Chapter 4. Creating images

The following guidelines apply when creating a container image in general, and are independent of whether the images are used on Red Hat OpenShift Service on AWS.

Reuse images

Wherever possible, base your image on an appropriate upstream image using the FROM statement. This ensures your image can easily pick up security fixes from an upstream image when it is updated, rather than you having to update your dependencies directly.

In addition, use tags in the FROM instruction, for example, rhel:rhel7, to make it clear to users exactly which version of an image your image is based on. Using a tag other than latest ensures your image is not subjected to breaking changes that might go into the latest version of an upstream image.

Maintain compatibility within tags

When tagging your own images, try to maintain backwards compatibility within a tag. For example, if you provide an image named image and it currently includes version 1.0, you might provide a tag of image:v1. When you update the image, as long as it continues to be compatible with the original image, you can continue to tag the new image image:v1, and downstream consumers of this tag are able to get updates without being broken.

If you later release an incompatible update, then switch to a new tag, for example image:v2. This allows downstream consumers to move up to the new version at will, but not be inadvertently broken by the new incompatible image. Any downstream consumer using image:latest takes on the risk of any incompatible changes being introduced.

Avoid multiple processes

Do not start multiple services, such as a database and SSHD, inside one container. This is not necessary because containers are lightweight and can be easily linked together for orchestrating multiple processes. Red Hat OpenShift Service on AWS allows you to easily colocate and co-manage related images by grouping them into a single pod.

This colocation ensures the containers share a network namespace and storage for communication. Updates are also less disruptive as each image can be updated less frequently and independently. Signal handling flows are also clearer with a single process as you do not have to manage routing signals to spawned processes.

Use exec in wrapper scripts

Many images use wrapper scripts to do some setup before starting a process for the software being run. If your image uses such a script, that script uses exec so that the script’s process is replaced by your software. If you do not use exec, then signals sent by your container runtime go to your wrapper script instead of your software’s process. This is not what you want.

If you have a wrapper script that starts a process for some server. You start your container, for example, using podman run -i, which runs the wrapper script, which in turn starts your process. If you want to close your container with CTRL+C. If your wrapper script used exec to start the server process, podman sends SIGINT to the server process, and everything works as you expect. If you did not use exec in your wrapper script, podman sends SIGINT to the process for the wrapper script and your process keeps running like nothing happened.

Also note that your process runs as PID 1 when running in a container. This means that if your main process terminates, the entire container is stopped, canceling any child processes you launched from your PID 1 process.

Clean temporary files

Remove all temporary files you create during the build process. This also includes any files added with the ADD command. For example, run the yum clean command after performing yum install operations.

You can prevent the yum cache from ending up in an image layer by creating your RUN statement as follows:

RUN yum -y install mypackage && yum -y install myotherpackage && yum clean all -y

Note that if you instead write:

RUN yum -y install mypackage
RUN yum -y install myotherpackage && yum clean all -y

Then the first yum invocation leaves extra files in that layer, and these files cannot be removed when the yum clean operation is run later. The extra files are not visible in the final image, but they are present in the underlying layers.

The current container build process does not allow a command run in a later layer to shrink the space used by the image when something was removed in an earlier layer. However, this may change in the future. This means that if you perform an rm command in a later layer, although the files are hidden it does not reduce the overall size of the image to be downloaded. Therefore, as with the yum clean example, it is best to remove files in the same command that created them, where possible, so they do not end up written to a layer.

In addition, performing multiple commands in a single RUN statement reduces the number of layers in your image, which improves download and extraction time.

Place instructions in the proper order

The container builder reads the Dockerfile and runs the instructions from top to bottom. Every instruction that is successfully executed creates a layer which can be reused the next time this or another image is built. It is very important to place instructions that rarely change at the top of your Dockerfile. Doing so ensures the next builds of the same image are very fast because the cache is not invalidated by upper layer changes.

For example, if you are working on a Dockerfile that contains an ADD command to install a file you are iterating on, and a RUN command to yum install a package, it is best to put the ADD command last:

FROM foo
RUN yum -y install mypackage && yum clean all -y
ADD myfile /test/myfile

This way each time you edit myfile and rerun podman build or docker build, the system reuses the cached layer for the yum command and only generates the new layer for the ADD operation.

If instead you wrote the Dockerfile as:

FROM foo
ADD myfile /test/myfile
RUN yum -y install mypackage && yum clean all -y

Then each time you changed myfile and reran podman build or docker build, the ADD operation would invalidate the RUN layer cache, so the yum operation must be rerun as well.

Mark important ports

The EXPOSE instruction makes a port in the container available to the host system and other containers. While it is possible to specify that a port should be exposed with a podman run invocation, using the EXPOSE instruction in a Dockerfile makes it easier for both humans and software to use your image by explicitly declaring the ports your software needs to run:

Set environment variables

It is good practice to set environment variables with the ENV instruction. One example is to set the version of your project. This makes it easy for people to find the version without looking at the Dockerfile. Another example is advertising a path on the system that could be used by another process, such as JAVA_HOME.

Avoid default passwords

Avoid setting default passwords. Many people extend the image and forget to remove or change the default password. This can lead to security issues if a user in production is assigned a well-known password. Passwords are configurable using an environment variable instead.

If you do choose to set a default password, ensure that an appropriate warning message is displayed when the container is started. The message should inform the user of the value of the default password and explain how to change it, such as what environment variable to set.

Avoid sshd

It is best to avoid running sshd in your image. You can use the podman exec or docker exec command to access containers that are running on the local host. Alternatively, you can use the oc exec command or the oc rsh command to access containers that are running on the Red Hat OpenShift Service on AWS cluster. Installing and running sshd in your image opens up additional vectors for attack and requirements for security patching.

Use volumes for persistent data

Images use a volume for persistent data. This way Red Hat OpenShift Service on AWS mounts the network storage to the node running the container, and if the container moves to a new node the storage is reattached to that node. By using the volume for all persistent storage needs, the content is preserved even if the container is restarted or moved. If your image writes data to arbitrary locations within the container, that content could not be preserved.

All data that needs to be preserved even after the container is destroyed must be written to a volume. Container engines support a readonly flag for containers, which can be used to strictly enforce good practices about not writing data to ephemeral storage in a container. Designing your image around that capability now makes it easier to take advantage of it later.

Explicitly defining volumes in your Dockerfile makes it easy for consumers of the image to understand what volumes they must define when running your image.

See the Kubernetes documentation for more information on how volumes are used in Red Hat OpenShift Service on AWS.

The following are guidelines that apply when creating container images specifically for use on Red Hat OpenShift Service on AWS.

RUN chgrp -R 0 /some/directory && \
    chmod -R g=u /some/directory

You can use the LABEL instruction in a Dockerfile to define image metadata. Labels are similar to environment variables in that they are key value pairs attached to an image or a container. Labels are different from environment variable in that they are not visible to the running application and they can also be used for fast look-up of images and containers.

Docker documentation for more information on the LABEL instruction.

The label names are typically namespaced. The namespace is set accordingly to reflect the project that is going to pick up the labels and use them. For Red Hat OpenShift Service on AWS the namespace is set to io.openshift and for Kubernetes the namespace is io.k8s.

See the Docker custom metadata documentation for details about the format.

LABEL io.openshift.tags   mongodb,mongodb24,nosql

LABEL io.openshift.wants   mongodb,redis

LABEL io.k8s.description The MySQL 5.5 Server with master-slave replication support

LABEL io.openshift.non-scalable     true

LABEL io.openshift.min-memory 16Gi
LABEL io.openshift.min-cpu     4

The build process consists of the following three fundamental elements, which are combined into a final container image:

S2I generates a Dockerfile with the builder image as the first FROM instruction. The Dockerfile generated by S2I is then passed to Buildah.

You can write source-to-image (S2I) scripts in any programming language, as long as the scripts are executable inside the builder image. S2I supports multiple options providing assemble/run/save-artifacts scripts. All of these locations are checked on each build in the following order:

Both the io.openshift.s2i.scripts-url label specified in the image and the script specified in a build configuration can take one of the following forms:

Example S2I scripts

The following example S2I scripts are written in Bash. Each example assumes its tar contents are unpacked into the /tmp/s2i directory.

#!/bin/bash

# restore build artifacts
if [ "$(ls /tmp/s2i/artifacts/ 2>/dev/null)" ]; then
    mv /tmp/s2i/artifacts/* $HOME/.
fi

# move the application source
mv /tmp/s2i/src $HOME/src

# build application artifacts
pushd ${HOME}
make all

# install the artifacts
make install
popd

#!/bin/bash

# run the application
/opt/application/run.sh

#!/bin/bash

pushd ${HOME}
if [ -d deps ]; then
    # all deps contents to tar stream
    tar cf - deps
fi
popd

#!/bin/bash

# inform the user how to use the image
cat <<EOF
This is a S2I sample builder image, to use it, install
https://github.com/openshift/source-to-image
EOF

The standard location for the test script is test/run. This script is invoked by the Red Hat OpenShift Service on AWS S2I image builder and it could be a simple Bash script or a static Go binary.

The test/run script performs the S2I build, so you must have the S2I binary available in your $PATH. If required, follow the installation instructions in the S2I README.

S2I combines the application source code and builder image, so to test it you need a sample application source to verify that the source successfully transforms into a runnable container image. The sample application should be simple, but it should exercise the crucial steps of assemble and run scripts.

The S2I tooling comes with powerful generation tools to speed up the process of creating a new S2I image. The s2i create command produces all the necessary S2I scripts and testing tools along with the Makefile:

$ s2i create <image_name> <destination_directory>

The generated test/run script must be adjusted to be useful, but it provides a good starting point to begin developing.

The easiest way to run the S2I image tests locally is to use the generated Makefile.

If you did not use the s2i create command, you can copy the following Makefile template and replace the IMAGE_NAME parameter with your image name.

IMAGE_NAME = openshift/ruby-20-centos7
CONTAINER_ENGINE := $(shell command -v podman 2> /dev/null | echo docker)

build:
	${CONTAINER_ENGINE} build -t $(IMAGE_NAME) .

.PHONY: test
test:
	${CONTAINER_ENGINE} build -t $(IMAGE_NAME)-candidate .
	IMAGE_NAME=$(IMAGE_NAME)-candidate test/run

The test script assumes you have already built the image you want to test. If required, first build the S2I image. Run one of the following commands:

The following steps describe the default workflow to test S2I image builders:

Running these steps is generally enough to tell if the builder image is working as expected.

Once you have a Dockerfile and the other artifacts that make up your new S2I builder image, you can put them in a git repository and use Red Hat OpenShift Service on AWS to build and push the image. Define a Docker build that points to your repository.

If your Red Hat OpenShift Service on AWS instance is hosted on a public IP address, the build can be triggered each time you push into your S2I builder image GitHub repository.

You can also use the ImageChangeTrigger to trigger a rebuild of your applications that are based on the S2I builder image you updated.