Starting from Docker 17.05+, you can create a single
Dockerfile that can build multiple helper images with compilers, tools, and tests and use files from above images to produce the final Docker image.
The “core principle” of Dockerfile
Docker can build images by reading the instructions from a
Dockerfile is a text file that contains a list of all the commands needed to build a new Docker image. The syntax of
Dockerfile is pretty simple and the Docker team tries to keep it intact between Docker engine releases.
The core principle is very simple:
1 Dockerfile -> 1 Docker Image.
This principle works just fine for basic use cases, where you just need to demonstrate Docker capabilities or put some “static” content into a Docker image.
Once you advance with Docker and would like to create secure and lean Docker images, singe
Dockerfile is not enough.
People who insist on following the above principle find themselves with slow Docker builds, huge Docker images (several GB size images), slow deployment time and lots of CVE violations embedded into these images.
The Docker Build Container pattern
The basic idea behind Build Container pattern is simple:
Create additional Docker images with required tools (compilers, linters, testing tools) and use these images to produce lean, secure and production ready Docker image.
An example of the Build Container pattern for typical Node.js application:
FROMa Node base image (for example
- Install all node modules from
- Copy application code
- Run compilers, code coverage, linters, code analysis and testing tools
- Create the production Docker image; derive
FROMsame or other Node base image
- install node modules required for runtime (
npm install --only=production)
PORTand define default
CMD(command to run your application)
- Push the production image to some Docker registry
This flow assumes that you are using two or more separate
Dockerfiles and a shell script or flow tool to orchestrate all steps above.
I use a fork of Let’s Chat node.js application.
Builder Docker image with eslint, mocha and gulp
FROM alpine:3.5 # install node RUN apk add --no-cache nodejs # set working directory WORKDIR /root/chat # copy project file COPY package.json . # install node packages RUN npm set progress=false && \ npm config set depth 0 && \ npm install # copy app files COPY . . # run linter, setup and tests CMD npm run lint && npm run setup && npm run test
Production Docker image with ‘production’ node modules only
FROM alpine:3.5 # install node RUN apk add --no-cache nodejs tini # set working directory WORKDIR /root/chat # copy project file COPY package.json . # install node packages RUN npm set progress=false && \ npm config set depth 0 && \ npm install --only=production && \ npm cache clean # copy app files COPY . . # Set tini as entrypoint ENTRYPOINT ["/sbin/tini", "--"] # application server port EXPOSE 5000 # default run command CMD npm run start
What is Docker multi-stage build?
Docker 17.0.5 extends
Dockerfile syntax to support new multi-stage build, by extending two commands:
The multi-stage build allows using multiple
FROM commands in the same Dockerfile. The last
FROM command produces the final Docker image, all other images are intermediate images (no final Docker image is produced, but all layers are cached).
FROM syntax also supports
AS keyword. Use
AS keyword to give the current image a logical name and reference to it later by this name.
To copy files from intermediate images use
COPY --from=<image_AS_name|image_number>, where number starts from
0 (but better to use logical name through
Creating a multi-stage Dockerfile for Node.js application
Dockerfile below makes the Build Container pattern obsolete, allowing to achieve the same result with the single file.
# # ---- Base Node ---- FROM alpine:3.5 AS base # install node RUN apk add --no-cache nodejs-npm tini # set working directory WORKDIR /root/chat # Set tini as entrypoint ENTRYPOINT ["/sbin/tini", "--"] # copy project file COPY package.json . # # ---- Dependencies ---- FROM base AS dependencies # install node packages RUN npm set progress=false && npm config set depth 0 RUN npm install --only=production # copy production node_modules aside RUN cp -R node_modules prod_node_modules # install ALL node_modules, including 'devDependencies' RUN npm install # # ---- Test ---- # run linters, setup and tests FROM dependencies AS test COPY . . RUN npm run lint && npm run setup && npm run test # # ---- Release ---- FROM base AS release # copy production node_modules COPY --from=dependencies /root/chat/prod_node_modules ./node_modules # copy app sources COPY . . # expose port and define CMD EXPOSE 5000 CMD npm run start
Dockerfile creates 3 intermediate Docker images and single release Docker image (the final
- First image
FROM alpine:3.5 AS bas- is a base Node image with:
tini(init app) and
- Second image
FROM base AS dependencies- contains all node modules from
devDependencieswith additional copy of
dependenciesrequired for final image only
- Third image
FROM dependencies AS test- runs linters, setup and tests (with
mocha); if this run command fail not final image is produced
- The final image
FROM base AS release- is a base Node image with application code and all node modules from
Try Docker multi-stage build today
In order to try Docker multi-stage build, you need to get Docker 17.0.5, which is going to be released in May and currently available on the beta channel.
So, you have two options:
- Use beta channel to get Docker 17.0.5
- Run dind container (docker-in-docker)
Running Docker-in-Docker 17.0.5 (beta)
Running Docker 17.0.5 (beta) in docker container (
--privileged is required):
$ docker run -d --rm --privileged -p 23751:2375 --name dind docker:17.05.0-ce-dind --storage-driver overlay2
Try mult-stage build. Add
--host=:23751 to every Docker command, or set
DOCKER_HOST environment variable.
$ # using --host $ docker --host=:23751 build -t local/chat:multi-stage . $ # OR: setting DOCKER_HOST $ export DOCKER_HOST=localhost:23751 $ docker build -t local/chat:multi-stage .
With Docker multi-stage build feature, it’s possible to implement an advanced Docker image build pipeline using a single
Dockerfile. Kudos to Docker team!
Hope, you find this post useful. I look forward to your comments and any questions you have.
_This is a working draft version. The final post version is published at Codefresh Blog on April 24, 2017._