Docker has sharply in the past years. It has been one of the tools that have as software engineers and DevOps Engineers. From Docker v 17.05 was introduced which helped abandon the older with use of stages and . This post discussed how you can exploit docker multi-stage build to build optimal images suited for dev/test and production with a NodeJs example application. risen in popularity changed the way we work multi-stage build builder pattern target Prerequisites You are aware of docker and know the basic docker commands like build, exec You know about docker-compose (not a necessity) Docker multi-stage builds intro Docker multi-stage build lets us build docker images in stages with multiple FROM statements. Files can be copied from one stage to another. A very good example would be how a Golang 1.13 official image (123 MB even with Alpine) can be just as big as the go executable of your application. As Golang is compiled and gives out an executable binary, the first stage can be compiling it and the second stage can be an alpine image (5 MB) just to run that executable. So, if you go app binary is 10 MB your image can be 15 Mb (10 MB binary + 5 MB alpine) rather than the heavy 294 MB official go image or 123 MB alpine go image. You can have a look at an too. 294 MB example Another great example can be a frontend javascript application, you could use an app with node, webpack and all needed npm dev dependencies to build the application. In the next stage, it can be served with a minimal nginx apline image which will be of much less size. Below is the official information about docker multi-stage builds: With multi-stage builds, you use multiple FROM statements in your Dockerfile. Each FROM instruction can use a different base, and each of them begins a new stage of the build. You can selectively copy artifacts from one stage to another, leaving behind everything you don’t want in the final image. Unfortunately, all the language don’t compile to an executable binary as golang does, still, you can leverage multi-stage builds to craft docker images that serve the purpose better. We look into how to do this below with an open-source node js application example. Issues before multi-stage build We are going to see an example Node Js app which is a currency converter API built with Express. Currently, the problems with the Dockerfile and build are as follows: Nodemon is installed on productionCurrent docker image does not have dev dependencies (runs )The image size can be made smaller (even though its using alpine) npm install --production Following are the current Dockerfile and docker-compose.yml for local development: Dockerfile FROM node:12-alpine

WORKDIR /src
COPY package.json package-lock.json /src/
RUN npm install --production

COPY . /src

EXPOSE 8080

RUN npm config unsafe-perm RUN npm install -g nodemon

CMD [ , ] set true "node" "index.js" As we can see nodemon is installed even on production which is unnecessary on production. Another issue is there are no dev dependencies so tests can’t be run inside docker. Docker Compose file web:
  build: .
  volumes:
   - .:/src : npm start
  ports:
    - environment:
    NODE_ENV: dev
    VIRTUAL_HOST: VIRTUAL_PORT: 8080 command "8080:8080" 'currency.test' Don’t be concerned about the and that is for . VIRTUAL_HOST VIRTUAL_PORT nginx proxy Current image size Let’s look at how big is this image we got from running . docker build . -t currency-api-original So currently it is 165 MB, hopefully, we can decrease its size too in this process. Solution with multi-stage build Now as we want to have dev dependencies and nodemon on dev builds and only production npm dependencies on production build, the docker related files have been modified as follows: Dockerfile with multi-stage build FROM node:12-alpine as base

WORKDIR /src
COPY package.json package-lock.json /src/
COPY . /src
EXPOSE 8080

FROM base as production

ENV NODE_ENV=production
RUN npm install --production

CMD [ , ]

FROM base as dev

ENV NODE_ENV=development
RUN npm config unsafe-perm && npm install -g nodemon
RUN npm install
CMD [ , ] "node" "index.js" set true "npm" "start" Let’s analyze what changed here and why? Following are the highlights: We start with a base image that has node, then copy needed files to the image like 1-5 For production we set the to production and install non-dev dependencies, also notice that we run node (not nodemon) NODE_ENV Later the last 6 lines of the Dockefile, we create the image from the base and set to development, then we install nodemon as we want to watch the files on dev NODE_ENV On dev image build we install all npm dependencies including dev ones so that we can run tests The builds are more streamlined and we have optimized our docker images to be more environment-specific. We solved the above-mentioned issues and don’t have nodemon and dev dependencies on production and we can run our tests on dev/test. That’s a win! Docker-compose file after multi-stage build version: services:
  web:
    build:
      context: ./
      target: dev
    volumes:
    - .:/src : npm start
    ports:
      - environment:
      NODE_ENV: dev
      VIRTUAL_HOST: VIRTUAL_PORT: 8080 '3.5' command "8080:8080" 'currency.test' The main change for the docker-compose file is the target:dev in the build parameters. All the changes made can be viewed in this too. Let’s look at how big is the image now: pull request We ran the following commands to build the dev and the production images: docker build . -t currency-api-dev –target=dev docker build . -t currency-api-prod –target=production We have shaved off ~25 MB from the older image for a production build. It happened because we removed nodemon and some dev dependencies for production. Even for the dev build it is ~21 MB smaller. Conclusion / tl;dr The main point here is to build docker images apt for the environment and multi-stage builds are an answer to this problem. You can use the same concept to build images for PHP with composer. For example, the dev build can have xdebug for debugging and production build can have enabled by default. opcache Anytime you need different things for different environments, opt for docker multi-stage builds and avoid having 3 different dockerfiles.

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