Load Test Output
In this tutorial, we will show you how to use Neocortix Cloud Services Scalable Compute to run a distributed Performance Test batch job, using a Puppeteer and Lighthouse client.
First, please follow the steps in the tutorial Setting Up For Batch Jobs. After completion of the initial setup, you will have a directory with examples,
In the subdirectory
you will find the runBatchPuppeteerLighthouse.py command. This script will create a set of instances running on mobile devices, one instance for each load generator. In the default example provided, we ask for 5 successful instances:
startFrame = 1, endFrame = 5, nWorkers = 10,
By setting
nWorkers = 10
, we slightly over-allocate instances to allow for some fraction to fail.
It will command the instances to install Node.js, Chromium, Puppeteer, and Lighthouse, and then run Puppeteer to capture a screenshot of the Google.com home page, and then run Lighthouse to analyze the Google.com home page.
def frameCmd( self, frameNum ): cmd = 'date && export NODE_PATH=/usr/local/lib/node_modules && export PATH=$PATH:/usr/local/bin && node %s && lighthouse https://www.google.com --no-enable-error-reporting --chrome-flags="--headless --no-sandbox" --emulated-form-factor=none --throttling-method=provided && mv google.png google_%03d.png && mv *google*.html google_%03d.html && tar -zcvf Puppeteer_results_%03d.tar.gz google*' % ( self.PuppeteerFilePath, frameNum, frameNum, frameNum ) return cmd
The output of each instance will be a Puppeteer screenshot image file
and a Lighthouse performance report
. It will also produce a
file, showing the locations of all the instances.

Example Command

Simply run
python3 ./runBatchPuppeteerLighthouse.py
When the program is done, the output files
, and
will be put in a directory
Here are example outputs, showing a Puppeteer screenshot, a Lighthouse report, and the instance location map:
Load Test Output
Load Test Output
Load Test Output