How to use this image

All examples in this guide use the public image. If you've mirrored the repository for your own use (for example, to your Docker Hub namespace), update your commands to reference the mirrored image instead of the public one.

For example:

• Public image: dhi.io/azure-cli:<tag>
• Mirrored image: <your-namespace>/dhi-azure-cli:<tag>

For the examples, you must first use docker login dhi.io to authenticate to the registry to pull the images.

Getting started with Azure CLI

The image's entry point is az, so any arguments you pass after the image reference are handed directly to the Azure CLI. Check the version:

docker run --rm dhi.io/azure-cli:<tag> version

Run any other Azure CLI command the same way, for example listing the built-in Azure clouds:

docker run --rm dhi.io/azure-cli:<tag> cloud list --output table

The image provides the az command and its Python runtime. For complete command, usage, and configuration documentation, see the upstream project⁠.

Configuration directory

Azure CLI keeps its configuration, logs, sign-in token cache, and telemetry state in a config directory. This image sets AZURE_CONFIG_DIR=/azure and creates that directory writable for the nonroot runtime user. To persist sign-in state and configuration across container runs, mount a volume at /azure:

docker run --rm -v azure-cli-config:/azure dhi.io/azure-cli:<tag> config set core.output=table

That command writes /azure/config in the volume, so the setting is still in effect the next time you run the image with the same volume mounted. Commands that talk to Azure need a sign-in first; see Authentication⁠.

Authentication

Most Azure CLI commands require you to sign in first. In a container, non-interactive sign-in methods are usually the most convenient:

• Service principal: supply the credentials at runtime and sign in with az login --service-principal.

  docker run --rm -v azure-cli-config:/azure \
    -e AZURE_CLIENT_ID -e AZURE_CLIENT_SECRET -e AZURE_TENANT_ID \
    dhi.io/azure-cli:<tag> \
    login --service-principal -u "$AZURE_CLIENT_ID" -p "$AZURE_CLIENT_SECRET" --tenant "$AZURE_TENANT_ID"
  

  Copy

• Managed identity: when running on Azure infrastructure, sign in with az login --identity.

The credentials above are secrets and must be provided at runtime; they are never baked into the image. After a successful sign-in, reuse the same /azure volume so subsequent commands stay authenticated.

Non-hardened images vs. Docker Hardened Images

Entry point

The upstream mcr.microsoft.com/azure-cli image has no entry point and starts a shell by default, so commands are written with a leading az, for example docker run mcr.microsoft.com/azure-cli az group list. This image sets az as the entry point, so drop the leading az and pass the subcommand directly:

docker run --rm dhi.io/azure-cli:<tag> group list

Running the image with no arguments prints az --help. Because az is the entry point on every variant, including dev, open a shell in the dev variant by overriding it:

docker run --rm -it --entrypoint bash dhi.io/azure-cli:<tag>-dev

Configuration location

The upstream mcr.microsoft.com/azure-cli image runs as root and leaves AZURE_CONFIG_DIR unset, so az uses its default of $HOME/.azure — /root/.azure in that image. This image runs as the nonroot user and sets AZURE_CONFIG_DIR=/azure instead.

If you are migrating a mount that targeted the upstream path, retarget it. A -v azcfg:/root/.azure mount is not an error in this image, it is simply ignored: az reads /azure, finds no credentials there, and reports that you are not signed in.

# Upstream
docker run --rm -v azcfg:/root/.azure mcr.microsoft.com/azure-cli az account show

# This image
docker run --rm -v azcfg:/azure dhi.io/azure-cli:<tag> account show

The contents are compatible, so a volume populated by the upstream image works once it is mounted at /azure. Note that the files must be readable by the nonroot user (uid 65532).

Commands that shell out

The runtime variant has no shell and no package manager. Some az subcommands run other programs in the container, and those will not work in the runtime variant unless you add the program yourself. Examples include az aks commands that invoke kubectl, az ssh, and flows that call git. For these workflows, use the dev variant, which includes a shell and package manager, or add the required tools in a build stage alongside az.

Extensions

az extension add works in both variants, because pip is kept in the payload venv for exactly that purpose. Extensions install into $AZURE_CONFIG_DIR/cliextensions, so mount /azure if you want them to survive the container. Extensions that publish prebuilt wheels — the common case — need nothing further.

An extension that compiles on install needs a C toolchain, and neither variant ships one: the dev variant has bash, apt-get and dpkg, but no compiler. Install the build dependencies there first, in a build stage:

FROM dhi.io/azure-cli:<tag>-dev
RUN apt-get update && apt-get install -y --no-install-recommends gcc python3-dev \
 && az extension add --name <extension>

Image variants

Docker Hardened Images come in different variants depending on their intended use.

• Runtime variants are designed to run your application in production. These images are intended to be used either directly or as the FROM image in the final stage of a multi-stage build. These images typically:

  • Run as the nonroot user
  • Do not include a shell or a package manager
  • Contain only the minimal set of libraries needed to run the app

• Build-time variants typically include dev in the variant name and are intended for use in the first stage of a multi-stage Dockerfile. These images typically:

  • Run as the root user
  • Include a shell and package manager
  • Are used to build or compile applications

• FIPS variants include fips in the variant name and tag. They come in both runtime and build-time variants. These variants use cryptographic modules that have been validated under FIPS 140, a U.S. government standard for secure cryptographic operations. For example, usage of MD5 fails in FIPS variants.

  For Azure CLI specifically, the validated module backs the system OpenSSL that Python's ssl links, which is the path az uses for TLS to Azure endpoints. The bundled cryptography library ships its own statically linked OpenSSL, so cryptographic primitives that az drives through cryptography rather than through ssl do not run in the validated module.

Migrate to a Docker Hardened Image

To migrate your application to a Docker Hardened Image, you must update your Dockerfile. At minimum, you must update the base image in your existing Dockerfile to a Docker Hardened Image. This and a few other common changes are listed in the following table of migration notes.

The following steps outline the general migration process.

1. Find hardened images for your app.

   A hardened image may have several variants. Inspect the image tags and find the image variant that meets your needs.

2. Update the base image in your Dockerfile.

   Update the base image in your application's Dockerfile to the hardened image you found in the previous step. For framework images, this is typically going to be an image tagged as dev because it has the tools needed to install packages and dependencies.

3. For multi-stage Dockerfiles, update the runtime image in your Dockerfile.

   To ensure that your final image is as minimal as possible, you should use a multi-stage build. All stages in your Dockerfile should use a hardened image. While intermediary stages will typically use images tagged as dev, your final runtime stage should use a non-dev image variant.

4. Install additional packages

   Docker Hardened Images contain minimal packages in order to reduce the potential attack surface. You may need to install additional packages in your Dockerfile. Inspect the image variants to identify which packages are already installed.

   Only images tagged as dev typically have package managers. You should use a multi-stage Dockerfile to install the packages. Install the packages in the build stage that uses a dev image. Then, if needed, copy any necessary artifacts to the runtime stage that uses a non-dev image.

   For Alpine-based images, you can use apk to install packages. For Debian-based images, you can use apt-get to install packages.

Troubleshooting migration

The following are common issues that you may encounter during migration.

General debugging

The hardened images intended for runtime don't contain a shell nor any tools for debugging. The recommended method for debugging applications built with Docker Hardened Images is to use Docker Debug⁠ to attach to these containers. Docker Debug provides a shell, common debugging tools, and lets you install other tools in an ephemeral, writable layer that only exists during the debugging session.

Permissions

By default image variants intended for runtime, run as the nonroot user. Ensure that necessary files and directories are accessible to the nonroot user. You may need to copy files to different directories or change permissions so your application running as the nonroot user can access them.

Privileged ports

Non-dev hardened images run as a nonroot user by default. As a result, applications in these images can't bind to privileged ports (below 1024) when running in Kubernetes or in Docker Engine versions older than 20.10. To avoid issues, configure your application to listen on port 1025 or higher inside the container, even if you map it to a lower port on the host. For example, docker run -p 80:8080 my-image will work because the port inside the container is 8080, and docker run -p 80:81 my-image won't work because the port inside the container is 81.

No shell

By default, image variants intended for runtime don't contain a shell. Use dev images in build stages to run shell commands and then copy any necessary artifacts into the runtime stage. In addition, use Docker Debug to debug containers with no shell.

Entry point

Docker Hardened Images may have different entry points than images such as Docker Official Images. Use docker inspect to inspect entry points for Docker Hardened Images and update your Dockerfile if necessary.