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Kubernetes chaos engineering at scale: Krkn Operator Developer Preview in Red Hat Advanced Cluster Management

August 17, 2026
Tullio Sebastiani Naga Ravi Chaitanya Elluri
Related topics:
KubernetesPlatform engineeringDevOps
Related products:
Red Hat Advanced Cluster Management for KubernetesRed Hat OpenShift

    With the release of the developer preview of the Krkn Operator in Red Hat Advanced Cluster Management for Kubernetes, platform teams can now run Kubernetes-native chaos engineering directly from their management hub. The operator integrates Krkn, an open source Cloud Native Computing Foundation (CNCF) project, to bring multicluster chaos testing and resilience validation directly to Red Hat Advanced Cluster Management.

    Built on Kraken Kubernetes chaos engineering principles, the Krkn Operator helps teams catch failure modes and verify recovery times before bugs hit production. The operator aligns closely with Open Cluster Management (OCM), the upstream open source project that powers multicluster management across hybrid environments.

    Users can run individual experiments or use Chaos Studio to visually build reusable multicluster chaos testing workflows that combine multiple failure scenarios sequentially or in parallel. These workflows measure service and platform behavior, generate a resiliency score, and establish a baseline that users can compare after upgrades, configuration changes, releases, or tuning activities.

    From chaos experiments to measurable resilience

    A single experiment shows how a system responds to a pod, node, network, storage, or service failure. However, real environments might face multiple disruptions, making consistent validation across clusters difficult.

    The Krkn Operator centralizes target clusters, access controls, experiment execution, results, and reusable workflows. Platform teams can run identical tests across any cluster managed by Red Hat Advanced Cluster Management or OCM, making chaos testing repeatable and scalable.

    Instead of manually firing off isolated scripts on individual clusters, platform engineers can now run and track chaos experiments across hundreds of managed clusters directly from a single hub. Platform teams can systematically validate resilience policies and application recovery their entire fleet.

    Design reusable workflows with Chaos Studio

    Chaos Studio provides an interactive visual editor for creating complex resilience workflows. Each node represents a Krkn scenario, and the connections determine whether scenarios run sequentially or in parallel.

    For example, users can combine an application pod disruption, network latency, and resource pressure into 1 workflow to validate how a complete service or platform behaves under realistic failure conditions.

    How Chaos Studio calculates resiliency scores

    Chaos Studio can also evaluate Prometheus metrics such as availability, latency, error rate, throughput, and recovery time. These results contribute to a resiliency score, providing a measurable outcome instead of only a pass-or-fail result.

    Users can run a workflow against a known-good environment and establish the score as a baseline. They can then rerun the same workflow after an OpenShift or application upgrade, configuration change, infrastructure update, or performance-tuning activity.

    If the score remains stable or improves, users gain additional confidence in the change. If it drops, the workflow results and metrics can help identify what degraded before the change reaches production.

    Once you establish a baseline score on a known-good cluster, run the same workflow in your CI pipeline after every OpenShift update.

    Quick start: Install the Krkn Operator with Red Hat Advanced Cluster Management integration

    Start in a non-production environment. Follow the installation documentation and replace <VERSION> with the current release:

    helm install krkn-operator \
      oci://quay.io/krkn-chaos/charts/krkn-operator \
      --version <VERSION> \
      --namespace krkn-operator-system \
      --create-namespace \
      --set console.route.enabled=true \
      --set acm.enabled=true

    Verify the components are running:

    oc get pods -n krkn-operator-system

    Confirm Red Hat Advanced Cluster Management- or OCM-managed clusters are available:

    oc get managedclusters

    For an initial evaluation, access the console through port forwarding:

    oc port-forward \
      -n krkn-operator-system \
      svc/krkn-operator-console \
      3000:3000

    Then open:

    http://localhost:3000

    For longer-running environments, expose the console through an OpenShift route or another supported access method described in the installation guide.

    Run your 1st multicluster chaos experiment

    From the Krkn Operator console, select 1 or more target clusters and choose a scenario from the available registry. Configure the required parameters, attach any supporting files, review the settings, and start the experiment.

    Begin with a clear hypothesis in a non-production environment:

    If an application pod is disrupted, OpenShift should restore the expected replica count and service availability within the defined recovery window.

    Choose a pod disruption scenario, configure the target namespace and label selector, and monitor the execution from the Jobs page.

    The goal is not to inject failure. Validate whether the application recovered within the expected time, whether users experienced errors, and whether monitoring and operational processes detected the disruption.

    After validating the first scenario, combine it with network, node, service, or resource-pressure experiments in Chaos Studio to build a broader resilience workflow.

    Scale validation across Red Hat Advanced Cluster Management and OCM

    Red Hat Advanced Cluster Management and OCM integration automatically discovers managed clusters and adds them to the same target pool as manually registered clusters.

    Users can run the same workflow across development, staging, regional, or differently configured environments. Comparing results and resiliency scores can help identify configuration drift, environment-specific weaknesses, and behavioral changes after platform updates.

    Help shape the future of the Krkn Operator

    Because this is a developer preview, your feedback directly shapes the project roadmap.

    We encourage early adopters to complete the Krkn Operator feedback form and share:

    • Adoption stories and lessons learned
    • Real-world use cases and resilience challenges
    • Missing scenarios and integration needs
    • Installation or documentation gaps
    • Feature and enablement requests

    The project team reviews every submission to help guide future priorities. You can also submit bugs and enhancement requests through the Krkn Operator GitHub repository.

    Get involved

    Ready to stress-test your infrastructure? Check out the Krkn Operator documentation to install the developer preview and build your first workflow in Chaos Studio.

    To get involved with the community:

    • Submit feedback through the feedback form
    • Report bugs or contribute on GitHub
    • Join community office hours or request a demo
    • Connect with users and maintainers in the #krkn channel on Kubernetes Slack

    Give the preview a spin, create your first workflow, and join us in the #krkn channel on Kubernetes Slack to share what you find.

    Related Posts

    • Integrate Red Hat Advanced Cluster Management with Argo CD

    • Type what you want to break: AI-assisted chaos engineering with Krkn

    • Krkn-AI: A feedback-driven approach to chaos engineering

    • Unleash controlled chaos with krknctl

    • Enhancing system resilience with Krkn chaos dashboard

    • Rebalance hub workloads with managed cluster migration

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