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Create and manage Windows Server container images.

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The Hello World type of question when we're

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confronted with Docker containers is,

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what's the difference between a Docker container and a virtual machine,

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and why would you care?

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After all, we're administrators, not developers.

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Well, as an administrator,

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you're probably creating environments that are consumed by your developers.

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Virtual machines, as I'm sure you know by now,

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are software‑based computer instances that run on top of a hypervisor platform.

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So, in Microsoft land, we have Hyper‑V as our hypervisor,

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and then in our virtual machine, we have a virtualized set of hardware,

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CPU, RAM, network, storage.

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Of course, the VMs are all sharing that hardware from the host.

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But the point is we've got the full stack within each VM,

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a full instance of the operating system,

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all software binaries, dependencies, and then your applications.

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It's a lot faster nowadays for your developers to do

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their test and dev work and even present services in

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production using Docker containers.

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Now if we compare and contrast, by the way,

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this diagram, you can see the attribution URL in the lower left corner,

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just wanted to say that, we still have the underlying hardware infrastructure,

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but instead of having each container enclosing a full operating system,

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which is pretty heavy in terms of disk space and network

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bandwidth allocation and just simple upkeep,

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we have a single operating system and a single

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container engine running on our host,

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and each Docker container is simply the application and

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its supporting binaries and libraries.

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Now there's some underlying smoke and mirrors that are going on.

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We can look at Docker containers running on a container host as basically

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processes because those containers are all sharing the underlying

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container engine operating system and host hardware.

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However,

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Microsoft put a little wrinkle on that with Hyper‑V

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containers that we'll learn about momentarily.

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Long story short,

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containers represent a way to virtualize individual applications

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in a way that's much faster and more portable,

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generally speaking, than doing the same thing with big old virtual machines.

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Now this notion of application virtualization is not specific to Docker.

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In fact,

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the underlying techniques in Linux that support containerization predate Docker.

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Docker just presented a uniform API for working with those

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application virtualization technologies.

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And Microsoft and Docker have a really tight partnership.

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They've been very close business partners for the last several years; therefore,

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it is absolutely in scope for your AZ‑800 and AZ‑801

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exams for you to know a bit about Docker,

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okay?

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So here in this blurry image, sorry, it was the highest res I could find,

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it shows the Docker workflow.

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To build a container involves first getting hold of an

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image or creating your own image.

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You create a Docker image by installing the Docker CLI,

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Docker command‑line tools, the build tools on your system,

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of course, these are available for Windows,

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macOS, and Linux, and you create what's called a Dockerfile.

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This is a set of instructions using a domain‑specific

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syntax that Docker created that provides instructions on

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what you want to be in your image,

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and you'll always start with an existing image,

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and then you can add and subtract from there.

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We don't need to get too much deeper into the weeds there.

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You do need to know just a little bit about the Dockerfile

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syntax in case you see that on your exam,

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and I'll show you how to do that in the demo,

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so don't worry about that.

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But bottom line is your Dockerfile is then built or compiled into an image.

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Again, you do this all using the Docker client tools.

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That image is a binary snapshot of the container contents,

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and this is going to be what you use to run or spawn Docker containers.

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That's the highest‑level view here.

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Again, the image is the binary deployable unit,

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and you'll want to keep your Docker images in a central repository to where

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your developers and infrastructure people can get to them.

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And because the Docker files are plain text files,

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you'll want to keep those in Source Code Control.

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In order to run Docker containers, you'll need the Docker server component,

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and this is called a daemon, or in Windows,

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it'd be a Windows service, the Docker service,

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same idea, it's a background process,

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and this on the Docker host supports that runtime

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environment for your containers.

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And of course, we've got support for Windows Server for Docker,

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for Windows 10, Windows 11 client, and then Azure as well.

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One of the value propositions among many of containerizing

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your workloads is that they're universal,

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they can run in any environment.

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The bottom line is it doesn't matter whether your Docker host is in Amazon or

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Google Cloud or Azure or on‑premises or in another provider.

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As long as you've got the Docker daemon running,

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you should be able to create containers based on those images.

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It's a really universal way to develop and deliver software.

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This is one of the big reasons why Docker has such a big foothold in the business and software development lifecycle market.