From RHEL-hosted applications to Kubernetes workloads

Private, instructor-led training for Linux systems engineers who need to containerize applications and operate them on Kubernetes.

Your engineers already know how to manage processes, hosts, networks, and storage. Kubernetes adds decisions about image contents, application health, and where workloads run. Linux administration remains part of the platform.

LearnKube connects familiar host-level tasks to Kubernetes through a sample Linux application. Your team will package, deploy, and diagnose it across application and node boundaries.

Discuss your team's training

Hands-on learning and the skills engineers take back to work.

Preview: course-wide figures are not yet available.

  • Hands-on learning
    60%
    Of instruction time spent on labs and challenges.
  • Troubleshooting confidence
    86%
    Of respondents report greater confidence diagnosing Kubernetes problems.
  • Relevant to your work
    92%
    Of respondents say the course addressed their engineering responsibilities.
  • Skills put into practice
    95%
    Of respondents applied their new skills at work within 90 days.

Extend your Linux skills to workload operations

  • Deploy a Linux application by separating its image, configuration, and persistent data, so Kubernetes can replace its Pods consistently.
  • Preserve application availability by configuring probes and rollout controls, so traffic reaches healthy replicas during releases.
  • Locate operational failures by comparing application logs, Pod events, and node conditions, so engineers investigate the correct layer.
  • Define operating responsibilities by documenting workload recovery and host maintenance procedures, so application and infrastructure teams can coordinate changes.

From a managed host to a replaceable workload

On a Linux host, administrators install packages, configure services, and manage processes and files. In Kubernetes, an image supplies the application runtime, while controllers maintain the requested workloads. Replacement Pods can run on different nodes. Configuration and persistent data therefore need an explicit lifecycle beyond the container.

I want a replacement Pod to work without manual repairs. Packages belong in the image, and required state needs durable storage. A repair made inside a running container can disappear when Kubernetes replaces it.

— Daniele Polencic, LearnKube founder and Kubernetes instructor

Current task or requirementNew concept or decisionPractice
Install application packagesContainer image contentsBuild a runtime image
Restart a host serviceProbes and Pod lifecycleDiagnose a restart loop
Store application filesPersistentVolumeClaims and mountsRecover data after replacement
Investigate a machinePod and node conditionsLocate the failure layer

Your team is not alone in this transition

Rampant Technologies has a strategic transition from RHEL-based systems toward Kubernetes-based containerization. Its environment includes an R&D lab connected to the enterprise and legacy application modernization across projects.

A transition like this requires engineers to preserve application dependencies while changing packaging, deployment, and recovery. For this situation, we recommend a workshop focused on images, workload lifecycles, and diagnosis across hosts and containers.

A recommended four-day workshop for Linux teams

This proposed agenda starts with your team's Linux experience and focuses on the differences between application containers and cluster nodes.

Day 1

We explain container isolation, images, volumes, and runtime configuration. You will connect those concepts to Pods, Deployments, Services, probes, and rolling updates.

Hands-on exercises

  • Build an image for a sample Linux service and deploy it.
  • Introduce a startup error, inspect the logs, and restore a healthy release.

Day 2

You will use Helm and Kustomize to manage repeatable configuration. We explain the control plane, etcd, and kubelet, including what happens when a node becomes unavailable.

Hands-on exercises

  • Package application configuration for two environments.
  • Simulate a node failure and compare node conditions with Pod events.

Day 3

We show how familiar ports and interfaces relate to Pod networking, Services, DNS, and ingress. You will discuss network policies, service meshes, and workload placement across nodes.

Hands-on exercises

  • Trace a request from the cluster entrance to the application process.
  • Diagnose a failed connection between workloads on different nodes.

Day 4

You will compare local files with persistent storage and review secrets, autoscaling, and RBAC. We explain how container permissions and resource limits affect your application.

Hands-on exercises

  • Mount persistent storage and confirm that data survives Pod replacement.
  • Generate load and observe the relationship between resource requests and autoscaling.

Your Linux applications, storage dependencies, and host-support responsibilities can shape the agenda. Get in touch to tailor the workshop to your Linux-to-Kubernetes workload transition.

Connect symptoms to the right layer

If an engineer tries to fix a container by installing a missing package inside it, the instructor can show what happens after replacement. The team then moves that dependency into the image and discusses which files need persistent storage.

I really enjoyed the 'challenges' at the end of the first 3 lessons as they really had the concepts start to make sense and allow me to follow and learn at my own pace.

— James, Systems Specialist at Sabel Systems.

Bring your application and host requirements

Tell us which Linux applications you operate, what their Kubernetes environment will provide, and who owns the hosts and workloads. We will recommend a course focus and practical exercises.

Discuss your team's training