Do you desire to build an elite Cloud Architect career Solution Architect career or cloud engineer career? If so this video is for you. In this video, we are going to teach you about the cloud. And then you'll know how to work on multiple clouds. And we're going to show you how the cloud is nothing more than a network in a data center has been virtualized, we will teach you the network and data center services, or at least some of them that you will need to know. And then you will understand the equivalent services on the cloud.
So you will know how to migrate those services to the cloud. Let's begin, but before we do, I want to tell you my background, I've been working in this technology industry for over 25 years. And I've spent the last 20 years helping others get their first tech job or get promoted in tech.
And of course, I want to help you get cloud hired or cloud promoted. So we're first gonna start with the most fundamental element of cloud computing, virtualization virtualization is what makes cloud computing possible. And I love virtualization.
No virtualization is not new. It's about 50 years old, and IBM initially invented it. And then after that, about 20 years ago, we had modern virtualization, and VMware created server virtualization. And that's what we're going to talk about today.
Now, we will also tell you the equivalent services on the clouds, you know exactly what to use, and where but we want you to truly understand server virtualization and why to take those virtual servers and then network in the data center to migrate them to the cloud, you need to know what they are. And by the end of this discussion, you'll not only know what they are, you know what they are on Azure, Google and AWS, and be prepared to work on any of them. So let's talk about server virtualization. One of my favorite things.
If we go back to the old days, 2530 years ago, we had very small capacity servers, maybe they had a CPU core, maybe they had a couple of Meg's of RAM. And in those days, one server was for one application. And in many cases, we have multiple servers for a small application. And that's what we used to do.
And then the server started getting two cores, and four cores, now we're up to 128 cores, now you can get a good six terabytes of DRAM on a physical server. Now, most applications don't need a giant server like that. So what happened is, we could either buy these big fancy, you know, 60 $75,000 servers, and they could be 2%. US sucking up our electric and sucking up our financial resources. Or we could take these same servers and use them for multiple applications.
Now, single set of electricity, single space on our racks, efficiency in terms of real estate efficiency in terms of power and efficiencies in terms of cost. Because now that 60, or $70,000 server might replace 30 servers, or 40 servers, or if it's going to be used for containers, which we'll talk about later, it might just host 100 containers. But let's really talk about how this works.
See what happens is now that the servers are powerful, we want to find a way to use them. And that's where server virtualization chromosomes. So we take our servers, and we chop them into logical mini servers. So instead of having one server, we've got a bunch, which is great. So what do we do, we take our physical server, and we have to install a thin layer of software on it, that's going to divide the server up into many pieces of that server, divide the CPU cores, the memory, the storage.
Now that software is called a hypervisor. So we have a hardware, we lay our hypervisor and from there, we create our virtual machines. In our virtual machine, we tell it how many CPU cores CPU cores, we need a DRAM, we need the type of hard drive etc. And then we install an operating system on each virtual machine just like any other computer, we install our applications. And bingo, now we've got multiple servers. Now we've got 128 cores, chances are we've got, you know, a bunch of four core servers that we can put there or less number of eight core servers or an even smaller number of 16 core servers, or how many 32 core server so you get the point.
By doing this, we can take one server, chop it up with the multiple service, how does it work? The hypervisor. That's the magical secret weapon to making this work. Bare Metal.
We take our server we install just the hypervisor, no operating system. And then we've got our virtual machines, and each one has their own operating system and their own applications. Great way to do virtualization, still the primary form of competing on the cloud virtual machines.
Now we've talked about a type one hypervisor, which is server virtualization, and guess what on the cloud will tell you how to find these. While your data center is typically sitting on VMware, KVM or QAM, you Three of them were more common hypervisor on the cloud. If you're getting it from AWS, it's going to sit on an easy to instance, or Elastic Compute Cloud. And if you're on Azure, well, they're gonna call it a virtual machine. They call it an Azure virtual machine. If you're on Oracle, they also call it a virtual machine.
But if you're on Google, they call it a Compute Engine instance. So now, you know, we strip away all these fancy names. What is it? It's a virtual machine.
Now this is a type one hypervisor. This is what we use with server virtualization. Now, because we were talking about server virtualization on type one hypervisors, I wanted to make sure there was no confusion.
So what am I referring to here, many of us like me, I use a Mac. And every once in a while, there's some program I have to use Windows for. Or better yet, when I used to use Linux, there was always some program that I needed to use Windows for. And because of that, I always run a virtual machine on my computer.
But it was not the same kind of virtual machine we were talking about. So many of you, for example, have Macs, and you want to run Windows virtual machine. And when you do that, but you have is a type two hypervisor, which is nowhere near the performance of a type one hypervisor, but it has a different use case.
Now, in this case, we have our physical hardware, say it's our notebook. We have our operating system, say it's Red Hat, Linux, or guess what my favorite Mac iOS? Well, at least for us, so I can write Word documents on it. And then I would have a hypervisor.
Now note, in this case, we had the hardware, the operating system and the hypervisor, which runs on top of the operating system. Hence, it's slow, because the operating systems are another layer away from the physical hardware. And here, what will we do, then we will install our virtual machines, which would help of course, their own memory and CPU and hardware resources. But the fact that they're running inside of an operating system slows them down. So this is not what we're going to use for server virtualization.
But many of you have worked with it in the past with via VirtualBox, or VMware Workstation or parallels, and I wanted you to know what they are, understand this, and you'll be good to go and get yourself cloud hired or promoted, because that's critical information for the cloud architect, Solution Architect, Enterprise Architect, or cloud engineer critical information for our world. So now let's talk about the next form of computing on the cloud. It's called the container. So virtualization is not new. And the concept of the container is not new either. In networking, we had something called the private VLAN, which VLAN was basically a server virtualization, but for virtual switches.
And then we came up with a private VLAN, which meant one user inside of a VLAN, couldn't talk to another user inside of the same VLAN. And now, in Compute, we've got the same thing. We basically created an environment called the containerized environment, what does a containerized environment really do? In simple terms, it almost basically virtualizes your operating system. So with a container, we can have one virtual machine or one physical server doesn't matter. And here we can have an application in a container, and another application in another container, and another application and another container, and it's beautiful.
Now what happens on one container should have no impact on another container. Well, that's great. So that means security and performance.
So let's think about this just for a minute, we will have our physical hardware, we will have our host operating system, and we will have a Container Engine. So hardware, operating system and Container Engine, no, we're also usually going to have something that orchestrates the containers. But you don't need to go there right now. And in and remember, in virtualization, we had virtual machines, and each virtual machine had their own operating system and their own application. But with the container, oh, we're going to have the container system libraries, and our applications.
And why do the containers work? What happened when we when we build a container? That container pulls things from the operating systems libraries. So it doesn't need to run another virtual machine with its own operating system? It's leveraging the operating system libraries on the primary operating system. Why does this matter? Well, if you're going to run a container on your Mac, guess what, you can't move that container to a Windows system because it's dependent upon the containers and the libraries on your Mac. Likewise, if you built something on a Windows system, you can't port it to a container to an containerized environment on a Linux server because it needs the operating system libraries. So keep that in the back of your mind.
What is the container physical hardware us Container Engine, an isolated container library, an application library and application library and application. And because of this containers are very lightweight. No operating system means we can save lots of RAM, lots of memory resources. And the containers are fast so fast and light and a server that might only be able to do 10 virtual machines might be able to do 50 containers because they're so efficient.
So containers for the most apart are the virtualization of the present and the future. Now granted, the majority of the work is still being done on virtual machines, like containers are there. Now virtual machines will always be muted for use for things that need high performance and lots of memory and compute power. But for things that don't need it, the containers are a very efficient strategy.
It's almost as if like, they virtualized your operating system. And here's why you got a container and another container, they can't talk to each other, it's great. If container a crashes, it should not have an impact on container b because they're logically separated. So containers are wonderful, high performance, low overhead, and another form of computing.
Now on the data center, we've got Kubernetes, we've been using it for a while. In the cloud, we still have Kubernetes, we can use the elastic Kubernetes service with AWS, we could be using Red Hat OpenShift. For example, we could be using the Azure Kubernetes service, the Google Kubernetes engine.
And there we go, we've got managed Kubernetes orchestration systems in the cloud. But guess what, whether we want to run a Kubernetes cluster off of virtual machines, we can do it in the cloud, just like the data center or with a cloud, we've got managed services, things for these things. But now you know, Kubernetes, or containers and container orchestration, it's been around, it's the same thing in the datacenter.
Maybe it's running Kubernetes, maybe it's running OpenShift, which is kind of the same thing. We're in the cloud, like I said, elastic Kubernetes service with AWS, Azure Kubernetes service with Azure and Google Kubernetes service with Google, same thing. Let's not get fire from what we really started. And we know all clouds. Now it's not the name of the service and how to configure it. It's not cloud, all clouds.
They're all this. So now let's talk about one of my favorite devices, the load balancer. Why do I love load balancers, load balancers increase performance, and availability, wow, performance and availability in the same device? Load balancers are really cool.
So why do load balancers do this? And how do they work? Well, a load balancer distributes the load across multiple devices. So by sharing the load across multiple devices, we remove single points of failure. Imagine having one server it fails. Guess what? Let's assume this is a web server websites down. Now, how many businesses want their website down? Not many. So if they had us two smaller servers instead of one bigger server, and one of those small web servers went down, guess what, we still have another web server.
So the point is, we use load balancers to improve performance and availability. Now we've got two kinds of load balancers. As a rule, we have network load balancers, and we have application load balancers. And whether you're dealing with a physical device, like the f5, load balancer, or a virtual load balancer, it doesn't matter.
They all work the same way. So I want you to understand what is a load balancer? A load balancer is a device or a logical device, it doesn't matter that will take your traffic and distribute your load load. Now let's talk about how they work. Why do we use network load balancers because they're really fast. We use network load balancers to load balance usually between big bad servers, like 128 core card or between firewalls, or between network devices. So we use network load balancers when we need speed, wire network load balancers fast.
Let's talk about how they work. You basically have your when you deal with your OSI model, you've got layer four, which is your TCP and UDP, your transport. And what's going on is this load balancer, it looks at layer four, the the tight the protocol, TCP, UDP, the source and destination addresses.
And they are really fast. They send the data through as fast as possible in out and out. And it's fast. And that's all use network load balancers. Why are they fast, they don't have to do a lot of work. The computations are simple.
Imagine if we decided to do two times two all day long 248 1632 64 128. You know, you get to the point, if you wanted to do something like that, it's pretty easy now, not to do that with calculus, we're gonna get really slow, really slow, because we have to slow it down to process it. Now let's look at the application load balancers. When do we use them? When we need intelligence, when we need deep packet inspection when we want to have intelligence and our routing? So now we've got an application load balancer.
It's not fast. It can't be why can't it be it's doing a lot. It's smart. It's looking at layer seven.
It's looking at an HTTPS header, for example. And it's looking at the protocol on the source and the person they get and all this information and the headers. And by that it's going to make an intelligent decision. So because of that it is really slow.
Now on the data center, we typically get load balancers. I've often use them from f5. But there's other load balancer vendors.
And these are great devices in the cloud. We also have load balancers and guess what kind of we have network load balancers and application load balancing The same as we have in the data center, but on the cloud another logical. So if we wanted to get a network load balancer in the cloud, we get it from all of them. But when we're dealing with AWS, they call their load balancers, elastic load balancers, Azure calls their load balancers, Azure Load balancers, and Google calls their load balancers, cloud load balancers, and guess what their load balancers and you can select between application and network just like any other load balancer. But in the network in the data center, learn the cloud.
Now, you know, the load balancer and the data center. And guess what you now know what in the cloud. Now let's discuss storage. When we discuss storage, we're going to describe the three kinds of storage we're going to find in the data center, object storage, block storage, and file storage. And guess what, these are the same types of storage we're going to find on the cloud.
We're going to teach you how they work and why you would use each one. And we'll teach you what they're called and the data center and for their from there, we'll teach you what they're called on each of the cloud providers. So that way, you know that cloud, instead of just merely the name of a cloud provider service, we're how to configure it. So now let's talk about object storage. Object Storage is widely used in the data center, and the cloud. And object storage is an exceptional type of storage.
But object storage is not like regular storage. See, object storage is the type of storage area network. So what's going to limit its speed and performance, then network. So first, you have to remember, it's network based storage. Now object storage you also have to understand is only good for a write once read many time environment, you can't use it like a local harddrive.
servers don't mount object storage, like a regular drive. Object Storage is used for backup and archival purposes, sharing and distributing software, sharing images and videos, those types of use cases, object storage is not traditional storage. The reason object storage can't be used as traditional storage is the way object storage functions.
See objects stored anytime an object gets touched or modify by even a minimal percentage of a percent. It creates a new version. So imagine you had a computer that had a swap file, that's a terabyte big. And imagine that swap file was modified by the operating system 1000 times per minute, well, then you would have 1001 terabyte objects sitting in your object storage inside of a minute, that would fill up your systems. And obviously, that doesn't work. So to better understand object storage, let's talk about how it works.
The way object storage works is as follows. We have data, we always have data, but we break that data down into something called an object. Now, when we break the data down into these cool objects, we actually create something called metadata, which is data about the data. And because we have data about the data with object storage, we can do some really cool things. So for an example, we can search for our data or query for it.
Because we've got this metadata, we might only need to retrieve part of an object instead of the full object and save time and networking performance and bandwidth. See, object storage gives us this information. But as I mentioned before, object storage is not traditional storage, it doesn't do well with things that are changed. So object storage is used for white write once, read many times. Now the last thing about object storage is it's fantastic for big data environments.
And why? See object storage has metadata, which means you can take that metadata and use it for the creation of data lakes, and other big data environments. So object storage, fantastic storage platform, highly scalable, highly scalable, but right once read many times, not matter used by computers, used to back up used to share information and used to create big data environments. Now, in the data center, we call it object storage. Where that comes from Dell, EMC or IBM, it's I object storage. But on the cloud, the cloud providers have to make up their own names.
So with AWS, you're dealing with s3. With Microsoft, you're dealing with Azure Blob. And with Google, you're dealing with Cloud Storage. But guess what, it's object storage, and it works and feels the same on all of these clouds. It doesn't matter which college you're on. So learn object storage.
That's what we talked about it. And you'll be good to go as a multi cloud architect, multi cloud engineer. Now the next type of storage we're going to talk about is block storage. Now block storage is a different type of storage area network technology, which guess what takes your data and breaks it down into blocks. Now, because block storage is also network storage, the fastest throughput you'll get will be limited by your network speed, your network card speed your network interface mean, so keep that in the back of your mind. Now why do we use block storage and why do we love it? Well, with block storage, we take our data and break it down into blocks.
But what's so interesting about block storage is we can place these blocks anywhere in our storage area network, so it doesn't have to be attached to the server, it can be anywhere that we've got IP connectivity to, or network connectivity to. So as such, block storage, totally decouples, the servers, or the compute on the storage, which means you can scale scale scale scale scale. So box stores as a brilliant form of a storage area network, especially in the cloud environment. Now, block storage isn't fast. Even though the cloud providers, I want to tell you how blazingly fast it is, it's not, it's the fastest of the cloud storage, but it's much slower than the kind of storage that's actually in the server themselves. So whenever we're dealing with the servers and the cloud providers, we basically get some form of instance, storage, maybe called ephemeral storage, or instant storage, but what it is, it's the storage that comes in the server.
But in the cloud, unfortunately, the the storage and the server or that instance storage, so that ephemeral storage, whatever want to call it doesn't survive instance, termination, etc. So because of that, we can have storage, which goes away, if we lose the server. So we use block storage in the cloud, for those reasons, block storage as the best performing storage. Although it's not the fastest storage the best we're going to get in the cloud.
Now, in the data center, you may see block storage plugged in via Fibre Channel card. And if we go to the club biters data centers, we may still see that of course, we can also see them being plugged into the IP network using IP network protocols for block storage as well. So now you know why we use block storage, we use it because it feels like a harddrive.
Even though it's not, it feels like this local file storage, even though it's not, it feels like the hard drive in the system, even though it's not. That's what we use in the cloud environment. And that's why block storage is ubiquitous. Now, if we call Dell, EMC or IBM, we buy block storage, but we go to the cloud, guess what, of course, the cloud providers have to come up with their own fancy names for this data center technology. So AWS calls it elastic block storage, Azure calls it Azure disk storage, and Google calls it a persistent disk. Here's the thing, it's the same thing.
It's block storage, it's what we use to mount to our servers. Because it feels like a harddrive that's local, even though it's over the network. Now, let's talk about the last kind of storage, which I'm sure you're familiar with file storage. Got a hard drive in your computer, you've got file storage, and you're using it.
Now with regards to file storage, you store files, okay? Now, file storage could be local to your computer and its hard drive. Or it could be on something called the file server. So most organizations, they have file servers.
And if you're on a Windows system, you map to the network drive, you make it look like a drive letter, and you store and retrieve things from the files. And why do you do that? It's stored on the server and not your computer, which means other people, your same company can access the data that you save. That's why we use File service servers.
So let's say for example, we had 10 Unix servers that all needed access to the same information at the same time to do job, we would need file storage. Now, we could have 10, Windows servers that also need to access this file, sir, that would also be file servers. So now you know what the point of that is. Now, when we use file storage, there's basically two protocols we use. If we're dealing with Unix hosts, or Linux hosts, we're dealing with the network file system for file storage invented by Sun Microsystems a long time ago, if we're dealing with Windows systems, we're dealing with Server Message Block, file storage and file storage protocols. That's it.
So NFS, for that friend for the Linux and UNIX, Windows uses Server Message Block or SMB. So now you know, but guess what, if you're in the cloud providers, they have file servers for you, too, that are fully managed. Or guess what you could create your own file server by creating a virtual machine, attaching a block storage to it and then creating a file share.
But let's talk about them managed storage servers of the providers have. AWS has the elastic file system, guess what? That is file servers for Linux and Unix systems. It's just like suns network file system. Guess what, we have Azure Files, that's files, file sharing services on the Azure Cloud. And with Google, we have Google file store. So now you know about object storage in the data center and the clouds block storage in the data center on the cards, and file storage and the data center and the cloud.
Why don't we talk about today we talked about server virtualization, and how it works. We talked about containers, and how it worked, where they work. We talked about load balancers, the type of load balancers how they worked in the network, data center, of course, the cloud. And we talked about file storage, how it works in the network and the data center on how it works in the cloud. And if you want a cloud architect, job solution, architect job or good cloud engineer job, it's great for you to know these things know the cloud, and you work and work anywhere you desire.
I'm Michael Gibbs. I'm the founder of CEO and CO called careers and I want to help you get cloud hired. are called promoted. I look forward to seeing you in another video coming very soon.
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This is Michael Gibbs from go cloud architects.
2022-03-13