Kubernetes production training for application and platform engineers

Private, instructor-led training for engineers who already deploy and operate Kubernetes workloads but need a connected explanation of the platform beneath their commands.

Your team can apply manifests and inspect Pods. Successful commands do not explain whether controllers, traffic, capacity, and application state agree, especially during failure or change.

LearnKube follows a representative service from declared configuration to observed behavior. Engineers investigate discrepancies, justify a correction, and record the evidence that supports it.

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.

Explain the platform before choosing an action

  • Explain workload behavior through controllers, node components, and resource relationships, so the team can predict what happens after a change.
  • Diagnose unexpected results using events, status, logs, and request observations, so engineers distinguish application symptoms from platform causes.
  • Validate a correction under a repeatable failure or load condition, so the team can judge whether the behavior improved without hiding another problem.
  • Make investigations repeatable through a documented sequence of questions and evidence, so another engineer can apply the same reasoning.

An accepted manifest starts a control process

The team already changes Kubernetes objects, but an accepted request only records desired state. Controllers and cluster components must coordinate work before an application behaves as intended. Comparing resource status with traffic, placement, and data access helps engineers identify the incomplete step instead of assuming that the last command completed the entire operation.

I ask which observation would prove the engineer's explanation wrong. If every symptom leads to the same restart, the team has an action it recognizes but not yet a model that guides diagnosis.

— Daniele Polencic, LearnKube founder and Kubernetes instructor

Production questionMechanism to understandPractice
Why is state different?Desired and observed stateTrace a controller decision
Why is traffic missing?Readiness and endpoint selectionCompare requests and endpoints
Why is work waiting?Placement and resource requirementsInspect scheduler evidence
Did the correction help?Application success conditionsRepeat the original observation

Case Study: Coinbase

Coinbase engineers already used Kubernetes and wanted deeper understanding of the existing platform. LearnKube delivered a private Advanced Kubernetes course with explanations, architecture, and practical work.

Asked what he valued most, Angelo highlighted the learning format:

Both content and format. Challenges, quiz and labs.

— Angelo, Engineer at Coinbase.

A proposed four-day workshop on operating mechanisms

We shorten familiar setup tasks and follow one service through releases, infrastructure behavior, networking, and state. Each investigation ends with an explanation supported by observations.

Day 1

Explain the relationship between Pods, controllers, probes, and rollout status. Compare declared resources with actual application responses before choosing a correction.

Hands-on exercises

  • Investigate a release whose objects exist but whose replicas are not ready.
  • State a hypothesis and collect evidence that supports or rejects it.

Day 2

Connect Helm and Kustomize output to resources managed by the control plane and kubelet. Investigate what continues automatically after a workload or node interruption.

Hands-on exercises

  • Compare rendered configuration with the live workload and its owning controller.
  • Trace replacement behavior and identify the component responsible for each step.

Day 3

Follow DNS, Services, ingress, policy, and node selection through the sample application. Distinguish the requested configuration from the data path that actually serves traffic.

Hands-on exercises

  • Locate a request failure using endpoint and network observations.
  • Explain a Pending Pod using its constraints and available capacity.

Day 4

Connect storage, credentials, autoscaling metrics, authentication, and RBAC to application behavior. Combine observations into a reusable investigation rather than a list of commands.

Hands-on exercises

  • Diagnose a state or permission dependency that prevents recovery.
  • Repeat an investigation from another engineer's written reasoning and evidence.

Your current stack, unexplained behavior, and operating responsibilities can shape the agenda. Get in touch to tailor the workshop to your team's work.

Turn a familiar command into a testable explanation

When an engineer proposes a restart, the instructor can ask which mechanism the restart is expected to change. A controlled example then distinguishes a useful correction from an action that merely removes visible evidence.

Start with what the team cannot yet explain

Tell us what your team runs, which behavior it cannot confidently explain or change, and which components it owns. We will recommend a course focus and representative investigations.

Discuss your team's training