The Jenkins Continuous Integration and Delivery server.
This is a fully functional Jenkins server, based on the Long Term Support release http://jenkins.io/.
For weekly releases check out jenkinsci/jenkins
How to use this image
docker run -p 8080:8080 -p 50000:50000 jenkins
This will store the workspace in /var/jenkins_home. All Jenkins data lives in there - including plugins and configuration. You will probably want to make that a persistent volume (recommended):
docker run -p 8080:8080 -p 50000:50000 -v /your/home:/var/jenkins_home jenkins
This will store the jenkins data in /your/home on the host. Ensure that /your/home is accessible by the jenkins user in container (jenkins user - uid 1000) or use -u some_other_user parameter with docker run.
You can also use a volume container:
docker run --name myjenkins -p 8080:8080 -p 50000:50000 -v /var/jenkins_home jenkins
Then myjenkins container has the volume (please do read about docker volume handling to find out more).
Backing up data
If you bind mount in a volume - you can simply back up that directory (which is jenkins_home) at any time.
This is highly recommended. Treat the jenkins_home directory as you would a database - in Docker you would generally put a database on a volume.
If your volume is inside a container - you can use docker cp $ID:/var/jenkins_home command to extract the data, or other options to find where the volume data is. Note that some symlinks on some OSes may be converted to copies (this can confuse jenkins with lastStableBuild links etc)
For more info check Docker docs section on Managing data in containers
Setting the number of executors
You can specify and set the number of executors of your Jenkins master instance using a groovy script. By default its set to 2 executors, but you can extend the image and change it to your desired number of executors :
COPY executors.groovy /usr/share/jenkins/ref/init.groovy.d/executors.groovy
Attaching build executors
You can run builds on the master (out of the box) but if you want to attach build slave servers: make sure you map the port: -p 50000:50000 - which will be used when you connect a slave agent.
Passing JVM parameters
You might need to customize the JVM running Jenkins, typically to pass system properties or tweak heap memory settings. Use JAVA_OPTS environment variable for this purpose :
docker run --name myjenkins -p 8080:8080 -p 50000:50000 --env JAVA_OPTS=-Dhudson.footerURL=http://mycompany.com jenkins
Jenkins logging can be configured through a properties file and java.util.logging.config.file Java property. For example:
cat > data/log.properties <<EOF
docker run --name myjenkins -p 8080:8080 -p 50000:50000 --env JAVA_OPTS="-Djava.util.logging.config.file=/var/jenkins_home/log.properties" -v
Passing Jenkins launcher parameters
Argument you pass to docker running the jenkins image are passed to jenkins launcher, so you can run for sample :
$ docker run jenkins --version
This will dump Jenkins version, just like when you run jenkins as an executable war.
You also can define jenkins arguments as JENKINS_OPTS. This is usefull to define a set of arguments to pass to jenkins launcher as you define a derived jenkins image based on the official one with some customized settings. The following sample Dockerfile uses this option to force use of HTTPS with a certificate included in the image
COPY https.pem /var/lib/jenkins/cert
COPY https.key /var/lib/jenkins/pk
ENV JENKINS_OPTS --httpPort=-1 --httpsPort=8083 --httpsCertificate=/var/lib/jenkins/cert --httpsPrivateKey=/var/lib/jenkins/pk
You can also change the default slave agent port for jenkins by defining JENKINS_SLAVE_AGENT_PORT in a sample Dockerfile.
ENV JENKINS_SLAVE_AGENT_PORT 50001
or as a parameter to docker,
$ docker run --name myjenkins -p 8080:8080 -p 50001:50001 --env JENKINS_SLAVE_AGENT_PORT=50001 jenkins
Installing more tools
You can run your container as root - and install via apt-get, install as part of build steps via jenkins tool installers, or you can create your own Dockerfile to customise, for example:
if we want to install via apt
RUN apt-get update && apt-get install -y ruby make more-thing-here
USER jenkins # drop back to the regular jenkins user - good practice
In such a derived image, you can customize your jenkins instance with hook scripts or additional plugins. For this purpose, use /usr/share/jenkins/ref as a place to define the default JENKINS_HOME content you wish the target installation to look like :
COPY plugins.txt /usr/share/jenkins/ref/
COPY custom.groovy /usr/share/jenkins/ref/init.groovy.d/custom.groovy
RUN /usr/local/bin/plugins.sh /usr/share/jenkins/ref/plugins.txt
When jenkins container starts, it will check JENKINS_HOME has this reference content, and copy them there if required. It will not override such files, so if you upgraded some plugins from UI they won't be reverted on next start.
Also see JENKINS-24986
For your convenience, you also can use a plain text file to define plugins to be installed (using core-support plugin format). All plugins need to be listed as there is no transitive dependency resolution.
And in derived Dockerfile just invoke the utility plugin.sh script
COPY plugins.txt /usr/share/jenkins/plugins.txt
RUN /usr/local/bin/plugins.sh /usr/share/jenkins/plugins.txt
All the data needed is in the /var/jenkins_home directory - so depending on how you manage that - depends on how you upgrade. Generally - you can copy it out - and then "docker pull" the image again - and you will have the latest LTS - you can then start up with -v pointing to that data (/var/jenkins_home) and everything will be as you left it.
As always - please ensure that you know how to drive docker - especially volume handling!
The jenkins images come in many flavors, each designed for a specific use case.
This is the defacto image. If you are unsure about what your needs are, you probably want to use this one. It is designed to be used both as a throw away container (mount your source code and start the container to start your app), as well as the base to build other images off of.
This image is based on the popular Alpine Linux project, available in the alpine official image. Alpine Linux is much smaller than most distribution base images (~5MB), and thus leads to much slimmer images in general.
This variant is highly recommended when final image size being as small as possible is desired. The main caveat to note is that it does use musl libc instead of glibc and friends, so certain software might run into issues depending on the depth of their libc requirements. However, most software doesn't have an issue with this, so this variant is usually a very safe choice. See this Hacker News comment thread for more discussion of the issues that might arise and some pro/con comparisons of using Alpine-based images.
To minimize image size, it's uncommon for additional related tools (such as git or bash) to be included in Alpine-based images. Using this image as a base, add the things you need in your own Dockerfile (see the alpine image description for examples of how to install packages if you are unfamiliar).
Supported Docker versions
This image is officially supported on Docker version 1.11.1.
Support for older versions (down to 1.6) is provided on a best-effort basis.
Please see the Docker installation documentation for details on how to upgrade your Docker daemon.
Documentation for this image is stored in the jenkins/ directory of the docker-library/docs GitHub repo. Be sure to familiarize yourself with the repository's README.md file before attempting a pull request.
If you have any problems with or questions about this image, please contact us through a GitHub issue. If the issue is related to a CVE, please check for a cve-tracker issue on the official-images repository first.
You can also reach many of the official image maintainers via the #docker-library IRC channel on Freenode.
You are invited to contribute new features, fixes, or updates, large or small; we are always thrilled to receive pull requests, and do our best to process them as fast as we can.
Before you start to code, we recommend discussing your plans through a GitHub issue, especially for more ambitious contributions. This gives other contributors a chance to point you in the right direction, give you feedback on your design, and help you find out if someone else is working on the same thing.