Best practices for writing Dockerfiles
Estimated reading time: 31 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 Dockerfile
:
FROM ubuntu:18.04
COPY . /app
RUN make /app
CMD python /app/app.py
Each instruction creates one layer:
FROM
creates a layer from theubuntu:18.04
Docker image.COPY
adds files from your Docker client’s current directory.RUN
builds your application withmake
.CMD
specifies 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
configuration.
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 (-f
). Regardless
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
context.
Build context example
Create a directory for the build context and
cd
into it. Write “hello” into a text file namedhello
and create a Dockerfile that runscat
on 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 .
Move
Dockerfile
andhello
into separate directories and build a second version of the image (without relying on cache from the last build). Use-f
to 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
building your Dockerfile
:
Sending build context to Docker daemon 187.8MB
Pipe Dockerfile through stdin
Docker has the ability to build images by piping Dockerfile
through stdin
with a local or remote build context. Piping a Dockerfile
through stdin
can be useful to perform one-off builds without writing a Dockerfile to disk,
or in situations where the Dockerfile
is generated, and should not persist
afterwards.
The examples in this section use here documents for convenience, but any method to provide the
Dockerfile
onstdin
can be used.For example, the following commands are equivalent:
echo -e 'FROM busybox\nRUN echo "hello world"' | docker build -
docker build -<<EOF FROM busybox RUN echo "hello world" EOF
You can substitute the examples with your preferred approach, or the approach that best fits your use-case.
Build an image using a Dockerfile from stdin, without sending build context
Use this syntax to build an image using a Dockerfile
from stdin
, without
sending additional files as build context. The hyphen (-
) takes the position
of the PATH
, and instructs Docker to read the build context (which only
contains a Dockerfile
) from stdin
instead of a directory:
docker build [OPTIONS] -
The following example builds an image using a Dockerfile
that is passed through
stdin
. No files are sent as build context to the daemon.
docker build -t myimage:latest -<<EOF
FROM busybox
RUN echo "hello world"
EOF
Omitting the build context can be useful in situations where your Dockerfile
does not require files to be copied into the image, and improves the build-speed,
as no files are sent to the daemon.
If you want to improve the build-speed by excluding some files from the build- context, refer to exclude with .dockerignore.
Note: Attempting to build a Dockerfile that uses
COPY
orADD
will fail if this syntax is used. The following example illustrates this:# create a directory to work in mkdir example cd example # create an example file touch somefile.txt docker build -t myimage:latest -<<EOF FROM busybox COPY somefile.txt . RUN cat /somefile.txt EOF # observe that the build fails ... Step 2/3 : COPY somefile.txt . COPY failed: stat /var/lib/docker/tmp/docker-builder249218248/somefile.txt: no such file or directory
Build from a local build context, using a Dockerfile from stdin
Use this syntax to build an image using files on your local filesystem, but using
a Dockerfile
from stdin
. The syntax uses the -f
(or --file
) option to
specify the Dockerfile
to use, using a hyphen (-
) as filename to instruct
Docker to read the Dockerfile
from stdin
:
docker build [OPTIONS] -f- PATH
The example below uses the current directory (.
) as the build context, and builds
an image using a Dockerfile
that is passed through stdin
using a here
document.
# create a directory to work in
mkdir example
cd example
# create an example file
touch somefile.txt
# build an image using the current directory as context, and a Dockerfile passed through stdin
docker build -t myimage:latest -f- . <<EOF
FROM busybox
COPY somefile.txt .
RUN cat /somefile.txt
EOF
Build from a remote build context, using a Dockerfile from stdin
Use this syntax to build an image using files from a remote git
repository,
using a Dockerfile
from stdin
. The syntax uses the -f
(or --file
) option to
specify the Dockerfile
to use, using a hyphen (-
) as filename to instruct
Docker to read the Dockerfile
from stdin
:
docker build [OPTIONS] -f- PATH
This syntax can be useful in situations where you want to build an image from a
repository that does not contain a Dockerfile
, or if you want to build with a custom
Dockerfile
, without maintaining your own fork of the repository.
The example below builds an image using a Dockerfile
from stdin
, and adds
the hello.c
file from the “hello-world” Git repository on GitHub.
docker build -t myimage:latest -f- https://github.com/docker-library/hello-world.git <<EOF
FROM busybox
COPY hello.c .
EOF
Under the hood
When building an image using a remote Git repository as build context, Docker performs a
git clone
of the repository on the local machine, and sends those files as build context to the daemon. This feature requiresgit
to be installed on the host where you run thedocker build
command.
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
similar to .gitignore
files. For information on creating one, see the
.dockerignore file.
Use multi-stage builds
Multi-stage builds allow you to drastically reduce the size of your final image, without struggling to reduce the number of intermediate layers and files.
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:1.11-alpine 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.
Decouple applications
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:
-
Only the instructions
RUN
,COPY
,ADD
create layers. Other instructions create temporary intermediate images, and do not increase the size of the build. -
Where possible, use 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 buildpack-deps
image:
RUN apt-get update && apt-get install -y \
bzr \
cvs \
git \
mercurial \
subversion \
&& rm -rf /var/lib/apt/lists/*
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 --no-cache=true
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
Dockerfile
with one of the child images is sufficient. However, certain instructions require more examination and explanation. -
For the
ADD
andCOPY
instructions, 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
ADD
andCOPY
commands, cache checking does not look at the files in the container to determine a cache match. For example, when processing aRUN apt-get -y update
command 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.
Dockerfile instructions
These recommendations are designed to help you create an efficient and
maintainable Dockerfile
.
FROM
Dockerfile reference for the FROM instruction
Whenever possible, use current official images 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.
LABEL
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
supported.
# 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.
RUN
Dockerfile reference for the RUN instruction
Split long or complex RUN
statements on multiple lines separated with
backslashes to make your Dockerfile
more readable, understandable, and
maintainable.
apt-get
Probably the most common use-case for RUN
is an application of apt-get
.
Because it installs packages, the RUN apt-get
command has several gotchas to
look out for.
Avoid 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.
Always combine RUN apt-get update
with apt-get install
in the same RUN
statement. For example:
RUN apt-get update && apt-get install -y \
package-bar \
package-baz \
package-foo \
&& rm -rf /var/lib/apt/lists/*
Using apt-get update
alone in a RUN
statement causes caching issues and
subsequent apt-get install
instructions fail. For example, say you have a
Dockerfile:
FROM ubuntu:18.04
RUN apt-get update
RUN apt-get install -y curl
After building the image, all layers are in the Docker cache. Suppose you later
modify apt-get install
by adding extra package:
FROM ubuntu:18.04
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 curl
and
nginx
packages.
Using 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,
for example:
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 apt-get
recommendations.
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/*
The s3cmd
argument specifies a version 1.1.*
. If the image previously
used an older version, specifying the new one causes a cache bust of apt-get
update
and ensures 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 /var/lib/apt/lists
it
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 apt-get install
.
Official Debian and Ubuntu images automatically run
apt-get clean
, so explicit invocation is not required.
Using pipes
Some 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
as the 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,
prepend 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
-o pipefail
option.In cases such as the
dash
shell on Debian-based images, consider using the exec form ofRUN
to explicitly choose a shell that does support thepipefail
option. For example:RUN ["/bin/bash", "-c", "set -o pipefail && wget -O - https://some.site | wc -l > /number"]
CMD
Dockerfile reference for the CMD instruction
The CMD
instruction should be used to run the software contained in your
image, along with any arguments. CMD
should almost always be used in the form
of CMD ["executable", "param1", "param2"…]
. Thus, if the image is for a
service, such as Apache and Rails, you would run something like CMD
["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 CMD
["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
conjunction with ENTRYPOINT
, unless
you and your expected users are already quite familiar with how ENTRYPOINT
works.
EXPOSE
Dockerfile reference for the EXPOSE instruction
The 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
use EXPOSE 80
, while an image containing MongoDB would use EXPOSE 27017
and
so on.
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, MYSQL_PORT_3306_TCP
).
ENV
Dockerfile reference for the ENV instruction
To make new software easier to run, you can use ENV
to update the
PATH
environment variable for the software your container installs. For
example, ENV PATH=/usr/local/nginx/bin:$PATH
ensures that CMD ["nginx"]
just works.
The ENV
instruction is also useful for providing required environment
variables specific to services you wish to containerize, such as Postgres’s
PGDATA
.
Lastly, ENV
can also be used to set commonly used version numbers so that
version bumps are easier to maintain, as seen in the following example:
ENV PG_MAJOR=9.3
ENV PG_VERSION=9.3.4
RUN curl -SL https://example.com/postgres-$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.
Each 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’t 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
$ docker run --rm test sh -c 'echo $ADMIN_USER'
mark
To prevent this, and really unset the environment variable, use a RUN
command
with shell commands, to set, use, and unset the variable all in a single layer.
You can separate your commands with ;
or &&
. 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 test sh -c 'echo $ADMIN_USER'
ADD or COPY
Although ADD
and COPY
are functionally similar, generally speaking, COPY
is preferred. That’s because it’s more transparent than ADD
. COPY
only
supports the basic copying of local files into the container, while ADD
has
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
context, 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.
For example:
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 curl
or 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
things like:
ADD https://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 https://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 ADD
’s tar
auto-extraction capability, you should always use COPY
.
ENTRYPOINT
Dockerfile reference for the ENTRYPOINT instruction
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
default flags).
Let’s start with an example of an image for the command line tool s3cmd
:
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.
The 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 ENTRYPOINT
:
#!/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
exec
Bash 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 theENTRYPOINT
reference.
The helper script is copied into the container and run via ENTRYPOINT
on
container start:
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
Dockerfile reference for the VOLUME instruction
The 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.
USER
Dockerfile reference for the USER instruction
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
like 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/faillog
in the container layer is filled with NULL (\0) characters. A workaround is to pass the--no-log-init
flag to useradd. The Debian/Ubuntuadduser
wrapper 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 root
but
running it as non-root
, consider using “gosu”.
Lastly, to reduce layers and complexity, avoid switching USER
back and forth
frequently.
WORKDIR
Dockerfile reference for the WORKDIR instruction
For clarity and reliability, you should always use absolute paths for your
WORKDIR
. Also, you should use WORKDIR
instead of proliferating instructions
like RUN cd … && do-something
, which are hard to read, troubleshoot, and
maintain.
ONBUILD
Dockerfile reference for the ONBUILD instruction
An ONBUILD
command executes after the current Dockerfile
build completes.
ONBUILD
executes in any child image derived FROM
the current image. Think
of the ONBUILD
command as an instruction the parent Dockerfile
gives
to the child Dockerfile
.
A Docker build executes ONBUILD
commands before any command in a child
Dockerfile
.
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 ONBUILD
variants.
Images built with ONBUILD
should get a separate tag, for example:
ruby:1.9-onbuild
or ruby:2.0-onbuild
.
Be careful when putting ADD
or COPY
in 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
allowing the Dockerfile
author to make a choice.
Examples for Official Images
These Official Images have exemplary Dockerfile
s:
Additional resources:
- Dockerfile Reference
- More about Base Images
- More about Automated Builds
- Guidelines for Creating Official Images