Best practices for writing DockerfilesEstimated reading time: 26 minutes
This document covers recommended best practices and methods for building efficient images.
Docker builds images automatically by reading the instructions from a
Dockerfile -- a text file that contains all commands, in order, needed to
build a given image. A
Dockerfile adheres to a specific format and set of
instructions which you can find at Dockerfile reference.
A Docker image consists of read-only layers each of which represents a
Dockerfile instruction. The layers are stacked and each one is a delta of the
changes from the previous layer. Consider this
FROM ubuntu:15.04 COPY . /app RUN make /app CMD python /app/app.py
Each instruction creates one layer:
FROMcreates a layer from the
COPYadds files from your Docker client’s current directory.
RUNbuilds your application with
CMDspecifies what command to run within the container.
When you run an image and generate a container, you add a new writable layer (the “container layer”) on top of the underlying layers. All changes made to the running container, such as writing new files, modifying existing files, and deleting files, are written to this thin writable container layer.
For more on image layers (and how Docker builds and stores images), see About storage drivers.
General guidelines and recommendations
Create ephemeral containers
The image defined by your
Dockerfile should generate containers that are as
ephemeral as possible. By “ephemeral,” we mean that the container can be stopped
and destroyed, then rebuilt and replaced with an absolute minimum set up and
Refer to Processes under The Twelve-factor App methodology to get a feel for the motivations of running containers in such a stateless fashion.
Understand build context
When you issue a
docker build command, the current working directory is called
the build context. By default, the Dockerfile is assumed to be located here,
but you can specify a different location with the file flag (
of where the
Dockerfile actually lives, all recursive contents of files and
directories in the current directory are sent to the Docker daemon as the build
Build context example
Create a directory for the build context and
cdinto it. Write “hello” into a text file named
helloand create a Dockerfile that runs
caton it. Build the image from within the build context (
mkdir myproject && cd myproject echo "hello" > hello echo -e "FROM busybox\nCOPY /hello /\nRUN cat /hello" > Dockerfile docker build -t helloapp:v1 .
hellointo separate directories and build a second version of the image (without relying on cache from the last build). Use
-fto point to the Dockerfile and specify the directory of the build context:
mkdir -p dockerfiles context mv Dockerfile dockerfiles && mv hello context docker build --no-cache -t helloapp:v2 -f dockerfiles/Dockerfile context
Inadvertently including files that are not necessary for building an image
results in a larger build context and larger image size. This can increase the
time to build the image, time to pull and push it, and the container runtime
size. To see how big your build context is, look for a message like this when
Sending build context to Docker daemon 187.8MB
Pipe Dockerfile through
Docker 17.05 added the ability to build images by piping
stdin with a local or remote build-context. In earlier versions, building an
image with a
stdin did not send the build-context.
Docker 17.04 and lower
docker build -t foo -<<EOF FROM busybox RUN echo "hello world" EOF
Docker 17.05 and higher (local build-context)
docker build -t foo . -f-<<EOF FROM busybox RUN echo "hello world" COPY . /my-copied-files EOF
Docker 17.05 and higher (remote build-context)
docker build -t foo https://github.com/thajeztah/pgadmin4-docker.git -f-<<EOF FROM busybox COPY LICENSE config_local.py /usr/local/lib/python2.7/site-packages/pgadmin4/ EOF
Exclude with .dockerignore
To exclude files not relevant to the build (without restructuring your source
repository) use a
.dockerignore file. This file supports exclusion patterns
.gitignore files. For information on creating one, see the
Use multi-stage builds
Because an image is built during the final stage of the build process, you can minimize image layers by leveraging build cache.
For example, if your build contains several layers, you can order them from the less frequently changed (to ensure the build cache is reusable) to the more frequently changed:
Install tools you need to build your application
Install or update library dependencies
Generate your application
A Dockerfile for a Go application could look like:
FROM golang:1.9.2-alpine3.6 AS build # Install tools required for project # Run `docker build --no-cache .` to update dependencies RUN apk add --no-cache git RUN go get github.com/golang/dep/cmd/dep # List project dependencies with Gopkg.toml and Gopkg.lock # These layers are only re-built when Gopkg files are updated COPY Gopkg.lock Gopkg.toml /go/src/project/ WORKDIR /go/src/project/ # Install library dependencies RUN dep ensure -vendor-only # Copy the entire project and build it # This layer is rebuilt when a file changes in the project directory COPY . /go/src/project/ RUN go build -o /bin/project # This results in a single layer image FROM scratch COPY --from=build /bin/project /bin/project ENTRYPOINT ["/bin/project"] CMD ["--help"]
Don’t install unnecessary packages
To reduce complexity, dependencies, file sizes, and build times, avoid installing extra or unnecessary packages just because they might be “nice to have.” For example, you don’t need to include a text editor in a database image.
Each container should have only one concern. Decoupling applications into multiple containers makes it easier to scale horizontally and reuse containers. For instance, a web application stack might consist of three separate containers, each with its own unique image, to manage the web application, database, and an in-memory cache in a decoupled manner.
Limiting each container to one process is a good rule of thumb, but it is not a hard and fast rule. For example, not only can containers be spawned with an init process, some programs might spawn additional processes of their own accord. For instance, Celery can spawn multiple worker processes, and Apache can create one process per request.
Use your best judgment to keep containers as clean and modular as possible. If containers depend on each other, you can use Docker container networks to ensure that these containers can communicate.
Minimize the number of layers
In older versions of Docker, it was important that you minimized the number of layers in your images to ensure they were performant. The following features were added to reduce this limitation:
In Docker 1.10 and higher, only the instructions
ADDcreate layers. Other instructions create temporary intermediate images, and do not directly increase the size of the build.
In Docker 17.05 and higher, you can do multi-stage builds and only copy the artifacts you need into the final image. This allows you to include tools and debug information in your intermediate build stages without increasing the size of the final image.
Sort multi-line arguments
Whenever possible, ease later changes by sorting multi-line arguments
alphanumerically. This helps to avoid duplication of packages and make the
list much easier to update. This also makes PRs a lot easier to read and
review. Adding a space before a backslash (
\) helps as well.
Here’s an example from the
RUN apt-get update && apt-get install -y \ bzr \ cvs \ git \ mercurial \ subversion
Leverage build cache
When building an image, Docker steps through the instructions in your
Dockerfile, executing each in the order specified. As each instruction is
examined, Docker looks for an existing image in its cache that it can reuse,
rather than creating a new (duplicate) image.
If you do not want to use the cache at all, you can use the
option on the
docker build command. However, if you do let Docker use its
cache, it is important to understand when it can, and cannot, find a matching
image. The basic rules that Docker follows are outlined below:
Starting with a parent image that is already in the cache, the next instruction is compared against all child images derived from that base image to see if one of them was built using the exact same instruction. If not, the cache is invalidated.
In most cases, simply comparing the instruction in the
Dockerfilewith one of the child images is sufficient. However, certain instructions require more examination and explanation.
COPYinstructions, the contents of the file(s) in the image are examined and a checksum is calculated for each file. The last-modified and last-accessed times of the file(s) are not considered in these checksums. During the cache lookup, the checksum is compared against the checksum in the existing images. If anything has changed in the file(s), such as the contents and metadata, then the cache is invalidated.
Aside from the
COPYcommands, cache checking does not look at the files in the container to determine a cache match. For example, when processing a
RUN apt-get -y updatecommand the files updated in the container are not examined to determine if a cache hit exists. In that case just the command string itself is used to find a match.
Once the cache is invalidated, all subsequent
Dockerfile commands generate new
images and the cache is not used.
These recommendations are designed to help you create an efficient and
Whenever possible, use current official repositories as the basis for your images. We recommend the Alpine image as it is tightly controlled and small in size (currently under 5 MB), while still being a full Linux distribution.
You can add labels to your image to help organize images by project, record
licensing information, to aid in automation, or for other reasons. For each
label, add a line beginning with
LABEL and with one or more key-value pairs.
The following examples show the different acceptable formats. Explanatory comments are included inline.
Strings with spaces must be quoted or the spaces must be escaped. Inner quote characters (
"), must also be escaped.
# Set one or more individual labels LABEL com.example.version="0.0.1-beta" LABEL vendor1="ACME Incorporated" LABEL vendor2=ZENITH\ Incorporated LABEL com.example.release-date="2015-02-12" LABEL com.example.version.is-production=""
An image can have more than one label. Prior to Docker 1.10, it was recommended
to combine all labels into a single
LABEL instruction, to prevent extra layers
from being created. This is no longer necessary, but combining labels is still
# Set multiple labels on one line LABEL com.example.version="0.0.1-beta" com.example.release-date="2015-02-12"
The above can also be written as:
# Set multiple labels at once, using line-continuation characters to break long lines LABEL vendor=ACME\ Incorporated \ com.example.is-beta= \ com.example.is-production="" \ com.example.version="0.0.1-beta" \ com.example.release-date="2015-02-12"
See Understanding object labels for guidelines about acceptable label keys and values. For information about querying labels, refer to the items related to filtering in Managing labels on objects. See also LABEL in the Dockerfile reference.
Split long or complex
RUN statements on multiple lines separated with
backslashes to make your
Dockerfile more readable, understandable, and
Probably the most common use-case for
RUN is an application of
Because it installs packages, the
RUN apt-get command has several gotchas to
look out for.
RUN apt-get upgrade and
dist-upgrade, as many of the “essential”
packages from the parent images cannot upgrade inside an
unprivileged container. If a package
contained in the parent image is out-of-date, contact its maintainers. If you
know there is a particular package,
foo, that needs to be updated, use
apt-get install -y foo to update automatically.
RUN apt-get update with
apt-get install in the same
statement. For example:
RUN apt-get update && apt-get install -y \ package-bar \ package-baz \ package-foo
apt-get update alone in a
RUN statement causes caching issues and
apt-get install instructions fail. For example, say you have a
FROM ubuntu:14.04 RUN apt-get update RUN apt-get install -y curl
After building the image, all layers are in the Docker cache. Suppose you later
apt-get install by adding extra package:
FROM ubuntu:14.04 RUN apt-get update RUN apt-get install -y curl nginx
Docker sees the initial and modified instructions as identical and reuses the
cache from previous steps. As a result the
apt-get update is not executed
because the build uses the cached version. Because the
apt-get update is not
run, your build can potentially get an outdated version of the
RUN apt-get update && apt-get install -y ensures your Dockerfile
installs the latest package versions with no further coding or manual
intervention. This technique is known as “cache busting”. You can also achieve
cache-busting by specifying a package version. This is known as version pinning,
RUN apt-get update && apt-get install -y \ package-bar \ package-baz \ package-foo=1.3.*
Version pinning forces the build to retrieve a particular version regardless of what’s in the cache. This technique can also reduce failures due to unanticipated changes in required packages.
Below is a well-formed
RUN instruction that demonstrates all the
RUN apt-get update && apt-get install -y \ aufs-tools \ automake \ build-essential \ curl \ dpkg-sig \ libcap-dev \ libsqlite3-dev \ mercurial \ reprepro \ ruby1.9.1 \ ruby1.9.1-dev \ s3cmd=1.1.* \ && rm -rf /var/lib/apt/lists/*
s3cmd instructions specifies a version
1.1.*. If the image previously
used an older version, specifying the new one causes a cache bust of
update and ensure the installation of the new version. Listing packages on
each line can also prevent mistakes in package duplication.
In addition, when you clean up the apt cache by removing
reduces the image size, since the apt cache is not stored in a layer. Since the
RUN statement starts with
apt-get update, the package cache is always
refreshed prior to
Official Debian and Ubuntu images automatically run
apt-get clean, so explicit invocation is not required.
RUN commands depend on the ability to pipe the output of one command into another, using the pipe character (
|), as in the following example:
RUN wget -O - https://some.site | wc -l > /number
Docker executes these commands using the
/bin/sh -c interpreter, which only
evaluates the exit code of the last operation in the pipe to determine success.
In the example above this build step succeeds and produces a new image so long
wc -l command succeeds, even if the
wget command fails.
If you want the command to fail due to an error at any stage in the pipe,
set -o pipefail && to ensure that an unexpected error prevents the
build from inadvertently succeeding. For example:
RUN set -o pipefail && wget -O - https://some.site | wc -l > /number
Not all shells support the
In such cases (such as the
dashshell, which is the default shell on Debian-based images), consider using the exec form of
RUNto explicitly choose a shell that does support the
pipefailoption. For example:
RUN ["/bin/bash", "-c", "set -o pipefail && wget -O - https://some.site | wc -l > /number"]
CMD instruction should be used to run the software contained by your
image, along with any arguments.
CMD should almost always be used in the form
CMD [“executable”, “param1”, “param2”…]. Thus, if the image is for a
service, such as Apache and Rails, you would run something like
["apache2","-DFOREGROUND"]. Indeed, this form of the instruction is recommended
for any service-based image.
In most other cases,
CMD should be given an interactive shell, such as bash,
python and perl. For example,
CMD ["perl", "-de0"],
CMD ["python"], or
[“php”, “-a”]. Using this form means that when you execute something like
docker run -it python, you’ll get dropped into a usable shell, ready to go.
CMD should rarely be used in the manner of
CMD [“param”, “param”] in
you and your expected users are already quite familiar with how
EXPOSE instruction indicates the ports on which a container listens
for connections. Consequently, you should use the common, traditional port for
your application. For example, an image containing the Apache web server would
EXPOSE 80, while an image containing MongoDB would use
EXPOSE 27017 and
For external access, your users can execute
docker run with a flag indicating
how to map the specified port to the port of their choice.
For container linking, Docker provides environment variables for the path from
the recipient container back to the source (ie,
To make new software easier to run, you can use
ENV to update the
PATH environment variable for the software your container installs. For
ENV PATH /usr/local/nginx/bin:$PATH ensures that
ENV instruction is also useful for providing required environment
variables specific to services you wish to containerize, such as Postgres’s
ENV can also be used to set commonly used version numbers so that
version bumps are easier to maintain, as seen in the following example:
ENV PG_MAJOR 9.3 ENV PG_VERSION 9.3.4 RUN curl -SL http://example.com/postgres-$PG_VERSION.tar.xz | tar -xJC /usr/src/postgress && … ENV PATH /usr/local/postgres-$PG_MAJOR/bin:$PATH
Similar to having constant variables in a program (as opposed to hard-coding
values), this approach lets you change a single
ENV instruction to
auto-magically bump the version of the software in your container.
ENV line creates a new intermediate layer, just like
RUN commands. This
means that even if you unset the environment variable in a future layer, it
still persists in this layer and its value can be dumped. You can test this by
creating a Dockerfile like the following, and then building it.
FROM alpine ENV ADMIN_USER="mark" RUN echo $ADMIN_USER > ./mark RUN unset ADMIN_USER CMD sh
$ docker run --rm -it test sh echo $ADMIN_USER mark
To prevent this, and really unset the environment variable, use a
with shell commands, to set, use, and unset the variable all in a single layer.
You can separate your commands with
&&. If you use the second method,
and one of the commands fails, the
docker build also fails. This is usually a
good idea. Using
\ as a line continuation character for Linux Dockerfiles
improves readability. You could also put all of the commands into a shell script
and have the
RUN command just run that shell script.
FROM alpine RUN export ADMIN_USER="mark" \ && echo $ADMIN_USER > ./mark \ && unset ADMIN_USER CMD sh
$ docker run --rm -it test sh echo $ADMIN_USER
ADD or COPY
COPY are functionally similar, generally speaking,
is preferred. That’s because it’s more transparent than
supports the basic copying of local files into the container, while
some features (like local-only tar extraction and remote URL support) that are
not immediately obvious. Consequently, the best use for
ADD is local tar file
auto-extraction into the image, as in
ADD rootfs.tar.xz /.
If you have multiple
Dockerfile steps that use different files from your
COPY them individually, rather than all at once. This ensures that
each step’s build cache is only invalidated (forcing the step to be re-run) if
the specifically required files change.
COPY requirements.txt /tmp/ RUN pip install --requirement /tmp/requirements.txt COPY . /tmp/
Results in fewer cache invalidations for the
RUN step, than if you put the
COPY . /tmp/ before it.
Because image size matters, using
ADD to fetch packages from remote URLs is
strongly discouraged; you should use
wget instead. That way you can
delete the files you no longer need after they’ve been extracted and you don’t
have to add another layer in your image. For example, you should avoid doing
ADD http://example.com/big.tar.xz /usr/src/things/ RUN tar -xJf /usr/src/things/big.tar.xz -C /usr/src/things RUN make -C /usr/src/things all
And instead, do something like:
RUN mkdir -p /usr/src/things \ && curl -SL http://example.com/big.tar.xz \ | tar -xJC /usr/src/things \ && make -C /usr/src/things all
For other items (files, directories) that do not require
auto-extraction capability, you should always use
The best use for
ENTRYPOINT is to set the image’s main command, allowing that
image to be run as though it was that command (and then use
CMD as the
Let’s start with an example of an image for the command line tool
ENTRYPOINT ["s3cmd"] CMD ["--help"]
Now the image can be run like this to show the command’s help:
$ docker run s3cmd
Or using the right parameters to execute a command:
$ docker run s3cmd ls s3://mybucket
This is useful because the image name can double as a reference to the binary as shown in the command above.
ENTRYPOINT instruction can also be used in combination with a helper
script, allowing it to function in a similar way to the command above, even
when starting the tool may require more than one step.
For example, the Postgres Official Image
uses the following script as its
#!/bin/bash set -e if [ "$1" = 'postgres' ]; then chown -R postgres "$PGDATA" if [ -z "$(ls -A "$PGDATA")" ]; then gosu postgres initdb fi exec gosu postgres "$@" fi exec "$@"
Configure app as PID 1
This script uses the
execBash command so that the final running application becomes the container’s PID 1. This allows the application to receive any Unix signals sent to the container. For more, see the
The helper script is copied into the container and run via
COPY ./docker-entrypoint.sh / ENTRYPOINT ["/docker-entrypoint.sh"] CMD ["postgres"]
This script allows the user to interact with Postgres in several ways.
It can simply start Postgres:
$ docker run postgres
Or, it can be used to run Postgres and pass parameters to the server:
$ docker run postgres postgres --help
Lastly, it could also be used to start a totally different tool, such as Bash:
$ docker run --rm -it postgres bash
VOLUME instruction should be used to expose any database storage area,
configuration storage, or files/folders created by your docker container. You
are strongly encouraged to use
VOLUME for any mutable and/or user-serviceable
parts of your image.
If a service can run without privileges, use
USER to change to a non-root
user. Start by creating the user and group in the
Dockerfile with something
RUN groupadd -r postgres && useradd --no-log-init -r -g postgres postgres.
Consider an explicit UID/GID
Users and groups in an image are assigned a non-deterministic UID/GID in that the “next” UID/GID is assigned regardless of image rebuilds. So, if it’s critical, you should assign an explicit UID/GID.
Due to an unresolved bug in the Go archive/tar package’s handling of sparse files, attempting to create a user with a significantly large UID inside a Docker container can lead to disk exhaustion because
/var/log/faillogin the container layer is filled with NULL (\0) characters. A workaround is to pass the
--no-log-initflag to useradd. The Debian/Ubuntu
adduserwrapper does not support this flag.
Avoid installing or using
sudo as it has unpredictable TTY and
signal-forwarding behavior that can cause problems. If you absolutely need
functionality similar to
sudo, such as initializing the daemon as
running it as non-
root), consider using “gosu”.
Lastly, to reduce layers and complexity, avoid switching
USER back and forth
For clarity and reliability, you should always use absolute paths for your
WORKDIR. Also, you should use
WORKDIR instead of proliferating instructions
RUN cd … && do-something, which are hard to read, troubleshoot, and
ONBUILD command executes after the current
Dockerfile build completes.
ONBUILD executes in any child image derived
FROM the current image. Think
ONBUILD command as an instruction the parent
to the child
A Docker build executes
ONBUILD commands before any command in a child
ONBUILD is useful for images that are going to be built
FROM a given
image. For example, you would use
ONBUILD for a language stack image that
builds arbitrary user software written in that language within the
Dockerfile, as you can see in Ruby’s
Images built from
ONBUILD should get a separate tag, for example:
Be careful when putting
ONBUILD. The “onbuild” image
fails catastrophically if the new build’s context is missing the resource being
added. Adding a separate tag, as recommended above, helps mitigate this by
Dockerfile author to make a choice.
Examples for Official Repositories
These Official Repositories have exemplary
- Dockerfile Reference
- More about Base Images
- More about Automated Builds
- Guidelines for Creating Official Repositories