Part One - Lectures
Part Two - Demonstration
AKS is a super-charged Kubernetes managed service which makes creating and running a Kubernetes cluster a breeze!
This course explores AKS, Azure’s managed Kubernetes service, covering the fundamentals of the service and how it can be used. You’ll first learn about how as a managed service it takes care of managing and maintaining certain aspects of itself, before moving onto the core AKS concepts such as cluster design and provisioning, networking, storage management, scaling, and security. After a quick look at Azure Container Registry, the course then moves on to an end-to-end demonstration that shows how to provision a new AKS cluster and then deploy a sample cloud-native application into it.
For any feedback, queries, or suggestions relating to this course, please contact us at firstname.lastname@example.org.
- Learn about what AKS is and how to provision, configure and maintain an AKS cluster
- Learn about AKS fundamentals and core concepts
- Learn how to work with and configure many of the key AKS cluster configuration settings
- And finally, you’ll learn how to deploy a fully working sample cloud-native application into an AKS cluster
- Anyone interested in learning about AKS and its fundamentals
- Software Engineers interested in learning about how to configure and deploy workloads into an AKS cluster
- DevOps and SRE practitioners interested in understanding how to manage and maintain an AKS cluster
To get the most from this course it would help to have a basic understanding of:
- Kubernetes (if you’re unfamiliar with Kubernetes, and/or require a refresher then please consider taking our dedicated Introduction to Kubernetes learning path)
- Containers, containerization, and microservice-based architectures
- Software development and the software development life cycle
- Networks and networking
If you wish to follow along with the demonstrations in part two of this course, you can find all of the coding assets hosted in the following three GitHub repositories:
Hello and welcome to the Introduction to AKS course, presented to you by Cloud Academy. In this lesson, we'll cover off the course agenda, intended audience, learning objectives, and course prerequisites.
I'm really excited to be taking you through this course on the Azure Kubernetes service. There's been a real ground swell towards building microservice-based architectures and hosting them as containers within Kubernetes.
Microsoft quotes that from 2022, more than 75% of the world's global organizations will be running containerized workloads in production. AKS will continue to be at the forefront of this momentum shift and there is no better time to upskill on this platform.
Now, before we continue, I'll quickly introduce myself. I'm Jeremy Cook, one of the trainers here at Cloud Academy, specializing in DevOps and software engineering. Feel free to connect with either myself and/or the wider team here at Cloud Academy regarding anything about this course. You can email us at email@example.com.
This training course focuses on bringing you up to speed with AKS, Azure's managed Kubernetes service. It will take you through all of the fundamentals involved in working with AKS.
Please note, this course is not an introduction to Kubernetes itself, so if you're unfamiliar with Kubernetes, then please consider taking our dedicated Introduction to Kubernetes learning path.
This course is split into two parts. The first part will bring you up to speed with the AKS managed service. You'll first learn about how, as a managed service, it takes care of managing and maintaining certain aspects of itself. We'll cover off many of the core AKS concepts, such as cluster design and provisioning, networking, storage management, scaling, and security, etc.
In the second part, I'll provide an end-to-end demonstration in which I provision a new AKS cluster and then, deploy a sample cloud-native application into it. The sample cloud-native application has been engineered using the following technologies; React, Go, MongoDB, and Docker containers.
The sample demonstrated deployment performed within the AKS cluster will use the following configuration as seen here and will consist of the following Kubernetes resources.
To help you follow along in part two, all of the coding assets as used and demonstrated are hosted within the following three Cloud Academy GitHub repositories. You are strongly encouraged to clone these repositories and perform the same deployment within your own AKS cluster.
The intended audience for this course includes anyone interested in learning about AKS and its fundamentals, software engineers interested in learning about how to configure and deploy workloads into an AKS cluster, and DevOps and SRE practitioners interested in understanding how to manage and maintain an AKS cluster.
By completing this course, you will learn about what AKS is and how to provision, configure, and maintain an AKS cluster, learn about the AKS fundamentals and core concepts, learn how to work with and configure many of the key AKS cluster configuration settings, and finally, you'll learn how to deploy a fully working sample cloud-native application into an AKS cluster.
The following prerequisites will be both useful and helpful for this course; a basic understanding of Kubernetes and basic Kubernetes resources, a basic understanding of containers, containerization, and microservice-based architectures, a basic understanding of software development and the software development lifecycle, and a basic understanding of networks and networking.
Okay, the course introduction has now been completed. Go ahead and close this lesson, and we'll see you shortly in the next one.
Jeremy is a Content Lead Architect and DevOps SME here at Cloud Academy where he specializes in developing DevOps technical training documentation.
He has a strong background in software engineering, and has been coding with various languages, frameworks, and systems for the past 25+ years. In recent times, Jeremy has been focused on DevOps, Cloud (AWS, GCP, Azure), Security, Kubernetes, and Machine Learning.
Jeremy holds professional certifications for AWS, GCP, and Kubernetes.