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  Use multi-stage builds
  Multi-stage builds let you reduce the size of your final image, by creating a
  cleaner separation between the building of your image and the final output.
  Split your Dockerfile instructions into distinct stages to make sure that the
  resulting output only contains the files that are needed to run the application.
  Using multiple stages can also let you build more efficiently by executing
  build steps in parallel.
  Multi-stage builds
  for more
  information.
  Create reusable stages
  If you have multiple images with a lot in common, consider creating a reusable
  stage that includes the shared components, and basing your unique stages on
  that. Docker only needs to build the common stage once. This means that your derivative images use memory
  on the Docker host more efficiently and load more quickly.
  It's also easier to maintain a common base stage ("Don't repeat yourself"),
  than it is to have multiple different stages doing similar things.
  Choose the right base image
  The first step towards achieving a secure image is to choose the right base
  image. When choosing an image, ensure it's built from a trusted source and keep
  it small.
  Docker Official Images
  are a curated collection that have clear documentation, promote best
  practices, and are regularly updated. They provide a trusted starting point
  for many applications.
  Verified Publisher
  images
  are high-quality images published and maintained by the organizations
  partnering with Docker, with Docker verifying the authenticity of the content
  in their repositories.
  Docker-Sponsored Open Source
  are published and maintained by open source projects sponsored by Docker
  through an
  open source program
  When you pick your base image, look out for the badges indicating that the
  image is part of these programs.
  When building your own image from a Dockerfile, ensure you choose a minimal base
  image that matches your requirements. A smaller base image not only offers
  portability and fast downloads, but also shrinks the size of your image and
  minimizes the number of vulnerabilities introduced through the dependencies.
  You should also consider using two types of base image: one for building and
  unit testing, and another (typically slimmer) image for production. In the
  later stages of development, your image may not require build tools such as
  compilers, build systems, and debugging tools. A small image with minimal
  dependencies can considerably lower the attack surface.
  Rebuild your images often
  Docker images are immutable. Building an image is taking a snapshot of that
  image at that moment. That includes any base images, libraries, or other
  software you use in your build. To keep your images up-to-date and secure, make
  sure to rebuild your image often, with updated dependencies.
  To ensure that you're getting the latest versions of dependencies in your build,
  you can use the
  --no-cache
  option to avoid cache hits.
  docker build --no-cache -t my-image:my-tag .
  The following Dockerfile uses the
  tag of the
  ubuntu
  image. Over time,
  that tag may resolve to a different underlying version of the
  ubuntu
  image,
  as the publisher rebuilds the image with new security patches and updated
  libraries. Using the
  --no-cache
  , you can avoid cache hits and ensure a fresh
  download of base images and dependencies.
  # syntax=docker/dockerfile:1
  FROM
  ubuntu:24.04
  apt-get -y update
  apt-get install -y --no-install-recommends python3
  Also consider
  pinning base image versions
  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 example, to exclude all files with the
  extension:
  *.md
  For information on creating one, see
  Dockerignore file
  Create ephemeral containers
  The image defined by your Dockerfile should generate containers that are as
  ephemeral as possible. Ephemeral means 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.
  Don't install unnecessary packages
  Avoid installing extra or unnecessary packages just because they might be nice to have. For example, you donât need to include a text editor in a database image.
  When you avoid installing extra or unnecessary packages, your images have reduced complexity, reduced dependencies, reduced file sizes, and reduced build times.
  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's 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.
  Sort multi-line arguments
  Whenever possible, sort multi-line arguments alphanumerically to make maintenance easier.
  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.
  Hereâs an example from the
  buildpack-deps image
  apt-get update
  apt-get install -y --no-install-recommends
  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. For each instruction, Docker
  checks whether it can reuse the instruction from the build cache.
  Understanding how the build cache works, and how cache invalidation occurs,
  is critical for ensuring faster builds.
  For more information about the Docker build cache and how to optimize your builds,
  Docker build cache
  Pin base image versions
  Image tags are mutable, meaning a publisher can update a tag to point to a new
  image. This is useful because it lets publishers update tags to point to
  newer versions of an image. And as an image consumer, it means you
  automatically get the new version when you re-build your image.
  For example, if you specify
  FROM alpine:3.21
  in your Dockerfile,
  resolves to the latest patch version for
  # syntax=docker/dockerfile:1
  FROM
  alpine:3.21
  At one point in time, the
  tag might point to version 3.21.1 of the
  image. If you rebuild the image 3 months later, the same tag might point to a
  different version, such as 3.21.4. This publishing workflow is best practice,
  and most publishers use this tagging strategy, but it isn't enforced.
  The downside with this is that you're not guaranteed to get the same for every
  build. This could result in breaking changes, and it means you also don't have
  an audit trail of the exact image versions that you're using.
  To fully secure your supply chain integrity, you can pin the image version to a
  specific digest. By pinning your images to a digest, you're guaranteed to
  always use the same image version, even if a publisher replaces the tag with a
  new image. For example, the following Dockerfile pins the Alpine image to the
  same tag as earlier,
  , but this time with a digest reference as well.
  # syntax=docker/dockerfile:1
  FROM
  alpine:3.21@sha256:a8560b36e8b8210634f77d9f7f9efd7ffa463e380b75e2e74aff4511df3ef88c
  With this Dockerfile, even if the publisher updates the
  tag, your builds
  would still use the pinned image version:
  a8560b36e8b8210634f77d9f7f9efd7ffa463e380b75e2e74aff4511df3ef88c
  While this helps you avoid unexpected changes, it's also more tedious to have
  to look up and include the image digest for base image versions manually each
  time you want to update it. And you're opting out of automated security fixes,
  which is likely something you want to get.
  Docker Scout's default
  Up-to-Date Base Images
  checks whether the
  base image version you're using is in fact the latest version. This policy also
  checks if pinned digests in your Dockerfile correspond to the correct version.
  If a publisher updates an image that you've pinned, the policy evaluation
  returns a non-compliant status, indicating that you should update your image.
  Docker Scout also supports an automated remediation workflow for keeping your
  base images up-to-date. When a new image digest is available, Docker Scout can
  automatically raise a pull request on your repository to update your
  Dockerfiles to use the latest version. This is better than using a tag that
  changes the version automatically, because you're in control and you have an
  audit trail of when and how the change occurred.
  For more information about automatically updating your base images with Docker
  Scout, see
  Remediation
  Build and test your images in CI
  When you check in a change to source control or create a pull request, use
  GitHub Actions
  or another CI/CD pipeline to
  automatically build and tag a Docker image and test it.
  Dockerfile instructions
  Follow these recommendations on how to properly use the
  Dockerfile instructions
  to create an efficient and maintainable Dockerfile.
  To improve linting, code navigation, and vulnerability scanning of your Dockerfiles in Visual Studio Code
  Docker VS Code Extension
  FROM
  Whenever possible, use current official images as the basis for your
  images. Docker recommends the
  Alpine image
  as it
  is tightly controlled and small in size (currently under 6 MB), while still
  being a full Linux distribution.
  For more information about the
  FROM
  instruction, see
  Dockerfile reference for the FROM instruction
  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
  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. For example:
  # 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. For example:
  # Set multiple labels on one line
  LABEL
  com.example.version
  "0.0.1-beta"
  com.example.release-date
  "2015-02-12"
  The above example 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"
  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
  statements on multiple lines separated with
  backslashes to make your Dockerfile more readable, understandable, and
  maintainable.
  For example, you can chain commands with the
  operator, and use
  escape characters to break long commands into multiple lines.
  apt-get update
  apt-get install -y --no-install-recommends
  package-bar
  package-baz
  package-foo
  By default, backslash escapes a newline character, but you can change it with
  escape
  directive
  You can also use here documents to run multiple commands without chaining them
  with a pipeline operator:
  <<EOF
  apt-get update
  apt-get install -y --no-install-recommends
  package-bar
  package-baz
  package-foo
  For more information about
  , see
  Dockerfile reference for the RUN instruction
  apt-get
  One common use case for
  instructions in Debian-based images is to install
  software using
  apt-get
  . Because
  apt-get
  installs packages, the
  RUN apt-get
  command has several counter-intuitive behaviors to look out for.
  Always combine
  RUN apt-get update
  with
  apt-get install
  in the same
  statement. For example:
  apt-get update
  apt-get install -y --no-install-recommends
  package-bar
  package-baz
  package-foo
  Using
  apt-get update
  alone in a
  statement causes caching issues and
  subsequent
  apt-get install
  instructions to fail. For example, this issue will occur in the following Dockerfile:
  # syntax=docker/dockerfile:1
  FROM
  ubuntu:22.04
  apt-get update
  apt-get install -y --no-install-recommends curl
  After building the image, all layers are in the Docker cache. Suppose you later
  modify
  apt-get install
  by adding an extra package as shown in the following Dockerfile:
  # syntax=docker/dockerfile:1
  FROM
  ubuntu:22.04
  apt-get update
  apt-get install -y --no-install-recommends 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
  isn't executed
  because the build uses the cached version. Because the
  apt-get update
  isn't
  run, your build can potentially get an outdated version of the
  curl
  nginx
  packages.
  Using
  RUN apt-get update && apt-get install -y --no-install-recommends
  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:
  apt-get update
  apt-get install -y --no-install-recommends
  package-bar
  package-baz
  package-foo
  Version pinning forces the build to retrieve a particular version regardless of
  whatâs in the cache. This technique can also reduce failures due to unanticipated changes
  in required packages.
  Below is a well-formed
  instruction that demonstrates all the
  apt-get
  recommendations.
  apt-get update
  apt-get install -y --no-install-recommends
  aufs-tools
  automake
  build-essential
  curl
  dpkg-sig
  libcap-dev
  libsqlite3-dev
  mercurial
  reprepro
  ruby1.9.1
  ruby1.9.1-dev
  s3cmd
  rm -rf /var/lib/apt/lists/*
  s3cmd
  argument specifies a version
  . 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
  reduces the image size, since the apt cache isn't stored in a layer. Since the
  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
  commands depend on the ability to pipe the output of one command into another, using the pipe character (
  ), as in the following example:
  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:
  -o pipefail
  wget -O - https://some.site
  wc -l > /number
  Note
  Not all shells support the
  -o pipefail
  option.
  In cases such as the
  dash
  shell on
  Debian-based images, consider using the
  exec
  form of
  to explicitly
  choose a shell that does support the
  pipefail
  option. For example:
  "/bin/bash"
  "-c"
  "set -o pipefail && wget -O - https://some.site | wc -l > /number"
  instruction should be used to run the software contained in your
  image, along with any arguments.
  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
  CMD ["apache2","-DFOREGROUND"]
  . Indeed, this form of the instruction is recommended
  for any service-based image.
  In most other cases,
  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
  , youâll get dropped into a usable shell, ready to go.
  should rarely be used in the manner of
  CMD ["param", "param"]
  conjunction with
  ENTRYPOINT
  , unless
  you and your expected users are already quite familiar with how
  ENTRYPOINT
  works.
  For more information about
  , see
  Dockerfile reference for the CMD instruction
  EXPOSE
  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
  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 (for example,
  MYSQL_PORT_3306_TCP
  For more information about
  EXPOSE
  , see
  Dockerfile reference for the EXPOSE instruction
  To make new software easier to run, you can use
  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.
  instruction is also useful for providing the required environment
  variables specific to services you want to containerize, such as Postgresâs
  PGDATA
  Lastly,
  can also be used to set commonly used version numbers so that
  version bumps are easier to maintain, as seen in the following example:
  PG_MAJOR
  PG_VERSION
  curl -SL https://example.com/postgres-
  $PG_VERSION
  .tar.xz
  tar -xJC /usr/src/postgres
  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
  instruction to
  automatically bump the version of the software in your container.
  Each
  line creates a new intermediate layer, just like
  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.
  # syntax=docker/dockerfile:1
  FROM
  alpine
  ADMIN_USER
  "mark"
  echo
  $ADMIN_USER
  > ./mark
  unset
  ADMIN_USER
  docker run --rm
  test
  sh -c
  'echo $ADMIN_USER'
  mark
  To prevent this and unset the environment variable, use a
  command
  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
  command just run that shell script.
  # syntax=docker/dockerfile:1
  FROM
  alpine
  export
  ADMIN_USER
  "mark"
  echo
  $ADMIN_USER
  > ./mark
  unset
  ADMIN_USER
  docker run --rm
  test
  sh -c
  'echo $ADMIN_USER'
  For more information about
  , see
  Dockerfile reference for the ENV instruction
  ADD or COPY
  COPY
  are functionally similar.
  COPY
  supports basic copying of
  files into the container, from the
  build context
  or from a stage in a
  multi-stage build
  supports features for fetching files from remote HTTPS and Git URLs, and
  extracting tar files automatically when adding files from the build context.
  You'll mostly want to use
  COPY
  for copying files from one stage to another in
  a multi-stage build. If you need to add files from the build context to the
  container temporarily to execute a
  instruction, you can often substitute
  COPY
  instruction with a bind mount instead. For example, to temporarily
  add a
  requirements.txt
  file for a
  RUN pip install
  instruction:
  --mount
  type
  bind,source
  requirements.txt,target
  /tmp/requirements.txt
  pip install --requirement /tmp/requirements.txt
  Bind mounts are more efficient than
  COPY
  for including files from the build
  context in the container. Note that bind-mounted files are only added
  temporarily for a single
  instruction, and don't persist in the final
  image. If you need to include files from the build context in the final image,
  COPY
  instruction is best for when you need to download a remote artifact
  as part of your build.
  is better than manually adding files using
  something like
  wget
  , because it ensures a more precise build cache.
  also has built-in support for checksum validation of the remote
  resources, and a protocol for parsing branches, tags, and subdirectories from
  Git URLs
  The following example uses
  to download a .NET installer. Combined with
  multi-stage builds, only the .NET runtime remains in the final stage, no
  intermediate files.
  # syntax=docker/dockerfile:1
  FROM
  scratch AS src
  DOTNET_VERSION
  .0.0-preview.6.23329.7
  --checksum
  sha256:270d731bd08040c6a3228115de1f74b91cf441c584139ff8f8f6503447cebdbb
  https://dotnetcli.azureedge.net/dotnet/Runtime/
  $DOTNET_VERSION
  /dotnet-runtime-
  $DOTNET_VERSION
  -linux-arm64.tar.gz /dotnet.tar.gz
  FROM
  mcr.microsoft.com/dotnet/runtime-deps:8.0.0-preview.6-bookworm-slim-arm64v8 AS installer
  # Retrieve .NET Runtime
  --mount
  from
  src,target
  /src <<EOF
  mkdir -p /dotnet
  tar -oxzf /src/dotnet.tar.gz -C /dotnet
  FROM
  mcr.microsoft.com/dotnet/runtime-deps:8.0.0-preview.6-bookworm-slim-arm64v8
  COPY
  --from
  installer /dotnet /usr/share/dotnet
  ln -s /usr/share/dotnet/dotnet /usr/bin/dotnet
  For more information about
  COPY
  , see the following:
  Dockerfile reference for the ADD instruction
  Dockerfile reference for the COPY instruction
  ENTRYPOINT
  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
  as the
  default flags.
  The following is an example of an image for the command line tool
  s3cmd
  ENTRYPOINT
  "s3cmd"
  "--help"
  You can use the following command to run the image and show the command's help:
  docker run s3cmd
  Or, you can use the right parameters to execute a command, like in the following example:
  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
  ENTRYPOINT
  #!/bin/bash
  'postgres'
  then
  chown -R postgres
  $PGDATA
  ls -A
  $PGDATA
  then
  gosu postgres initdb
  exec
  gosu postgres
  exec
  This script uses
  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 information, see the
  ENTRYPOINT
  In the following example, a helper script is copied into the container and run via
  ENTRYPOINT
  container start:
  COPY
  ./docker-entrypoint.sh /
  ENTRYPOINT
  "/docker-entrypoint.sh"
  "postgres"
  This script lets you interact with Postgres in several ways.
  It can simply start Postgres:
  docker run postgres
  Or, you can use it to run Postgres and pass parameters to the server:
  docker run postgres postgres --help
  Lastly, you can use it to start a totally different tool, such as Bash:
  docker run --rm -it postgres bash
  For more information about
  ENTRYPOINT
  , see
  Dockerfile reference for the ENTRYPOINT instruction
  VOLUME
  You should use the
  VOLUME
  instruction to expose any database storage area,
  configuration storage, or files and folders created by your Docker container. You
  are strongly encouraged to use
  VOLUME
  for any combination of mutable or user-serviceable
  parts of your image.
  For more information about
  VOLUME
  , see
  Dockerfile reference for the VOLUME instruction
  USER
  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 the following example:
  groupadd -r postgres
  useradd --no-log-init -r -g postgres postgres
  Note
  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 itâs
  critical, you should assign an explicit UID/GID.
  Note
  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
   (\0) characters. A workaround is to pass the
  --no-log-init
  flag to
  useradd
  . The Debian/Ubuntu
  adduser
  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
  running it as non-
  root
  , consider using
  âgosuâ
  Lastly, to reduce layers and complexity, avoid switching
  USER
  back and forth
  frequently.
  For more information about
  USER
  , see
  Dockerfile reference for the USER instruction
  WORKDIR
  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 â¦ && do-something
  , which are hard to read, troubleshoot, and
  maintain.
  For more information about
  WORKDIR
  , see
  Dockerfile reference for the
  WORKDIR
  instruction
  ONBUILD
  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 that 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
  Rubyâs
  ONBUILD
  variants
  Images built with
  ONBUILD
  should get a separate tag. For example,
  ruby:1.9-onbuild
  ruby:2.0-onbuild
  Be careful when putting
  COPY
  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.
  For more information about
  ONBUILD
  , see
  Dockerfile reference for the ONBUILD instruction