kube-state-metrics

The image exposes two TCP ports: 8080 for the cluster-state metrics scrape endpoint, and 8081 for kube-state-metrics' own self-metrics (telemetry about the exporter itself). The image is designed to run inside a Kubernetes cluster, where it authenticates to the API server using a ServiceAccount token mounted into the pod.

For the following examples, replace <tag> with the image variant you want to run. To confirm the correct namespace and repository name of the mirrored repository, select View in repository.

Start a kube-state-metrics instance

The image's entrypoint is kube-state-metrics --port=8080 --telemetry-port=8081. When you run the container without additional arguments, it starts the metrics server with defaults. Outside a Kubernetes cluster, the binary fails fast with a configuration error because it has no API server to connect to:

$ docker run --rm registry.ghost-prod.alphabravo.io/ghost-base/kube-state-metrics:<tag>

This is by design — kube-state-metrics is intended to run as a pod inside the cluster it monitors. See Deploy to Kubernetes below for the recommended installation pattern.

Display version information

To check the binary version, override the entrypoint to drop the baked-in --port flags. The version subcommand does not accept the global flags, so running it without --entrypoint fails:

$ docker run --rm --entrypoint kube-state-metrics registry.ghost-prod.alphabravo.io/ghost-base/kube-state-metrics:<tag> version
kube-state-metrics, version 2.17.0 (branch: dhi, ...)

Common kube-state-metrics use cases

Deploy to Kubernetes

kube-state-metrics is typically installed via the upstream prometheus-community/kube-state-metrics Helm chart. The chart handles ServiceAccount creation, RBAC permissions, the Deployment, and a Service for scraping. To use the Docker Hardened Image, override the chart's image fields to point at registry.ghost-prod.alphabravo.io.

Step 1: Create an image pull secret. The DHI registry requires authentication for cluster pulls:

$ kubectl create secret docker-registry helm-pull-secret \
    --docker-server=registry.ghost-prod.alphabravo.io \
    --docker-username=<Docker username> \
    --docker-password=<Docker token> \
    --docker-email=<Docker email>

Use a Docker Hub personal access token (not your account password). For more detail, see DHI authentication in Kubernetes.

Step 2: Add the upstream Helm repository:

$ helm repo add prometheus-community https://prometheus-community.github.io/helm-charts
$ helm repo update prometheus-community

Step 3: Install the chart with DHI image overrides:

$ helm install ksm prometheus-community/kube-state-metrics \
    --set image.registry=registry.ghost-prod.alphabravo.io \
    --set image.repository=kube-state-metrics \
    --set image.tag=<tag> \
    --set "imagePullSecrets[0].name=helm-pull-secret"

Note that DHI tags omit the v prefix that the upstream chart uses by default (for example, 2.17 instead of v2.17.0). Always override image.tag explicitly when using the upstream chart.

Step 4: Verify the deployment:

$ kubectl get pod -l app.kubernetes.io/instance=ksm
NAME                                      READY   STATUS    RESTARTS   AGE
ksm-kube-state-metrics-5b56fd95d8-8cqmh   1/1     Running   0          21s

Confirm the running pod is the digest-pinned DHI image:

$ kubectl get pod -l app.kubernetes.io/instance=ksm \
    -o jsonpath='{.items[0].spec.containers[0].image}'
registry.ghost-prod.alphabravo.io/ghost-base/kube-state-metrics:<tag>

To uninstall:

$ helm uninstall ksm

Scrape metrics with Prometheus

The chart creates a Service of type ClusterIP named ksm-kube-state-metrics exposing port 8080. Prometheus can scrape this service directly:

scrape_configs:
  - job_name: 'kube-state-metrics'
    static_configs:
      - targets: ['ksm-kube-state-metrics.default.svc.cluster.local:8080']

If you use the Prometheus Operator, the chart can also create a ServiceMonitor resource by setting prometheus.monitor.enabled=true during install. See the chart's values reference for full options:

$ helm show values prometheus-community/kube-state-metrics

Inspect available metrics

To preview the metrics output without setting up a full Prometheus stack, port-forward to the kube-state-metrics pod:

$ POD=$(kubectl get pod -l app.kubernetes.io/instance=ksm \
    -o jsonpath='{.items[0].metadata.name}')
$ kubectl port-forward $POD 8080:8080

Then in another terminal:

$ curl http://localhost:8080/metrics | grep ^kube_pod_status_phase | head

Common metric families produced by kube-state-metrics include kube_pod_*, kube_deployment_*, kube_node_*, kube_service_*, kube_configmap_*, kube_secret_*, kube_persistentvolume_*, and kube_job_*. See the upstream documentation for the full list: https://github.com/kubernetes/kube-state-metrics/blob/main/docs/README.md#exposed-metrics

Non-hardened images vs Ghost hardened images

Key differences

Why no shell or package manager?

Ghost 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 image contains only the kube-state-metrics binary and its required libraries — no shell, no coreutils, no package manager, no editors. Common debugging methods for applications built with Ghost hardened images include:

• Docker Debug to attach to containers
• Docker's Image Mount feature to mount debugging tools

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 example:

$ docker debug ksm-pod

For operational visibility without a shell, kube-state-metrics' own telemetry endpoint on port 8081 (/metrics) exposes self-metrics about scrape duration, request counts, and resource usage of the exporter itself.

Image variants

Ghost 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 (UID 65532)
• Do not include a shell or a package manager
• Contain only the minimal set of libraries needed to run the app

Build-time variants 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 (bash and /bin/sh) and a package manager (apt)
• Are used to build or compile applications

The kube-state-metrics image is published in the following variant combinations:

DHI tags use the upstream version number directly with no v prefix (for example, 2.17, not v2.17.0). Tags also include rolling major-version aliases — 2 always points to the latest 2.x release, and 2.17 to the latest 2.17.x patch.

To view all published tags and get more information about each variant, select the Tags tab for this repository.

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.

The kube-state-metrics FIPS variants are available through DHI Select and DHI Enterprise subscriptions only. To use them, mirror the repository into your own namespace and pull from your mirror. See Mirror a DHI repository.

FIPS variants of the kube-state-metrics image are drop-in replacements for the standard runtime variant — same entrypoint, same ports, same nonroot UID 65532. kube-state-metrics does not require any FIPS-specific configuration flags. TLS operations for the metrics server (when configured via --tls-config and --web.tls-cert-file) automatically use the FIPS-validated cryptographic providers.

What changes in FIPS mode

Compared to the standard runtime variant:

• Cryptographic modules: OpenSSL FIPS Provider is used for TLS operations
• Available algorithms: only FIPS 140-approved algorithms are available; non-approved algorithms (such as MD5) fail at runtime
• Image size: slightly larger due to the FIPS provider module
• Compliance labels: carries com.docker.dhi.compliance=fips,stig,cis
• Everything else: identical. Same kube-state-metrics version, same flags, same metrics output, same nonroot UID 65532

FIPS variants are appropriate for regulated environments such as FedRAMP, government, healthcare, financial services, and defense deployments.

Migrate to a Ghost hardened image

To migrate your kube-state-metrics deployment to a Ghost hardened image, update the image reference in your Helm values, Dockerfile, or Kubernetes manifests. The following table lists the most common changes:

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.

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.

   Ghost hardened images contain minimal packages in order to reduce the potential attack surface. 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.

Troubleshoot 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 Ghost 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 kube-state-metrics specifically, the most common operational issues are RBAC and authentication errors visible in the pod's stdout logs. Use kubectl logs <pod> to inspect them. The /metrics endpoint on port 8081 also exposes telemetry about the exporter itself, which is useful for diagnosing scrape failures and resource pressure.

Permissions

By default image variants intended for runtime, run as the nonroot user (UID 65532). The kube-state-metrics binary does not write to disk and does not require host filesystem mounts, so permission issues are typically RBAC-related rather than UID-related: the pod's ServiceAccount must have list and watch permissions on the resource types being exposed. The upstream Helm chart configures this RBAC automatically.

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 default kube-state-metrics ports (8080 and 8081) are above 1024 and are unaffected. If you override --port or --telemetry-port, use values above 1024.

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

The hardened image's entrypoint is kube-state-metrics --port=8080 --telemetry-port=8081. The --port and --telemetry-port flags are baked into the entrypoint and apply only to the metrics server, not to subcommands such as version or help. To run a subcommand, override the entrypoint:

$ docker run --rm --entrypoint kube-state-metrics registry.ghost-prod.alphabravo.io/ghost-base/kube-state-metrics:<tag> version
$ docker run --rm --entrypoint kube-state-metrics registry.ghost-prod.alphabravo.io/ghost-base/kube-state-metrics:<tag> help

Use docker inspect to view the exact entrypoint and command for a specific tag.