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GMT measureable reference Wagtail site implementation for energy usage benchmarking.

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Bakerydemo GOLD benchmarking for Djangocon EU 2024

This repository contains the project set up for the Djangocon EU workshop Greening Digital - how to set up your django app with green coding metrics in CI.

This is modified version of the original work by Green Coding Solutions Berlin to adapt the Django Wagtail Bakery for running in their open source energy measurement tooling software Green Metric Tool, to allow for developers to develop along the GOLD development principles - Green, Open, Lean, Distributed.

Project setup

This project is based upon Wagtail’s official bakerydemo, with tweaks to make it more suitable for local energy consumption benchmarking.

Differences with vanilla bakerydemo

With the overall goal of making the project more representative of a well-maintained real-world production site:

  • Full Debian base image rather than -slim
  • Gunicorn instead of uWSGI
  • Python 3.11 instead of 3.9
  • Latest WhiteNoise 6.2.0 for Python 3.11 compatibility
  • Up-to-date production-ready Django configuration

Differences with real-world production sites

With the overall goal of making it simpler to get the project running locally with Docker as the only requirement:

  • Running locally rather than in a data center
  • No reverse-proxy CDN caching requests
  • Serving media files with Django (bad practice) rather than dedicated object storage service (S3, Google Cloud Storage, etc)
  • Running over HTTP rather than HTTPS

Getting started

Requirement: Docker.

# Download a copy of https://github.com/thibaudcolas/bakerydemo-gold-benchmark.
cd bakerydemo-gold-benchmark
docker compose build app
docker compose up app
# The site is up and running but still needs its database initialised.
docker compose exec app ./manage.py migrate
docker compose exec app ./manage.py load_initial_data

The site is now up and running with its demo content, but still needs cache warming to be representative of a real-world production site. In particular, Wagtail generates optimised images on the fly the first time an image is requested.

Here is a sample wget command to warm up the cache:

wget --recursive --spider --no-directories http://localhost:8005/ -o warmup.log

From there, the site can be accessed at http://localhost:8005/.

Benchmark scenarios

Our scenarios cover different aspects of a site, representing real-world user journeys, all spanning multiple pages:

  • homepage-landing.js: The simplest user journey. Landing on the homepage, navigating to the bread listing page, and finally to a bread detail page.
  • blog-filtering.js: Another simple user journey. Landing on the blogs listing, filtering it by tag, and arriving on a blog page.
  • contact-us.js: Successful submission of a simple Wagtail form.
  • search.js: Usage of a search form. From the homepage, arriving on the search results for "bread", and opening one result.
  • admin.js: A simple journey through the Wagtail admin. Logging in, editing a blog page, and checking the results in the live preview.

Note although the navigation through the sequence of pages represents a real-world journey, the scenarios’ duration isn’t representative of real usage. Average times spent across different page types are:

  • Homepage: 2min
  • Listing page: 1min
  • Search results: 30s
  • Blog post: 1min30s to 8min

Puppeteer scenarios

Puppeteer test scripts are in benchmark/puppeteer. To run those scenarios (requirement: Node 18),

cd benchmark/puppeteer
npm install
# Then run each scenario with `node`.
# LIVE_DEMO=1 will make sure the browser is driven so you can see interactions on the page
# USAGE_SCENARIO_DOMAIN defines where to send the browser to connect to
LIVE_DEMO=1 USAGE_SCENARIO_DOMAIN=http://localhost:8005 node ./contact-us.js

Submitting to the hosted Green Metrics service for your own figures

You can manually submit your project to be tested via on the public Green Metrics Tool Cluster.

You can also trigger one-off code runs, with the provided python script in ./benchmark/register-for-run-with-gmt-measurement-cluster.py`

python -m venv .venv
source .venv/bin/activate
python -m pip install requests

# edit the file to point to the correct repo and where to send notifications for results
python benchmark/register-for-run-with-gmt-measurement-cluster.py

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