Golang and Docker Multi-Stage Build MK2

In my previous post I used Docker multi stage technique to build a Docker container image which only has the golang executable in a tiny Alpine Linux base image. I’ll go further to use the scratch base image which has basically nothing.

Here’s the Dockerfile I tested on my own project, I’ve also added comments to help understand important lines:

FROM golang:1.13.1 AS builder

# ENVs to ensure golang will need no external libraries
ENV CGO_ENABLED=0 GOOS=linux
WORKDIR /app
COPY . .
# build switches to ensure golang will need no external libraries
RUN go build -a -installsuffix cgo -o myapp main.go && \
# create non-privileged user and group to run the app
  addgroup --system --gid 2000 golang && \
  adduser --system --gid 2000 --uid 2000 golang

FROM scratch
# some sample ENVs for the app
ENV API_KEY=xxx \
  API_EMAIL=xxx
WORKDIR /app
# copy the golang executable over
COPY --from=builder /app/myapp .
# scratch has no adduser command so just copy the files from builder
COPY --from=builder /etc/passwd /etc/passwd
COPY --from=builder /etc/group /etc/group
# use the CA cert from builder to enable HTTPS access
COPY --from=builder /etc/ssl/certs/ca-certificates.crt /etc/ssl/certs/
USER golang
# run the executable directly
ENTRYPOINT ["/app/myapp"]

The result image is only 7.7MB, only 1MB larger than the golang app itself. 🙂

Golang and Docker Multi-Stage Build

I have noticed a common pattern amonst some new utilities such as kubectl, kops and terraform: There’s only 1 single executable file to install, and by ‘install’ it can be put anywhere as long as it’s in $PATH. This was before I learned some Golang but it’s easy to find out that the reason behind this pattern is that they are all written in Go.

And in the containers’ realm, the new-ish multi-stage build steps of Docker released in 2017 are super beneficial to Golang containers. A TL;DR example looks like:

  1. use a 1GB Debian container with all Golang tools and build dependencies to build the Golang executable( FROM ... AS in the sample ).
  2. put the executable into a tiny run-time container such as Alpine Linux, resulting in a < 20MB container image(depending on the size of the app obviously) ( COPY --FROM in the sample )

A multi-stage ‘hello world’ Dockerfile looks like:

FROM golang:1.12.5-alpine3.9 as builder
ENV GO111MODULE=on
RUN apk update --no-cache && \
apk add git
WORKDIR /app
ADD ./ /app
RUN go build -o golang-test .

FROM alpine:3.9.4
WORKDIR /app
RUN addgroup -g 2000 golang && \
adduser -D -u 2000 -G golang golang
USER golang
COPY --from=builder /app/golang-test .
CMD ["/app/golang-test"]
EXPOSE 8000

Note: To be able to use the multi-stage feature, the Docker version has to be > 17.06.

🙂

Home VPN with OpenVPN

Here are step to run a simple OpenVPN service at home, so that I can access home network easily while not at home.

First, clone the git repo for OpenVPN docker container:

git clone https://github.com/kylemanna/docker-openvpn.git

I can use the pre-built docker image from docker hub but it has just been breached so I’d rather build it myself:

cd docker-openvpn && docker build -t openvpn .

Create a docker volume to persist data if the OpenVPN container to be rebuilt:

export $OVPN_DATA=ovpn_data
docker volume create --name $OVPN_DATA

Generate OpenVPN configurations, if there’s no DNS record for the server, use the public IP of the home broadband alternatively.

docker run -v $OVPN_DATA:/etc/openvpn --log-driver=none --rm openvpn ovpn_genconfig -u udp://VPN.SERVERNAME.COM

Build a new secret key which will be used to generate user keys. I’d advise to use a strong password which can be saved in a password manager or vault. This is needed everytime when I create a new user.

docker run -v $OVPN_DATA:/etc/openvpn --log-driver=none --rm -it openvpn ovpn_initpki

Then the OpenVPN server container can be run as a service:

docker run -v $OVPN_DATA:/etc/openvpn -d -p 1194:1194/udp --cap-add=NET_ADMIN openvpn

Generate the first user profile. The password for secret key will be needed. Then retrieve the OpenVPN configuration with the 2nd command.

docker run -v $OVPN_DATA:/etc/openvpn --log-driver=none --rm -it openvpn easyrsa build-client-full <username> nopass
docker run -v $OVPN_DATA:/etc/openvpn --log-driver=none --rm openvpn ovpn_getclient <username> > <username>.ovpn

This .ovpn file can be used to configure OpenVPN client softwares on laptops or phones.

At last, ensure UDP 1194 port is forwarded to the host of the docker container. This is usually done in the home broadband router.

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…

🙂