Kubernetes has emerged as the leader in the container orchestration and management platforms. However, this begs a question: Who will manage your Kubernetes Infrastructure? In this course, Azure Kubernetes Service (AKS) – The Big Picture, you will learn the skills to deploy a managed Kubernetes platform on Microsoft Azure without worrying about the underlying computer and management overhead. First, you will learn the fundamentals of Docker and Kubernetes and see how it applies to a Microservices Architecture. Next, you will discover how to deploy an application to a local Kubernetes Cluster and see how that experience translates to deploying the same application to Azure Kubernetes Service without any change to the deployment experience. Finally, you will see how easy it is to scale your application workloads in AKS, which will help you take your AKS skills to the next level and help you modernize and re-platform your application workloads on Microsoft Azure. By the end of this course, you will have a foundational knowledge of Azure Kubernetes Service that will help you deploy containerized workloads on Azure with minimal management overhead.
Anyway, you could learn this course thorough the course provided by https://www.pluralsight.com/courses/azure-container-service-big-picture
Month: February 2019
Docker introduction
Docker is an open platform management tool for Linux Containers. It provides a means for developers and system administrators to build and package applications into lightweight containers. Docker consists of the following components:
- Docker Engine – A portable, lightweight runtime and packaging tool
- Docker Hub – A cloud service for sharing applications and automating workflows
Docker is used to create image-based application containers. Image-based containers package an application with the individual runtime stack into a single container. This makes the container-independent from the host operating system and kernel version. As a result, you can run the same application, unchanged, on laptops, data center virtual machines, and any cloud. You can transfer this container to another machine that runs Docker and runs the application without any compatibility issues.
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