Deploy and Manage Azure Compute Resources
Scott Hoag
5 h 1 m
Lecture Overview
In this course, you will learn how to provision Azure compute resources for the right workload. You will understand how to create and configure virtual machines (VMs) for high availability and scalability, as well as understand how to automatically deploy and configure VM based workloads. From there you will learn how to deploy workloads using containers with Azure Kubernetes Service (AKS) and web applications using Azure Web Apps.

Related Learning Path(s):
AZ - 104 Azure Administrator
  • Fundamentals of Microsoft Azure
  • Experience with a scripting environment such as PowerShell or Bash
  • Experience with infrastructure components such as virtual machines, networking and storage
Lecture Modules
In this module, we'll discuss how to create virtual machines and what types of Operating systems are supported in Azure. We'll also discuss how to configure your virtual machines, including how to size your VMs for CPU, memory, and storage. Then we'll cover how to configure networking for a virtual machine in Azure, including how create virtual machines with multiple network interfaces. Finally, we'll talk about how to move virtual machines between resource groups.

In this module we're going to discuss not only the concepts you need to know when it comes to high availability and scalability in Azure, but also how to implement these concepts. We'll start with high availability, which includes how to improve the uptime for your VMs by spreading your workloads across multiple servers and how to improve the performance of those workloads with lower latency between servers in a tier. We'll then discuss how to scale those workloads – both automatically and manually and some considerations for each. This is going to take us into a discussion around the implementation of Virtual Machine scale sets and how they can help you achieve both high availability and scalability.

In this module we'll run through an overview of Azure Resource Manager templates and how they can help you transition to infrastructure-as-code. Once you have a firm grounding in templates, we'll discuss how to take existing Azure Resources and turn them into templates and how to modify templates to fit your needs. Then we'll transition from Azure Resource Manager templates to creating your own custom virtual machines images using managed images. Finally, we'll discuss how to effect change within your virtual machines using automation and the Custom Script Extension.
First, we’re going to look at the different parts and services within the Azure Container Ecosystem and how they all fit together. We’ll then take a look at the Azure Container Registry used to store, access, manage, and build your container images. Next, we’ll explore Azure Kubernetes Service, a managed Kubernetes cluster offering within Azure. Finally, we'll explore Azure Container Instances, the simpler of the two managed container services offered in Azure.
In this module we will first discuss how to create a web app, then dive into create WebJobs.  Then we will discuss enabling diagnostic logging for your applications and how to containerize those web apps.  We will then discuss monitoring web apps with Azure Monitor.
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