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We're here to help you find itIntroduction to Kubernetes on Edge with k3s (LFS156x) Course Overview
In this course, you will learn the use cases for running compute in edge locations and about various supporting projects and foundations such as LF Edge and CNCF. The course covers how to deploy applications to the edge with open source tools such as K3s and k3sup, and how those tools can be applied to low-power hardware such as the Raspberry Pi. You will learn the challenges associated with edge compute, such as partial availability and the need for remote access. Through practical examples, students will gain experience of deploying applications to Kubernetes and get hands-on with object storage, MQTT and OpenFaaS. It also introduces the fleet management and GitOps models of deployment, and helps you understand messaging, and how to interface with sensors and real hardware.
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USD
View Fees Breakdown
Course Fee | 1,075 |
Total Fees |
1,075 (USD) |
USD
View Fees Breakdown
Course Fee | 850 |
Total Fees |
850 (USD) |
USD
View Fees Breakdown
Flexi Video | 16,449 |
Official E-coursebook | |
Exam Voucher (optional) | |
Hands-On-Labs2 | 4,159 |
+ GST 18% | 4,259 |
Total Fees (without exam & Labs) |
22,359 (INR) |
Total Fees (with exam & Labs) |
28,359 (INR) |
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You can request classroom training in any city on any date by Requesting More Information
Certainly! Here are the minimum required prerequisites for successfully undertaking the "Introduction to Kubernetes on Edge with k3s (LFS156x)" course at Koenig Solutions:
Prerequisites:
Introduction
The "Introduction to Kubernetes on Edge with k3s (LFS156x)" course is designed for IT professionals seeking to enhance their proficiency in deploying and managing Kubernetes at the edge.
Target Audience:
Introduction
The "Introduction to Kubernetes on Edge with k3s (LFS156x)" course provides a comprehensive understanding of Kubernetes applications at the edge, focusing on practical use cases and hands-on labs. Students will master deploying, managing, and scaling applications using the lightweight K3s distribution.
Learning Objectives and Outcomes