhost:8000/benchmarks/ and add at least one benchmark. The frontend now displays results with a benchmark name of your choice.

Add a measurement data point

Open your browser, go to http://localhost:8000/measurements/ and add a few entries via the form below with the benchmark added in previous step.

Try out the visualization frontend.

Go to http://ijsung.github.io/webperf/ and click the “All Results”. You should see the numbers you just added shown there in the chart.

This accesses the database we just created via JSON and renders it as a time series in your browser.