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Develop Azure Infrastructure as a Service compute solutions

27. AZ-203 - What is Kubernetes and Azure Kubernetes

Hi and welcome back. Now we come to the part where we're going to be looking at Azure Kubernetes as a service. Before we get into AzureKubernetes, let's define Kubernetes. So this is a tool that's available on the Internet. But why do we need this tool in the first place? Why do we need this platform? Now, we've already seen in earlier chapters how we could create containers and how we could basically launch containers on a virtual machine that had the Docker engine running. Now, in companies, you won't just have one container. You would have maybe thousands of containers with thousands of application components, and you could be distributing them across a lot of virtual machines. Now, for you to keep track of the company and to keep track of these containers on these virtual machines in order to scale these containers, you need to ensure that if a container stops working, they need to bring it back up. So all of this is really a tedious and manual process, and it gets more difficult as the number of containers starts increasing and the number of virtual machines running these containers starts to increase. In this case, you'll need container orchestration software, which is software or a platform that allows you to manage these containers as well as the virtual machines that host them. And that's where you have the Kubernetes service. So I'm not talking about your Kubernetes; I'm just talking about the vanilla Kubernetes as it is. So this is an open source platform that's available for managing your containers and the virtual machines hosting your containers. Now, if you look at the simple architecture of how you would deploy Kubernetes, well, first you would go ahead and have a virtual machine on which you would host the master node for a Kubernetes cluster. So you would go ahead and download and install the Kubernetes software on the virtual machine and mark it as the master of something known as a Kubernetes cluster. Now, on this cluster, you will have nodes or virtual machines that will be used to run your Docker containers. These nodes would be managed by your master node. So on each of these nodes, again, you would install Kubernetes software on them as well, and then you would connect them to the master in your cluster. You would then deploy your containers onto the nodes using something known as a Cube CTR tool. So this is a command-line interface tool that can be used to work with your Kubernetes cluster. So if you want to deploy your containers onto the cluster, you can use the Cube CTL tool. So this is just a primer on Kubernetes. We will now move on to Azure Kubernetes and see how we can deploy a simple cluster. So what is Kubernetes? So this is an open source platform that is used to manage containerized workloads. So, there are many features for Kubernetes when it comes to managing your containers. So this platform is able to provide a DNS name to your container. If there is a high load on your containers, Kubernetes can also load, balance, and distribute network traffic. It also has a specialty in restarting containers that fail. So if any of your application containers fail in the cluster, Kubernetes will try its best to restart those containers. It can also be used to replace or kill containers, and it also helps store and manage sensitive information such as passwords or tokens and SSH keys. So, what is Azure Kubernetes? Well, this is a fully managed service on the Azure platform. This makes it easy to deploy and manage containerized applications. It helps remove the burden of managing the underlying infrastructure for the Kubernetes deployment. Right, so let's go ahead and see how we can work as your Kubernetes.

28. AZ-203 - Lab - Creating a Kubernetes cluster

Hi and welcome back. So in this lab on Azure Kubernetes, we're going to see how to use the Azure command interface to create a resource group and the cluster. So in this lab, we're first going to have a look at the visitor that can be used to create the Kubernetes cluster. But then we're going to use Azure commandline tools to create a resource group and a cluster, since this is important from an exam perspective. So here we are in Azure. Now if you go ahead and click on Add a New Resource, you can click on Kubernetes Service. You could choose your resource group, give a name for the cluster, choose the region, and choose the version of committees that you want to use. Specify the DNS name prefix. Specify the name of the nodes. So remember, these are the nodes that will be used to run your containers. If you go on to Next for scale, over here, you can scale your cluster. If you go on to Next for authentication, you have a service principle. This service principle actually allows Kubernetes to work with other Azure resources. So let's say that you want Kubernetes to pickup the images from your Azure container registry. It will actually use the service principle in networking. Here you can make the service run as part of the virtual network. If you go on to monitoring, you can enable monitoring for the cluster, and then you can go onto stacks and do a review and create. But since from an example perspective, it's important to understand how you create a cluster from the Azure command line interface, let's do that. So let's open a cloud shell. Let me go ahead and choose an existing resource group. Create a new storage account and a new file share. Click on "Create Storage." Now, once I logged in, I'm currently in the Bash profile. You can actually switch between Bashand PowerShell and PowerShell right here. Now, the first command we're going to issue is to basically create a resource group. So I'm going to use the AZ Group Create command to create a new resource group in the East US region. The name of the group is Kubernetes GRP. Once this is in place, you can go ahead and create your cluster. So over here I'm specifying the AZ AKS Create command. I am specifying the name of the resource group, the name of the cluster, and the number of nodes in the cluster. Please know that you can scale up the number of nodes later on in the Adams. I'm making sure that mounting is enabled for the cluster, and I'm ensuring to generate the SSH key so that we can work with the cluster later on. So this is going to go ahead and create the Kubernetes cluster for you. So currently, it's gone ahead and finished creating the service principle. Let's come back once the entire cluster is in place. Now that the cluster has been established, you can access all resources. So now if you go and see all the resources, you can see a number of resources that have been created as part of the cluster. You can also see that you have one virtual machine running in your pool. So this is the node that's going to run our containers. Now, if you want to go ahead and start issuing commands against the Kubernetes cluster, you have to go in and use the Cube CTL tool. Now you can issue the following command to install the Cube CTL tool. Once this is done, you can issue the following command to ensure that the credentials are in place to work with your cluster. Once this is also complete, let me clear the screen. Now you can start using the Cube CTL tool. So if you want to get the number of nodes running in your cluster, you can issue the following command. So here you can see that there is one agent that has been running for the past 4 minutes. If you want to get all the deployments, pods, and services running on your cluster, you can issue the get all command for Cube CTL. So currently I just have one service running, and that's the main Kubernetes service. Apart from that, I don't have anything running on this cluster. Right? So this marks the end of this lab. Bye.

29. AZ-203 - Understanding of application deployment to a Kubernetes cluster

Now that we have our cluster in place, let's look at a lab to see how we can deploy an application to our Kubernetes cluster. So we're going to deploy our DotNetCore application to our Kubernetes cluster. We're going to make use of the image stored in our Azure container. Remember in the earlier chapters, we saw how we could publish net-core containerized applications to the Azure Container Registry? We are going to be using the same image, which is available in our Container Registry, and deploying it as a container on to a Kubernetes cluster. We are going to make use of something known as a deployment file. Those deployment files can be used to deploy containers on a Kubernetes cluster. So let's go ahead with our lab.

30. AZ-203 - Deploying an application onto a Kubernetes cluster – Steps

Just a quick reminder of what a service principle is. Now, in our use case, we're going to be making our Azure Query service actually pull out an image from the Azure Container Registry. Now, the Azure container street is a separate service. The Azure Kubernetes Service is again a separate service in Azure. Now, normally, when you want to make one service talk to another service in Azure, this service needs to be authorised to basically use the other service. Now, instead of having a user defined in Azure and then trying to make use of those user credentials, which will probably have access to the Azure container history, So instead of using this sort of method for authorising the cluster to get an image from the Azure container industry, you would instead use something known as a service principle. So this is like another identity that's available in Azure. So you could create a separate identity known as a service principle. The service principal would get an ID as well as a client ID. You could then assign a role to the service principal, and the service principle could be assigned to your service, or in this case, the Azure Kubernetes Cluster. This role would then give the required authorizations for this cluster to go ahead and pull the image from the Azure Container Registry. So just a quick note on the surface And so before we actually go ahead with our lab.

31. AZ-203 - What is a service principal

Just a quick reminder of what a service principle is. Now, in our use case, we're going to be making our Azure Query service actually pull out an image from the Azure Container Registry. Now, the Azure container street is a separate service. The Azure Kubernetes Service is again a separate service in Azure. Now, normally, when you want to make one service talk to another service in Azure, this service needs to be authorised to basically use the other service. Now, instead of having a user defined in Azure and then trying to make use of those user credentials, which will probably have access to the Azure container history, So instead of using this sort of method for authorising the cluster to get an image from the Azure container industry, you would instead use something known as a service principle. So this is like another identity that's available in Azure. So you could create a separate identity known as a service principle. The service principal would get an ID as well as a client ID. You could then assign a role to the service principal, and the service principle could be assigned to your service, or in this case, the Azure Kubernetes Cluster. This role would then give the required authorizations for this cluster to go ahead and pull the image from the Azure Container Registry. So just a quick note on the surface And so before we actually go ahead with our lab.