Training > Networking > DevOps for Network Engineers (LFS266)
Training Course

DevOps for Network Engineers (LFS266)

The line between Development and Operations is disappearing and both sides are learning to adjust to some common ground as organizations embrace Agile principles. This course will help network engineers familiarize themselves with the DevOps tools needed to assist in the DevOps/Agile process.

Who Is It For

This course is designed to provide network engineers with the skills necessary to start applying DevOps practices, learn their role in the DevOps cycle, and integrate their expertise in a DevOps environment.
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What You’ll Learn

This course will teach you how to integrate into a DevOps/Agile environment, commonly used DevOps tools, how DevOps teams collaborate on projects, how to confidently work with software and configuration files in version control, how to recognize the roles of SCRUM team members, how to confidently apply Agile principles in an organization, and more.
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What It Prepares You For

The course will prepare you to use DevOps tools and Agile processes to automate networks and contribute to connectivity, network performance tuning, security, and many other areas of network management that require network expertise.
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Course Outline
Chapter 1. Course Introduction
Chapter 2. Modern Project Management
Chapter 3. The DevOps Process: A Network Engineer’s Perspective
Chapter 4. Network Simulation and Testing with Mininet
Chapter 5. OpenFlow and ONOS
Chapter 6. Infrastructure as Code (Ansible Basics)
Chapter 7. Version Control (Git)
Chapter 8. Continuous Integration and Continuous Delivery (Jenkins)
Chapter 9. Using Gerrit in DevOps
Chapter 10. Jenkins, Gerrit and Code Review for DevOps
Chapter 11. The DevOps Process and Tools (Review)

Prerequisites
To make the most of this course, you will need to have:

  • Familiarity with Linux system administration
  • Familiarity with shell scripting
  • Knowledge of Python
Lab Info
Lab exercises in this course are designed to work either on native hardware, or using a virtual machine (VM), under a hypervisor, such as those in the KVM, VMWare, or Virtual Box families. Detailed instructions to set up your lab environment are provided in the course.

If using a cloud provider like GCP or AWS, you should be able to complete the lab exercises using the free tier or credits provided to you. However, you may incur charges if you exceed the credits initially allocated by the cloud provider, or if the cloud provider’s terms and conditions change. 

Reviews
Aug 2022
I like that this course provides a quick explanation of notions.
Oct 2020
Complete flow is covered, and all the labs were connected and serve the end goal.