Hey, everyone.
And welcome back.
Now, in today's video, we are going to discuss about the elastic Kubernetes service.
Now, for most of the organizations that are using Kubernetes, one of the primary challenges that you
will see is to build and maintain the entire Kubernetes cluster.
So in order to do that, it takes a lot of time and also a lot of resources.
So, for example, you will need to have an entire dedicated Kubernetes team that can manage and maintain
your cluster.
So when we discuss about manage and maintain the cluster, it's not just about creating the Kubernetes
cluster, it's about the overall upgrade.
So when a new Kubernetes version is launched, you'll have to update each and every component.
It's about security of the entire community's cluster and so on.
Now, although this seems to be fine for the organizations that is providing Kubernetes service, but
for the normal organizations, the question that will come is, will you focus on maintaining Kubernetes
or will you focus on your application?
And this is one of the challenge.
So even in this diagram, when we discuss about the Kubernetes cluster, you will see that there are
multiple components involved.
You have API server, controller, manager, scheduler, and then you need to have multiple set of these
components for overall high availability.
Then you'll have to take care of the load balancing solution across all of this.
And then you also have to take care of security and everything.
All right.
So in order to overcome this, what many of the cloud providers have been doing is that they are giving
the managed Kubernetes service for their customers.
So the entire setup and high availability and security is taken care of by the managed provider.
And as a customer, you can focus on your application and deployment of your application in the Kubernetes
cluster.
Now, when we discuss about the managed Kubernetes offering, there are multiple providers that offers
this.
One of the popular ones is Digital Ocean.
So you see you have Kubernetes in minutes.
So basically all you have to do is you have to go ahead and create a component cluster.
There are a few small options over here, like which is the version of Kubernetes that you want to use.
And you go ahead and create the cluster.
In such cases, everything over here, including load balancing, high availability and everything,
is taken care by the digital ocean.
So this is one offering.
The second very popular managed Kubernetes offering is provided by eight us.
So again, it's the same thing.
The entire Kubernetes cluster is managed by us.
And as a customer, you can focus on deploying an application.
And in this video we are going to focus on the A WS offering related to the managed Kubernetes cluster.
And the name of the offering is X.
All right.
So just to revise the Amazon Elastic Kubernetes service, also referred to as the Amazon X is a managed
service that you can use to run the Kubernetes cluster on us.
Now, one of the benefits of using the X is that it provides tight integration with various other services.
For example, it integrates very well with easier iam, elastic load balancing, etc. to provide end
to end features for your application deployments.
And this is one of the benefits of using any managed offering in a WS is that it provides the tight
integration with other services.
So let's do one thing.
Let's go ahead and have a quick demo now for today's video.
I have an X cluster that is already available and it is running on a specific version.
Now, if I quickly open this cluster over here now within here, if I go ahead and open up the compute,
you'll see that I have certain worker nodes over here.
So these are the worker nodes.
Let me quickly show you.
These are you see, you have a set of worker nodes.
Worker nodes are basically the servers with your Docker containers.
Or to be more precise, Kubernetes ports will be launched.
So worker node is where your application will be running.
So in my X cluster, there are two worker nodes that are available where the application is deployed.
Along with that X also makes it very simple to go ahead and take care of the networking related to the
cluster.
You can go ahead and manage and install various add ons.
You can take care of the authentication, you can take care of the logging, etc. so it becomes much
more simpler.
And even here you can see what are the exact ports that are running within your Kubernetes cluster,
for example, you see we have one engine export, or if you are new to Kubernetes, you can consider
it to be containers.
So you have an engine X container and you can also see various other objects and resources that are
part of your Kubernetes cluster.
Now, one of the recommended things that you need to do before you implement a service is to always
verify the pricing, specifically the managed service offerings related to very popular tool.
Like Cuban it is.
And others always verify the pricing before you create the cluster.
For example, if you look into the X, the pricing is you pay $0.10 per hour for each x cluster that
you create.
So if I open up that calculator, you have 0.10 into 24 hours.
So that is 2.4 USD in 230, which is 72 USD.
So $72 is something that you pay only for the cluster, nothing else.
Apart from that, you also pay for the compute.
So the SC two instances that have been launched as a worker node, you also pay for that.
SC Two instances as well.
So at the end, if you deploy the Kubernetes cluster, you can assume that the minimum bill would cost
somewhere around 100 USD.
All right.
So this is one thing that you need to take care of.
However, that's the overview.
And with this will conclude today's video.