Google Kubernetes Engine (GKE) Course Overview

Google Kubernetes Engine (GKE) Course Overview

The Google Kubernetes Engine (GKE) course is a comprehensive program designed to equip learners with the knowledge and skills required to deploy, manage, and scale containerized applications using Kubernetes on Google Cloud. It will help learners understand the fundamentals of containerization with Docker, including image creation, management, and orchestration.

Through the course, students will delve into the core concepts of Kubernetes, exploring its architecture, features, and the various components that constitute a Kubernetes cluster. They will gain hands-on experience in using Kubernetes resources and objects such as Pods, Deployments, and Services, and understand how to manage workloads and storage effectively.

The course also covers essential topics like environment variables, handling sensitive data with ConfigMap and Secrets, and implementing security best practices. By mastering these skills, learners will be well-prepared to design, secure, and maintain Kubernetes clusters, setting them up for success in the field of cloud-native technologies.

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  • Live Online Training (Duration : 32 Hours)
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  • Live Online Training (Duration : 32 Hours)
  • Per Participant

♱ Excluding VAT/GST

Classroom Training price is on request

You can request classroom training in any city on any date by Requesting More Information

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Course Prerequisites

Certainly, here are the minimum prerequisites for students interested in the Google Kubernetes Engine (GKE) course:

  • Basic understanding of software development or system administration
  • Familiarity with command-line tools and Linux operating system environments
  • Fundamental knowledge of cloud computing concepts
  • Some experience with using Docker for creating and managing containers is helpful but not strictly necessary
  • Basic awareness of web servers, networking, and internet-based applications

These prerequisites ensure that participants are equipped with the foundational skills needed to grasp the concepts taught in the GKE course effectively. However, it is important to note that the course is designed to accommodate a range of skill levels, and instructors will guide students through the complexities of Kubernetes from the ground up.

Target Audience for Google Kubernetes Engine (GKE)

Koenig Solutions' Google Kubernetes Engine course equips IT professionals with the skills to deploy, manage, and scale containerized applications using GKE.

  • DevOps Engineers
  • Cloud Engineers
  • Software Developers
  • System Administrators
  • IT Managers overseeing infrastructure
  • Site Reliability Engineers (SREs)
  • Technical Architects
  • Application Developers interested in containerization technologies
  • Cloud Solutions Architects
  • Security Specialists focusing on containerized environments
  • Data Engineers looking to implement workflows on Kubernetes
  • Technical Project Managers managing software development projects
  • IT Professionals seeking to learn about orchestration and cloud-native technologies

Learning Objectives - What you will Learn in this Google Kubernetes Engine (GKE)?

Introduction to the Course's Learning Outcomes:

The GKE course equips participants with comprehensive knowledge of containerization, Kubernetes architecture, deployment, and security, ensuring proficiency in managing applications on Google Kubernetes Engine.

Learning Objectives and Outcomes:

  • Understand the fundamentals of containerization and the role of Docker in creating and managing containers.
  • Install Docker and learn to build, store, and manage Docker images in both public and private registries.
  • Gain hands-on experience in persisting data using Docker volumes and applying Linux capabilities to containers.
  • Comprehend core Kubernetes concepts, its benefits, and the design principles that support scalable, fault-tolerant application deployments.
  • Navigate the Kubernetes architecture, including the roles of master/nodes, and become proficient in using essential tools like kubectl, kubeadm, kubelet, and kube-proxy.
  • Utilize Kubernetes features effectively by creating and managing Pods, Replica Sets, Services, Deployments, and manually scheduling workloads.
  • Manage Kubernetes resources, understand the purpose of namespaces, and implement resource limits and quotas to optimize cluster utilization.
  • Implement storage solutions in Kubernetes, learning to work with EmptyDir, host volumes, Persistent Volumes (PV), and Persistent Volume Claims (PVC).
  • Configure environment variables for container applications using plain key-value pairs, ConfigMaps, and Secrets for sensitive data management.
  • Understand and manage Kubernetes workloads through Jobs, CronJobs, and DaemonSets, and enforce security best practices within the cluster environment.

By completing this course, students will have the skills to deploy, manage, and scale applications on Google Kubernetes Engine with confidence, following best practices for security and resource optimization.