Kubernetes onboarding for the path to production

We provide private, instructor-led Kubernetes training to help application engineers learn how their code moves into a production environment.

New team members are familiar with application development, but they need to link the team's delivery tools with how Kubernetes works. A successful pipeline alone does not show if the right application version is ready to handle traffic.

At LearnKube, we guide learners through a typical change, from updating images and configurations to observing the workload. With support, learners practice explaining the release and learn how to ask for help when needed.

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Learning in practice

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.

Prepare a first supported application contribution

Get familiar with the delivery path by learning about image identity, configuration, and workload resources. This helps new engineers see where their application changes go.
Practice a supported release with help on Deployment state and probes. Learners will be able to explain the difference between delivery and when the application is actually ready.
Demonstrate an investigation through an unexpected release result, so engineers can identify their next action and the platform support needed.
Keep track of release explanations with notes and references, so future contributions can use the same reasoning.

Connect delivery-tool success to workload evidence

A delivery workflow changes a Deployment's Pod template. Readiness probes indicate whether a container is ready to accept traffic. New engineers need to trace image and configuration choices into the resulting replicas. A guided release makes that sequence clear. A changed result then asks learners to identify useful evidence before their next action or request for assistance.

I ask the new engineer to point to the version that actually serves the request. A successful pipeline is useful evidence, but it does not replace an explanation of the workload's state.
— Daniele Polencic, LearnKube founder and Kubernetes instructor

Role milestone	Required knowledge	Practice/check
Understand the delivery path	Images, configuration, and resources	Trace a representative change
Make a supported contribution	Pod templates and rollout behavior	Release a sample version
Explain the application result	Readiness and observed replicas	Identify the serving version
Repeat the reasoning later	Evidence and support boundaries	Annotate the release path

Your team is not alone in this onboarding challenge

BILL's internal platform work connects developer workflows from local setup to production with Kubernetes, Argo CD, and GitLab. That work explicitly includes new-engineer productivity.

For engineers getting ready to use this kind of delivery path, we suggest a four-day Kubernetes workshop. It links familiar application changes to how workloads behave, what checks are visible, and where platform support comes in.

A recommended four-day path to a supported contribution

This proposed agenda uses a typical application change. The course covers the Kubernetes part of the delivery process and helps learners explain results with less guidance as they progress.

Day 1

Trace an application version into the workload

We show how container images connect to Pods, Deployments, Services, and probes. Learners complete a supported release and compare the version they set with the replicas and application responses they see.

Hands-on exercises

Follow an image change into a Deployment and identify the resulting replicas.
Explain an unready release and distinguish pipeline success from application readiness.

Day 2

Understand the configuration behind the release

We use Helm and compare it to Kustomize to link environment inputs to resources. The course explains how the API, controllers, and kubelet turn these resources into workload behavior.

Hands-on exercises

Trace a configuration value from the supplied source into the application's environment.
Repeat a change with fewer prompts and explain which component acts on it.

Day 3

Investigate the first unexpected request path

We trace DNS, Services, ingress, policy, and scheduling. Service mesh discussion adds traffic behavior where relevant to the team's environment. Learners distinguish application observations from platform-owned controls.

Hands-on exercises

Diagnose a failed request and explain which part of the path the evidence rules out.
Prepare a request for platform assistance with the resource, observation, and remaining questions.

Day 4

Demonstrate a contribution with its dependencies

We link state, credentials, resource metrics, autoscaling, authentication, and RBAC to the release process. Learners explain a combined task and figure out what checks are needed before a workplace review.

Hands-on exercises

Demonstrate a configuration or version change with explicit data and access requirements.
Record the release evidence, support boundary, and references for the next supported contribution.

Your engineers' experience, delivery workflow, and first application responsibilities can shape the agenda. Get in touch to tailor the workshop to your team's path to production.

Ask the learner to account for the application response

If a new engineer only mentions a successful pipeline, the instructor can help compare the version set with the service's response. The learner can then find the workload evidence needed to explain any differences.

Zach described what he liked most about his course at L3Harris:

The split between lectures and lab. And the VM had everything setup for us.
— Zach, DevOps Engineer at L3Harris.

Start with the first change a new engineer needs to make

Tell us what your new engineers already know, how your team delivers applications, and which contribution they need to make first. We will recommend a technical starting point, guided exercises, and useful checks of understanding.

Discuss your team's training