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/k8ssandra-medusa:<tag>
• Mirrored image: <your-namespace>/dhi-k8ssandra-medusa:<tag>

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

About K8ssandra Medusa

K8ssandra Medusa is the backup and restore component of the K8ssandra project. It is not intended to be run as a standalone Docker container: the image runs a Medusa gRPC server that the k8ssandra-operator deploys as a sidecar in each Cassandra pod, plus a medusa-restore init container that handles in-place restores at pod startup. Backups, restores, and verifications are driven through K8ssandra custom resources (MedusaBackupJob, MedusaBackupSchedule, MedusaRestoreJob).

Configuring Medusa therefore happens in two places:

• The medusa block of a K8ssandraCluster resource (or the cassandra.medusa Helm values for the k8ssandra-operator chart), which selects the Medusa container image, storage backend, and credentials.
• A MedusaBackupJob (or schedule) resource that asks the operator to take a backup of a specific CassandraDatacenter.

The Docker Hardened image is a drop-in replacement for k8ssandra/medusa. You enable it by setting the spec.medusa.containerImage fields on a K8ssandraCluster to point at this image.

Prerequisites

Before using this image, you need:

• A Kubernetes cluster (version 1.21 or later)
• kubectl configured to access your cluster
• k8ssandra-operator and cass-operator already installed in the cluster
• Object storage Medusa can write to (S3, GCS, Azure, or an S3-compatible endpoint such as MinIO)
• A Kubernetes Secret containing credentials for that storage backend

For installing the operator with Docker Hardened Images, see the k8ssandra-operator and k8ssandra-cass-operator guides in this catalog.

Deploy K8ssandra with Medusa enabled

Create the storage credentials secret

Medusa expects a Kubernetes Secret whose credentials key contains the AWS-style INI credentials Medusa hands to its storage driver. The exact contents depend on the backend; this is the format expected by s3 and s3_compatible:

apiVersion: v1
kind: Secret
metadata:
  name: medusa-bucket-key
  namespace: k8ssandra
type: Opaque
stringData:
  credentials: |
    [default]
    aws_access_key_id = <YOUR_ACCESS_KEY>
    aws_secret_access_key = <YOUR_SECRET_KEY>

For other backends (google_storage, azure_blobs, etc.), see the Medusa storage configuration docs⁠.

Create a K8ssandraCluster with the Docker Hardened Medusa image

Set spec.medusa.containerImage to the DHI Medusa image. The K8ssandra containerImage schema treats repository as the namespace inside the registry and name as the image name; for the DHI public image the namespace is empty, so only registry, name, and tag are needed. The example below uses an S3-compatible bucket (e.g. MinIO); substitute storageProvider, host, and port for your real backend.

apiVersion: k8ssandra.io/v1alpha1
kind: K8ssandraCluster
metadata:
  name: demo
  namespace: k8ssandra
spec:
  cassandra:
    serverVersion: "4.0.17"
    datacenters:
      - metadata:
          name: dc1
        size: 3
    storageConfig:
      cassandraDataVolumeClaimSpec:
        storageClassName: standard
        accessModes:
          - ReadWriteOnce
        resources:
          requests:
            storage: 10Gi
  medusa:
    containerImage:
      registry: dhi.io
      name: k8ssandra-medusa
      tag: <tag>
    storageProperties:
      storageProvider: s3_compatible
      storageSecretRef:
        name: medusa-bucket-key
      bucketName: cassandra-backups
      prefix: demo
      host: minio.k8ssandra.svc.cluster.local
      port: 9000
      secure: false
    serviceProperties:
      grpcPort: 50051

If you mirror the image to your own registry under a namespace (<your-registry>/<your-namespace>/dhi-k8ssandra-medusa:<tag>), set all four fields:

medusa:
  containerImage:
    registry: <your-registry>
    repository: <your-namespace>
    name: dhi-k8ssandra-medusa
    tag: <tag>

Apply the manifest:

$ kubectl apply -f k8ssandracluster.yaml

The operator creates a Cassandra StatefulSet whose pods include a medusa sidecar container running this image and a medusa-restore init container. You can confirm the sidecar is in place with:

$ kubectl -n k8ssandra get pod demo-dc1-default-sts-0 \
    -o jsonpath='{.spec.containers[*].name}'
cassandra medusa server-system-logger

Override the default Medusa image at the chart level

The k8ssandra-operator Helm chart also lets you set a cluster-wide default Medusa image under global.imageConfig.images.medusa, which applies to every K8ssandraCluster that doesn't override spec.medusa.containerImage:

global:
  imageConfig:
    images:
      medusa:
        registry: dhi.io
        name: k8ssandra-medusa
        tag: <tag>

The Medusa image is selected per K8ssandraCluster or via this chart-wide default; setting the chart's top-level image.registry / image.repository only affects the operator container itself, not the Medusa sidecar.

Trigger a backup with MedusaBackupJob

Once Medusa is enabled on a cluster, request a backup by creating a MedusaBackupJob. The operator will fan out the backup across all nodes in the target CassandraDatacenter.

apiVersion: medusa.k8ssandra.io/v1alpha1
kind: MedusaBackupJob
metadata:
  name: backup-1
  namespace: k8ssandra
spec:
  cassandraDatacenter: dc1
  backupType: differential

Apply and watch the job:

$ kubectl apply -f medusabackupjob.yaml
$ kubectl -n k8ssandra get medusabackupjob backup-1 -w

The backup is complete when status.finishTime is set; any per-node failures show up in status.failed.

For scheduled backups, point-in-time restores, and the full set of fields, see the upstream Medusa backup and restore guide⁠.

Common K8ssandra Medusa use cases

For end-to-end examples and feature-specific manifests, refer to the upstream K8ssandra documentation:

• Backup and restore overview⁠
• Medusa component reference⁠
• MedusaBackupSchedule reference⁠
• MedusaRestoreJob reference⁠

Use the image override patterns in this guide when you want to substitute the upstream Medusa image with the Docker Hardened Image.

What's intentionally omitted compared to upstream

The DHI variant of k8ssandra-medusa is a drop-in replacement for the upstream k8ssandra/medusa image for the operator-driven backup/restore flow, but it intentionally omits a few things that ship in the upstream Dockerfile:

• gcloud CLI / Google Cloud SDK. Upstream installs the full Google Cloud SDK at /usr/local/gcloud. Medusa's GCS storage backend uses the google-cloud-storage Python library that ships in the bundled venv, so backups and restores against GCS work identically without the CLI. If you need ad-hoc gcloud access for debugging, run it in a separate container (for example, the dhi/google-cloud-cli image via kubectl debug or as a one-off kubectl run) rather than expecting it inside the Medusa sidecar.
• aws CLI. Upstream apt-installs awscli. Medusa's S3 and S3-compatible backends use boto3 from the bundled venv, so backups and restores work without the CLI. Use a separate container for ad-hoc aws s3 debugging.
• Debian/Ubuntu build chain (debhelper, dh-virtualenv, devscripts, equivs, build-essential, software-properties-common, gnupg). These are upstream build-time tools that were never required at runtime; they are kept out of the runtime image to reduce surface area. The 0-dev and 0-fips-dev variants include a package manager and a shell if you need a writable build environment.

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.

To view the image variants and get more information about them, select the Tags tab for this repository, and then select 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.

For Medusa specifically, you can also inspect the running sidecar with:

$ kubectl -n k8ssandra logs <cassandra-pod> -c medusa
$ kubectl -n k8ssandra logs <cassandra-pod> -c medusa-restore   # init container

Permissions

The Medusa sidecar runs as the cassandra user (UID 999) so it can share the Cassandra data volume with the Cassandra container. If you mount a Secret or ConfigMap into the sidecar, make sure its defaultMode allows reads by UID 999.

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. The Medusa gRPC server listens on 50051 by default, which is well above the privileged range.

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. The Medusa entry point is /home/cassandra/docker-entrypoint.sh, the same path as the upstream image. Use docker inspect to confirm if you override it.

FIPS

A FIPS-compliant variant of this image is available with the -fips suffix (e.g., k8ssandra-medusa:0-fips).

The FIPS variant is built with a FIPS-enabled Go toolchain (used by the bundled grpc_health_probe binary).

Use the FIPS variant when deploying in environments that require FIPS 140-2 compliance, such as US federal government workloads or FedRAMP-authorized systems.