Delivery: Online Self-Paced
Who It's For: Developers looking to learn how to deploy, configure, and test their containerized applications on a multi-node Kubernetes cluster.
Prerequisites: To get the most out of this course, you should have basic Linux command line and file editing skills and be familiar with using a programming language (such as Python, Node.js, Go). A knowledge of Cloud Native application concepts and architectures (such as is taught in our free Introduction to Kubernetes edX MOOC (https://training.linuxfoundation.org/linux-courses/system-administration-training/introduction-to-kubernetes)) is helpful for this course.
Materials: 1 year online access to all course content and labs.
This course is:
- 100% online and self-paced
- Loaded with labs (and solutions) designed by our experts
- Designed to help you start designing/architecting application orchestration solutions and know how they will work with Docker images.
About This Course
This course will teach you how to containerize, host, deploy, and configure an application in a multi-node cluster. Starting with a simple Python script, you will define application resources and use core primitives to build, monitors and troubleshoot scalable applications in Kubernetes. Working with network plugins, security and cloud storage, you will be exposed to many of the features needed to deploy an application in a production environment.
In this course you'll learn how to:
- Containerize and deploy a new Python script
- Configure the deployment with ConfigMaps, Secrets and SecurityContexts
- Understand multi-container pod design
- Configure probes for pod health
- Update and roll back an application
- Implement services and Network Policies
- Use PersistentVolumeClaims for state persistence
- And more
This course is designed to be vendor- and distribution-neutral, so you will be able to apply these concepts universally.
You will have access to the course for a full year from the date of purchase (or availability, for preorders), regardless of how quickly you complete the course. You can expect the course to take 30-35 hours to complete (although the course is self-paced, so you can move as quickly or as slowly as you like).