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Helm Charts for Kubernetes

Training & Course

Intensive introduction to managing Helm Charts on Kubernetes.

Helm is the de-facto standard for packaging and deploying applications on Kubernetes. This course provides a comprehensive introduction to Helm Charts on the Kubernetes platform. You will understand the basic principles and features of Helm, write your own charts and learn how to integrate Helm into CI/CD pipelines.

Course for your team.

We are happy to conduct tailored courses for your team - on-site, remotely or in our course rooms.

Request In-House Course

Caleb Woodbine

Content:

Together with the trainer, you will work on the following topics:

- Overview of Helm

- Kubernetes Refresh

- Install and upgrade simple charts

- Custom Variable Files

- Write a minimal chart

- Pull and push from chart museums

- Scaffold charts

- Build on dependencies

- Helm hooks and tests

- Helm templating features

- Helm and CI & CD (with GitLab)

- Demo ArgoCD and Helm

- Overview of advanced features

You will not only get to know these concepts, but also implement them in practice.

Disclaimer: The actual course content may vary from the above, depending on the trainer, implementation, duration and constellation of participants.

Whether we call it training, course, workshop or seminar, we want to pick up participants at their point and equip them with the necessary practical knowledge so that they can apply the technology directly after the training and deepen it independently.

Goal:

After this course, you will be able to efficiently manage and create Helm Charts and integrate Helm into CI/CD processes.

Form:

The course is well structured and consists of theoretical explanations and practical exercises. You will be accompanied by an experienced trainer who can answer questions related to Helm Charts and Kubernetes.

Target Audience:

This course is aimed at DevOps engineers, sysadmins, and developers who want to simplify the management of applications on Kubernetes and incorporate Helm Charts into their work.

Requirements:

Basic understanding in the use of the command line and Kubernetes.

Preparation:

Every participant will receive a questionnaire and a preparation checklist after registration. We provide a comprehensive laboratory environment for each participant, so that all participants can directly implement their own experiments and even complex scenarios.