Docker & Kubernetes: The Practical Guide [2023 Edition]
Learn Docker, Docker Compose, Multi-Container Projects, Deployment and all about Kubernetes from the ground up!
Created by Academind by Maximilian Schwarzmüller | 23.5 hours on-demand video course
Join this bestselling Docker & Kubernetes course and learn two of the most important development technologies from the ground up, in great detail! Docker & Kubernetes are amongst the most in-demand technologies and topics you can learn these days.
Because they significantly simplify the development and deployment process of both simple and complex software projects. Especially in web development (though not limited to that), Docker can really take you to the next level!
With Docker, you create and manage so-called “Containers” – basically packages of code and tools required to run that code. These containers allow you to run your programs in a predictable, environment-independent way – no matter where you need to run it.
For modern DevOps but also for local development – on your own or in a team – this is a winner feature since you will no longer have any “but it worked on my machine” discussions. It works inside of a container, hence it works everywhere!
This Docker & Kubernetes: The Practical Guide [2023 Edition] course will teach you both Docker & Kubernetes from the ground up with all the required theory and tons of examples and demos! We’ll explore all key concepts in detail and with practical examples and demos – from images and containers, over volumes and networking all the way up to deployment and Kubernetes Cluster: This course has it all!
What you’ll learn
- You will learn what Docker and Kubernetes are and why you might want to use them
- Learn how to install and use Docker on any system (macOS, Windows, Linux)
- Learn how to create and use Images & Containers with Docker
- Understand complex topics like managing and persisting data with Volumes
- Learn about Container Networking with Docker Networks and DNS Service Discovery
- Learn how to deploy Docker applications – manually, with managed services or with Kubernetes
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