Run Google Lighthouse in Docker Container

Thanks to my Colleague Simon’s suggestion, I was introduced to Google Lighthouse, an opensource nodejs framework to use Google Chrome to audit a website’s performance.

I like Lighthouse because:

  • opensource
  • good portability
  • can run as CLI command or as a nodejs module

Here’s a sample Dockerfile to have a container ready to run Lighthouse with Google Chrome for Linux.

FROM debian:stretch

USER root
WORKDIR /root
ENV CHROME_VERSION="google-chrome-stable"

# system packages
RUN apt update -qqy && \
  apt install -qqy build-essential gnupg wget curl jq

# nodejs 10
RUN curl -sL https://deb.nodesource.com/setup_10.x | bash - && \
  apt install -qqy nodejs && \
  npm install -g lighthouse

# google-chrome
RUN wget -q -O - https://dl-ssl.google.com/linux/linux_signing_key.pub | apt-key add - && \
  echo "deb http://dl.google.com/linux/chrome/deb/ stable main" >> /etc/apt/sources.list.d/google-chrome.list && \
  apt update -qqy && \
  apt install -qqy ${CHROME_VERSION:-google-chrome-stable}

# python3 (optional for metric processing)
RUN apt install -qqy python3 python3-pip && \
  pip3 install influxdb

# lighthouse
RUN useradd -ms /bin/bash lighthouse
USER lighthouse
WORKDIR /home/lighthouse

Then lighthouse can be executed in the container to audit $url:

CHROME_PATH=$(which google-chrome) lighthouse $url --emulated-form-factor=none --output=json --chrome-flags="--headless --no-sandbox"

The result json will be sent to stdout, and it can be easily piped to other scripts for post processing, eg. parse json and extract metrics, etc…

🙂

Play a bit Kubernetes with Minikube

I’ve just played a bit Kubernetes on my Arch Linux laptop, with Minikube. It’s easier than I thought.

Since I’ve already installed VirtualBox from the start, I can use minikube right after I installed it with

curl -Lo minikube https://storage.googleapis.com/minikube/releases/latest/minikube-linux-amd64 && chmod +x minikube && sudo mv minikube /usr/local/bin/

The command I used to start minikube is

minikube start --cpus 4 --memory 4096 --insecure-registry "10.0.0.0/8"

It’s obvious that I wanted to allocate 4 CPUs and 4GB memory to the Kubernetes cluster. The –insecure-registry option is useful when I want to use a local Docker Registry without SSL.

Check if the cluster is ready with

minikube status

And launch the Kubernetes Dashboard with

minikube dashboard

After all these, it’s time to play with Kubernetes(kubectl command). However the local Kubernetes cluster doesn’t have DNS management like its cloud counterpart does. I wanted to have a load balancer too so I needed to get the IP and then tell kubectl to use the IP for the load balancer service:

minikube ip
192.168.99.104

Then in the yaml file for kubectl:

---
apiVersion: v1
kind: Service
metadata:
...
spec:
  externalIPs:
    - 192.168.99.104
...
  type: LoadBalancer

For now I found this necessary otherwise the service stuck at pending state.

🙂