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/aws-mountpoint-s3-csi-driver:<tag>
• Mirrored image: <your-namespace>/dhi-aws-mountpoint-s3-csi-driver:<tag>

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

What's included in this image

This Docker Hardened AWS Mountpoint S3 CSI Driver image includes:

• /usr/bin/aws-s3-csi-driver - Main CSI driver (node plugin)
• /usr/bin/aws-s3-csi-controller - Controller component for managing Mountpoint Pods
• /usr/bin/aws-s3-csi-mounter - Mounter binary that runs inside Mountpoint Pods
• /usr/bin/mount-s3 - Mountpoint for Amazon S3 binary (FUSE client)

Start an AWS Mountpoint S3 CSI Driver image

The AWS Mountpoint for Amazon S3 CSI Driver enables Kubernetes applications to access S3 buckets through a file system interface. Unlike block storage CSI drivers, this driver mounts S3 buckets (object storage) as volumes using FUSE.

Basic usage

$ docker run --rm dhi.io/aws-mountpoint-s3-csi-driver:<tag> --version

Deployment in Kubernetes

The recommended way to deploy the AWS Mountpoint S3 CSI Driver is using the official Helm chart.

Prerequisites: Configure IAM Permissions

The driver requires IAM permissions to access S3 buckets. Configure IAM Roles for Service Accounts (IRSA) or EKS Pod Identities before deploying the driver.

For IRSA (IAM Roles for Service Accounts):

1. Create an IAM role with S3 permissions. See the Mountpoint S3 CSI Driver IAM setup guide⁠ for the required policy.

2. Note the IAM role ARN - you'll need it during Helm installation.

Deploy with Helm Chart

If you've already installed the add-on:

eksctl delete addon --name aws-mountpoint-s3-csi-driver --cluster <cluster-name>
# or via AWS Console: EKS → Add-ons → Delete

1. Add the Helm repository:

helm repo add aws-mountpoint-s3-csi-driver https://awslabs.github.io/mountpoint-s3-csi-driver
helm repo update

1. Install the driver with Docker Hardened Images:

helm install aws-mountpoint-s3-csi-driver aws-mountpoint-s3-csi-driver/aws-mountpoint-s3-csi-driver \
  --namespace kube-system \
  --set node.serviceAccount.annotations."eks\.amazonaws\.com/role-arn"="arn:aws:iam::ACCOUNT_ID:role/S3CSIDriverRole" \
  --set imagePullSecrets[0].name=dhi-secret \
  --set image.repository=dhi.io/aws-mountpoint-s3-csi-driver \
  --set image.tag=<tag>

1. Verify the deployment:

kubectl get pods -n kube-system -l app.kubernetes.io/name=aws-mountpoint-s3-csi-driver

Runtime Requirements

The AWS Mountpoint S3 CSI Driver has specific runtime requirements due to its FUSE-based architecture.

Controller Component

The controller component manages Mountpoint Pods and requires:

• IAM Permissions: Service account must have permissions to access S3 buckets.
• Cluster Access: Must communicate with the Kubernetes API server to create/manage Mountpoint Pods.

Node Component

The node component (DaemonSet) handles volume staging and requires:

• Privileged Mode: Required for FUSE mount operations.
• Host Path Access: Access to /var/lib/kubelet for pod volume mounts.

Mountpoint Pods (v2 Architecture)

In v2, the actual mount-s3 process runs in dedicated Mountpoint Pods (not on the host). This provides:

• Better isolation and security
• SELinux compatibility (ROSA support)
• Pod sharing for improved resource utilization

Common use cases

Mount an S3 Bucket (Static Provisioning)

The Mountpoint S3 CSI Driver supports static provisioning only - you must reference an existing S3 bucket.

1. Create a PersistentVolume:

apiVersion: v1
kind: PersistentVolume
metadata:
  name: s3-pv
spec:
  capacity:
    storage: 1200Gi # Ignored by S3, but required by Kubernetes
  accessModes:
    - ReadWriteMany
  csi:
    driver: s3.csi.aws.com
    volumeHandle: s3-csi-driver-volume
    volumeAttributes:
      bucketName: my-s3-bucket

1. Create a PersistentVolumeClaim:

apiVersion: v1
kind: PersistentVolumeClaim
metadata:
  name: s3-pvc
spec:
  accessModes:
    - ReadWriteMany
  storageClassName: "" # Empty for static provisioning
  resources:
    requests:
      storage: 1200Gi
  volumeName: s3-pv

1. Use in a Pod:

apiVersion: v1
kind: Pod
metadata:
  name: s3-app
spec:
  containers:
    - name: app
      image: busybox
      command: ["/bin/sh", "-c", "ls /data && sleep 3600"]
      volumeMounts:
        - name: s3-volume
          mountPath: /data
  volumes:
    - name: s3-volume
      persistentVolumeClaim:
        claimName: s3-pvc

Mount with Specific Prefix

Mount only a specific prefix (folder) from the bucket:

apiVersion: v1
kind: PersistentVolume
metadata:
  name: s3-prefix-pv
spec:
  capacity:
    storage: 1200Gi
  accessModes:
    - ReadWriteMany
  csi:
    driver: s3.csi.aws.com
    volumeHandle: s3-prefix-volume
    volumeAttributes:
      bucketName: my-s3-bucket
  mountOptions:
    - prefix=data/subfolder/

Read-Only Mount

For workloads that only need to read from S3:

apiVersion: v1
kind: PersistentVolume
metadata:
  name: s3-readonly-pv
spec:
  capacity:
    storage: 1200Gi
  accessModes:
    - ReadOnlyMany
  csi:
    driver: s3.csi.aws.com
    volumeHandle: s3-readonly-volume
    volumeAttributes:
      bucketName: my-s3-bucket
  mountOptions:
    - read-only

Non-hardened images vs. Docker Hardened Images

This Docker Hardened Image differs from the upstream image in the following ways:

• Base image: Uses Debian 13 instead of the AWS EKS distro minimal base (Amazon Linux 2), which eliminates several CVEs present in the upstream image's OpenSSL and curl packages.
• libfuse: Uses Debian's maintained libfuse2 package instead of the bundled 2018 version from Amazon Linux 2.
• Go runtime: Built with an updated Go toolchain that addresses known CVEs in the Go standard library.

Image 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

• 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.

FIPS compliance details

The FIPS variants provide FIPS-compliant cryptography for the CSI driver control plane with the following characteristics:

Compliance Summary

FIPS-Compliant Components:

• CSI Driver Control Plane: All Go-based CSI components (aws-s3-csi-driver, aws-s3-csi-controller, aws-s3-csi-mounter) use FIPS 140-3 validated cryptography
• Data Transfer Security: All S3 data transfers use TLS encryption to FIPS-compliant AWS endpoints
• Cryptographic Operations: Volume management, authentication, and control operations use FIPS-validated OpenSSL

Non-FIPS Component:

• mount-s3 Binary: The FUSE client uses AWS-LC (FIPS-validated library) but not built in FIPS mode

Component Details

FIPS implementation:

• Go binaries use GODEBUG=fips140=on with OpenSSL FIPS provider (3.1.2)
• OpenSSL FIPS module (3.5.5) provides FIPS 140-3 validated cryptography
• FIPS mode enforced at runtime via GOFIPS140=v1.0.0

Understanding mount-s3 FIPS Status

The mount-s3 binary uses AWS-LC (AWS LibCrypto) for cryptography through the AWS Common Runtime (CRT). AWS-LC itself has received FIPS 140-3, Level 1 certification⁠ (certificates #4631, #4759, #4816).

Why isn't mount-s3 built in FIPS mode?

The upstream mountpoint-s3 build explicitly disables the Go and Perl dependencies required for FIPS mode compilation to reduce build complexity and binary size. Enabling FIPS would require upstream changes to the mountpoint-s3-crt-sys build configuration.

What this means in practice:

• Control plane operations (volume creation, mounting, authentication) use FIPS-validated cryptography
• All S3 data transfers use TLS encryption to FIPS-compliant AWS endpoints
• AWS-LC library is the same FIPS-validated codebase used by AWS services
• mount-s3 binary uses AWS-LC but not compiled in FIPS mode

Regulatory Compliance Considerations

This image meets FIPS requirements for most regulated environments because:

1. Control plane is fully FIPS-compliant: All CSI driver operations (volume management, pod coordination, authentication) use FIPS 140-3 validated cryptography
2. Data in transit is protected: All S3 transfers use TLS to FIPS-compliant AWS endpoints
3. Cryptographic library is FIPS-validated: AWS-LC has NIST CMVP certification
4. Industry-standard approach: Similar to how many cloud services use FIPS-validated libraries

When full FIPS mode for mount-s3 would be required:

• Environments with strict requirements that ALL binaries must be built in FIPS mode
• Compliance frameworks that mandate FIPS mode compilation (not just FIPS-validated libraries)
• Organizations with policies requiring end-to-end FIPS mode enforcement

For environments requiring full FIPS compliance:

If your environment requires mount-s3 to be built in FIPS mode, consider:

1. Filing a feature request with the upstream project⁠ to add official FIPS build support
2. Contacting Docker support to discuss custom build options
3. Evaluating whether your compliance requirements are met by FIPS-compliant control plane and TLS-encrypted data transfers

Note: Most federal and regulated environments accept this configuration because the control plane uses FIPS-validated cryptography and all data transfers are encrypted with FIPS-compliant TLS to AWS endpoints.

To view the image variants a tag.

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.