Prerequisites

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/<repository>:<tag>
• Mirrored image: <your-namespace>/dhi-<repository>:<tag>

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

Start an Alloy instance

# Pull the public image
docker pull dhi.io/alloy:<tag>

# Create minimal config
cat > config.alloy << 'EOF'
logging {
  level  = "info"
  format = "logfmt"
}
prometheus.exporter.self "alloy" {}
prometheus.scrape "alloy" {
  targets    = prometheus.exporter.self.alloy.targets
  forward_to = []
}
EOF

# Start Alloy
docker run --rm -d \
  --name alloy-quick-test \
  -v "$PWD/config.alloy:/etc/alloy/config.alloy:ro" \
  -v alloy-data:/var/lib/alloy/data \
  -p 12345:12345 \
  dhi.io/alloy:<tag> \
  run /etc/alloy/config.alloy \
  --storage.path=/var/lib/alloy/data \
  --server.http.listen-addr=0.0.0.0:12345

# Wait for startup
sleep 5

# Check it's working
docker logs alloy-quick-test
curl http://localhost:12345/metrics | head -10

# Cleanup
docker rm -f alloy-quick-test
docker volume rm alloy-data

Start a Grafana Alloy container

Assuming that config.alloy file is available in your current directory that contains the configuration for Alloy, you can run the following command to start the container with a bind mount to the config.alloy file and a named volume for Alloy's data.

docker run --rm \
  -v "$PWD/config.alloy:/etc/alloy/config.alloy:ro" \
  -v alloy-data:/var/lib/alloy/data \
  -p 12345:12345 \
  dhi.io/alloy:<tag> \
  run /etc/alloy/config.alloy \
  --storage.path=/var/lib/alloy/data \
  --server.http.listen-addr=0.0.0.0:12345

The container starts using the default entrypoint, alloy, and command, run /etc/alloy/config.alloy --storage.path=/var/lib/alloy/data.

Use cases

Use case 1: Send metrics to Prometheus

This example shows how to collect Alloy's internal metrics and forward them to Prometheus using the remote write API.

Step 1: Create a Docker network

docker network create monitoring

Step 2: Create the configuration file

Create config-prometheus.alloy:

logging {
  level  = "info"
  format = "logfmt"
}

prometheus.exporter.self "alloy" {}

prometheus.scrape "alloy" {
  targets    = prometheus.exporter.self.alloy.targets
  forward_to = [prometheus.remote_write.prom.receiver]
}

prometheus.remote_write "prom" {
  endpoint {
    url = "http://prometheus:9090/api/v1/write"
  }
}

Step 3: Verify the configuration

cat config-prometheus.alloy

Step 4: Start Prometheus (if not already running)

docker run -d \
  --name prometheus \
  --network monitoring \
  -p 9090:9090 \
  prom/prometheus \
  --config.file=/etc/prometheus/prometheus.yml \
  --web.enable-remote-write-receiver

Step 5: Start Alloy

docker run --rm -d \
  --name alloy \
  -v "$PWD/config-prometheus.alloy:/etc/alloy/config.alloy:ro" \
  -v alloy-data:/var/lib/alloy/data \
  -p 12345:12345 \
  --network monitoring \
  dhi.io/alloy:<tag> \
  run /etc/alloy/config.alloy \
  --storage.path=/var/lib/alloy/data \
  --server.http.listen-addr=0.0.0.0:12345

Step 6: Verify Alloy is running

docker logs alloy

You should see: msg="now listening for http traffic" addr=0.0.0.0:12345

Use case 2: Collect Docker container metrics

This example shows how to automatically discover and scrape metrics from running Docker containers using Docker socket access.

Step 1: Ensure the monitoring network exists

If you already completed Use Case 1, the monitoring network already exists. If not, create it:

docker network create monitoring

Step 2: Create the configuration file

Create config-docker.alloy:

logging {
  level  = "info"
  format = "logfmt"
}

discovery.docker "containers" {
  host = "unix:///var/run/docker.sock"
}

prometheus.scrape "docker" {
  targets    = discovery.docker.containers.targets
  forward_to = [prometheus.remote_write.prom.receiver]
}

prometheus.remote_write "prom" {
  endpoint {
    url = "http://prometheus:9090/api/v1/write"
  }
}

Step 3: Verify the configuration

cat config-docker.alloy

Step 4: Start Prometheus (if not already running)

docker run -d \
  --name prometheus \
  --network monitoring \
  -p 9090:9090 \
  prom/prometheus \
  --config.file=/etc/prometheus/prometheus.yml \
  --web.enable-remote-write-receiver

Step 5: Start Alloy with Docker socket access

docker run --rm -d \
  --name alloy \
  -v "$PWD/config-docker.alloy:/etc/alloy/config.alloy:ro" \
  -v /var/run/docker.sock:/var/run/docker.sock:ro \
  -v alloy-data:/var/lib/alloy/data \
  -p 12345:12345 \
  --network monitoring \
  dhi.io/alloy:<tag> \
  run /etc/alloy/config.alloy \
  --storage.path=/var/lib/alloy/data \
  --server.http.listen-addr=0.0.0.0:12345

Step 6: Verify Alloy is running

docker logs alloy

You should see: msg="now listening for http traffic" addr=0.0.0.0:12345

Image variants

The Alloy Hardened Image is available as dev, runtime, and FIPS variants.

• 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.

Docker Hardened Images come in different variants depending on their intended use. Image variants are identified by their tag.

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 a 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 tag 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

Non-hardened images vs Docker Hardened Images

Based on empirical testing, here are the key differences:

Why no shell or package manager?

Docker Hardened Images prioritize security through minimalism:

• Reduced attack surface: Fewer binaries mean fewer potential vulnerabilities
• Immutable infrastructure: Runtime containers shouldn't be modified after deployment
• Compliance ready: Meets strict security requirements for regulated environments

The hardened runtime images don't contain a shell nor any tools for debugging. For Grafana Alloy, debugging options include:

• DHI Dev variant: Use dhi.io/alloy:<tag>-dev with entrypoint override

  docker run --rm -it --entrypoint=/bin/bash dhi.io/alloy:<tag>-dev
  

  Copy
• Docker Debug: Attach ephemeral debugging tools to running containers
• Container logs: Use docker logs to inspect application output

The dev variant includes bash, apt, and standard utilities, but requires overriding the entrypoint since the default is still to run Alloy. This design ensures the dev variant can be used for both debugging (with entrypoint override) and testing (with default behavior).

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. To view if a package manager is available for an image variant, select the Tags tab for this repository. To view what packages are already installed in an image variant, select the Tags tab for this repository, and then select a tag.

   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 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 a nonroot user. Ensure that necessary files and directories are accessible to that user. You may need to copy files to different directories or change permissions so your application running as a nonroot user can access them.

To view the user for an image variant, select the Tags tab for this repository.

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.

To see if a shell is available in an image variant and which one, select the Tags tab for this repository.

Entry point

Docker Hardened Images may have different entry points than images such as Docker Official Images.

To view the Entrypoint or CMD defined for an image variant, select the Tags tab for this repository, select a tag, and then select the Specifications tab.