Understanding The True Potential Of Containerization
Do you want to know about containerization? Whenever containers are mentioned, most people tend to default to something like Docker or even Kubernetes these days. But container technology has been around for quite some time.
It was back in 2008 that the Linux kernel introduced C groups or control groups that paved the way for all the different container technologies we see today. That includes Docker, but also things like Cloud Foundry as well as Rocket, and other container runtimes out there. Let’s get started with an example we’ll say that you are a developer and you have created a Node JS application and want to push it into production.
We’ll take two different form factors to kind of explain the advantages of containerization. So, let’s first talk about VMS And then we’ll talk about containers.
Construction Of VMS And Containers
1. Background
We’re going to talk about the difference between virtual machines and containers. But before we talk about the difference between the two, let’s go back and talk about how things were before VMs and containers. So, the traditional way that a company or a business operates is by having applications running on servers, and each server would just have one application running, whether that application is running a website, a database, or e-mail.
So, it would be one application on one server. This was because the operating systems on these servers, such as Linux and Windows, couldn’t run multiple applications securely on a single server. So, with the new applications that a business or a company offers, they would have to buy a new server for it.
On top of that, the application wouldn’t be able to use the server to its full compatibility. It would only use 10 percent of the server’s capability because servers today are powerful. It is reported that oftentimes the server is only running at the bare minimum of its capacity. So, running a single application on only a single server turned out to be a big waste of money. So, to cope with this problem, engineers developed VMs.
2. VMS
Virtual Machines is a developed machine that allows multiple applications to run on a single designated server by hardware and software. So, for example, if a company had three servers running one application each, those three applications can be run on a single server by simulating those 3 servers and their applications by creating three virtual machines.
So now this one server is running three virtual or software-based machines. It runs all the different operating systems and applications such as databases, web services, and e-mail. They’re all running side by side on one machine. So, to create a virtual machine you need hardware that creates the server, and then on top of that, you need a software called a hypervisor.
A hypervisor is what allows one machine to run multiple virtual machines. It’s what allocates and controls the sharing of a machine’s hardware. Some common hypervisors are VMware ESXi, Citrix XenServer, and Microsoft Hyper V, and on top of the hypervisor are the virtual machines, and each of these will have its operating systems such as Windows, Linux, and Unix, and then on top of the operating systems.
The applications that these machines are going to be running. So, as you can see, virtual machines solve the problem of wasting money on new servers. But as great as they are, they do have some drawbacks.
Drawbacks Of Virtual Machines
one of them is that VMs can consume a lot of disk space, and this is because each VM has its dedicated operating system and because they have their operating system,
VMS also consumes a lot of RAM and CPU power from the server that could be used for other processes.
VMS are slow to start up because since they have an entire operating system, they do take time to boot up.
Each VM also requires a license for the operating system which costs even more money.
Containers
Now let’s talk about containers. Now containers are like VMS, but the major difference is that where VM simulates an entire machine, containers only contain an application. A container is an application that’s been packaged with all the files, configurations, and dependencies necessary for it to run, which means that it’s bundled with everything that it needs to run on just about any computing environment without having to add anything else to that computer.
So for example, if a developer created a website and they wanted to distribute that website so it can be hosted on just about any other computer, they can create a container for that website by bundling it with everything it takes for it to be hosted on another computer, such as the libraries, HTML code, scripts, web images, and web server software.
Then that container image can be distributed and hosted on just about any computer or server without adding any additional software or doing any configuration. The container has everything it needs to run that website, all in a convenient little package which is amazing, and the leading software that is used to create, manage, and run containers.
It is docker, it can run on Linux and Windows on its machines. So just like VMS, to create containers you start with hardware such as a server, and then on top of the hardware is an operating system such as Linux. Now instead of a hypervisor, containers will use a container engine. A container engine is what unpacks the container files and then hands them off to the core of the operating system, which is the kernel.
Difference Between VMS And Containers
So, as we have stated before, the major difference between containers and virtual machines is that each VM contains an entire operating system, which makes their file size larger, which is why they are slower to boot up. But on the other hand, containers don’t.
The containers share the underlying operating system that’s on the server between them. Containers only contain an application, which makes their file size much smaller. This is why containers are considered lightweight, which also makes them lightning-fast.
So, while VMS can take minutes to boot up, containers take milliseconds. Containers also consume less RAM and CPU power from the server than VMs. Now. VM files and container files are portable, which means that you can move them easily to different machines. But container files are a lot smaller which makes them ultra-portable.
Drawbacks Of Containers
Now, containers do have some disadvantages when compared to virtual machines.
One disadvantage is that the container file or image must be packaged to work with the same operating system of the server that is running. So, if the server’s operating system is Linux, then the container file must be Linux-based. If the operating system is Windows, then the container must be Windows-based but with Virtual machines. This isn’t a problem. A VM can run any operating system at once.
Another disadvantage is that since the containers share the underlying operating system between them, that means that if the operating system on the server crashes, then all the containers will go down.
So, you can. You see that both VMS and containers are amazing technologies. Some organizations use both technologies on the same machine where they would have a server running VMS and inside those VMS, they would be running containers utilizing maximum productivity. But Docker containers are clear. This is the future because merging them both decreases their size exponentially, making it the best combination of portability and speed.
1. Construction Of a VMS
So, first things first, let’s introduce some of the things that we’ve got here. So, we’ve got the hardware itself, a big box, and we’ve got the guest or rather the host operating system. As well as the hypervisor. Hypervisor is what allows us to spin up VMS. Already we’ve taken a considerable amount of shared pool of resources with the host OS and hypervisor.
We’re going to assume that some of these resources have already been consumed. Next, let’s go ahead and take the JS application and push it in. To do that you need a Linux VM and in this VM, there are a few things to note. So, we’ve got another operating system in addition to the host OS. It’s going to be the guest OS as well as some binaries and libraries.
So that’s one of the things about the Linux VM set, even though we’re working with a lightweight application to create that Linux VM, we must put that guest host there and a set of binaries and libraries. So, that bloats it out. We think the smallest node JVM that we have seen out there is 400 plus megabytes. Whereas the Node JS runtime and app itself would be under 15 megabits.
So, we’ve got that, we’ve got to push the JS application into it. Just by doing that alone, we’re going to consume a set of resources. Next, let’s think about scaling this out. Right, so we’ll create two additional copies of it. And you’ll notice that even though it’s the same application, we must use and deploy that separate guest OS and libraries every time.
And so, we’ll do those three times. By doing that, essentially, we can assume that for this hardware. We’ve consumed all the resources. There’s another thing that we haven’t mentioned here, but this JS application if you have developed it on your MacBook, so when you pushed it into production to get it going on the VM you will notice that there were some issues and incompatibilities, this is the kind of foundations is a big issue where things might be working on your local machine and work great, but when you try to push it into production, things start to break and this gets in the way of doing Agile, Develops.
2. Construction Of Containers
When you use something like containers, there’s a three-step process when doing anything container-related work, like pushing or creating containers, and it almost always starts with a manifest, something that describes the container itself.
So, in the darker world, this would be something like a Docker file, and in Cloud Foundry this would be a manifest channel. Next, which we’ll do, is create the actual image itself. So, for the image, if you’re working with something like Docker, that could be something called a Docker image. If you’re working with Rocket, it would be an ACI or application container image.
You know, so regardless of the different containerization technologies, this process stays the same. The last thing you end up with is an actual container itself. You know, that contains all the runtimes, libraries, and binaries needed to run an application. That application runs on a very similar setup to the VMS. But what we’ve got on this site is a host operating system.
The difference here is Instead of a hypervisor, we’re going to have something like a runtime engine. So, if you’re using Docker, this would be the Docker engine, and different containerization technologies would have a different engine. Regardless, it’s something that runs those containers. Again, we’ve got this shared pool of resources, so we can assume that that alone consumes some set of resources.
Next, let’s think about containerizing this technology. So, we talked about the three-step process. We create some docker files, we build out the image, we push it to a registry, and we have our container, and we can start pushing this out as containers. The great thing is these are going to be much more lightweight, so deploying out multiple containers.
Since you don’t have to worry about a guest OS this time, just have the libraries as well as the application itself. So, we’ve scaled that out three times, and because we don’t have to duplicate all those operating system dependencies and create loaded VMS, we will use fewer resources. So, scaling that up three times. We still have a good number of resources left.
Introducing a 3rd Party Cognitive
Next, let’s say you decide for this JS application, let’s take advantage of a third party. Let’s say a Cognitive API to do something like image recognition. So, let’s say that we’ve got ours. Third-party service and we want to access that using maybe a Python application.
So, to access that third-party APIs and with our node JS application, we want to access that Python app to then access that service. If we wanted to do this in VMS, you may be tempted to create a VM out of both the JS application and the Python application because essentially that would allow you to continue to use the VMS that you have.
But that’s not truly cloud native Because if you wanted to scale out the JS but not the Python app, you wouldn’t be able to as they are running in the same VMS. Do it in a truly cloud-native way. Essentially, you would have to free up some of these resources, get rid of one of these VMSs, and then deploy the Python application in it instead. And you know that’s not ideal.
But with the container-based approach, what we can do is simply say, since we’re modular, we can say, OK, just deploy one copy of the Python application. So, we’ll go ahead and do that. There’s a different color here. And that consumes a little bit more resources and then with those Resources, the great thing about container technology is that the left-over resource becomes shared between all the processes running.
Another advantage if these container processes aren’t utilizing the CPU or memory, all those shared resources become accessible to the other containers running within that hardware. So, with container-based technology, we can truly take advantage of cloud-native-based architectures.
So, we talked about things like the portability of the containers, talked about how it’s easier to scale them out, and then overall with this kind of three-step process the way we push containers allows for more agile DevOps and continuous integration and delivery.
Conclusion
So, you can. You see that both VMS and containers are amazing technologies. Some organizations use both technologies on the same machine where they would have a server running VMS and inside those VMS, they would be running containers utilizing maximum productivity.
But Docker containers are clear. This is the future because merging them both decreases their size exponentially, making it the best combination of portability and speed. So, we have talked about things like the portability of the containers and the uses of their lightweight, talked about how it’s easier to scale them along with the example of VMS and inclusion of 3rd Party cognitive. We have provided you with all the information related to the use of containers and the value of containerization.
FAQs
What Is a Container And VMS?
1. VMS
Virtual Machines is the type of machine that uses multiple applications to run on one server by hardware and software. So, if a company has three servers running for one application, those three applications can be run on a single server vise known as a virtual machine.
This can be done by those 3 servers and their applications by creating one virtual machine. So now this 1 virtual machine server is running three virtual or software-based machines. It will run all the different operating systems and applications.
2. Container And Containerization
Now let’s talk about containers. Now containers are like VMS, but the major difference is that where a VM is an entire machine, containers only contain an application. A container is an application with all the files, configurations, and dependencies necessary for it to run. So for example, if a developer created a website and wanted to distribute that website so it can be hosted on just about any computer, they can create a container for that website. it
What Are The Advantages And Disadvantages Of VMS And Containers?
1. Disadvantage Of VMS
One of them is that VMs can consume a lot of disk space, and this is because each VM has its dedicated operating system and because they have their operating system. VMS also consumes a lot of RAM and CPU power from the server that could be used for other processes. VMS is slow to start up because since they have an entire operating system, they do take time to boot up. Each VM also requires a license for the operating system which costs even more money.
2. Disadvantage Of Container
The disadvantage is that the container file or image must be packaged to work with the same operating system as the server that is running. So, if the server’s operating system is Linux, then the container file must be Linux-based.
If the operating system is Windows, then the container must be Windows-based but with Virtual machines. This isn’t a problem. A VM can run any operating system at once. Another disadvantage is that since the containers share the underlying operating system between them, that means that if the operating system on the server crashes, then all the containers will go down.
3. Advantages Of VMS
The disadvantage is that the container file or image must be packaged to work with the same operating system as the server that is running. But with Virtual machines. This isn’t a problem. A VM can run any operating system at once. Another disadvantage is that since the containers share the underlying operating system, that means that if the operating system on the server crashes, then all the containers will go down.
4. Advantages Of Container
Each VM contains an entire operating system, which makes their file size larger, which is why they are slower to boot up. But on the other hand, containers don’t. The containers share the underlying operating system that’s on the server between them. Containers only contain an application, which makes their file size much smaller.
This is why containers are considered lightweight, which also makes them lightning-fast. So, while VMS can take minutes to boot up, containers take milliseconds. Containers also consume less RAM and CPU power from the server than VMs. Now. VM files and container files are portable, which means that you can move them easily to different machines. But container files are a lot smaller which makes them ultra-portable.
How Can I Utilize The VMS And Container In a Third-Party Cognitive?
Next, let’s say you decide for this JS application, let’s take advantage of a third party. Let’s say a Cognitive API to do something like image recognition. So, let’s say that we’ve got ours. Third-party service and we want to access that using maybe a Python application. So, to access that third-party APIs and with our node JS application, we want to access that Python app to then access that service.
If we wanted to do this in VMS, you may be tempted to create a VM out of both the JS application and the Python application because essentially that would allow you to continue to use the VMS that you have. But that’s not truly cloud native Because if you wanted to scale out the JS but not the Python app, you wouldn’t be able to as they are running in the same VMS.
Do it in a truly cloud-native way. Essentially, you would have to free up some of these resources, get rid of one of these VMSs, and then deploy the Python application in it instead. And you know that’s not ideal.
With the container-based approach, what we can do is simply say, since we’re modular, we can say, OK, just deploy one copy of the Python application. So, we’ll go ahead and do that. There’s a different color here. And that consumes a little bit more resources and then with those Resources, the great thing about container technology is that the left-over resource becomes shared between all the processes running.
Another advantage if these container processes aren’t utilizing the CPU or memory, all those shared resources become accessible to the other containers running within that hardware.
How Is a VMS Constructed?
So, first things first, let’s introduce some of the things that we’ve got here. So, we’ve got the hardware itself, a big box, and we’ve got the guest or rather the host operating system. As well as the hypervisor. Next, let’s go ahead and take the JS application and push it in. To do that you need a Linux VM and in this VM, there are a few things to note. So, we’ve got another operating system in addition to the host OS.
It’s going to be the guest OS as well as some binaries and libraries. So that’s one of the things about the Linux VM set, even though we’re working with a lightweight application to create that Linux VM, we must put that guest host there and a set of binaries and libraries. Next, let’s think about scaling this out. Right, so we’ll create two additional copies of it. The advanced method is mentioned above.
How is a Container Constructed?
When you use something like containers, there’s a three-step process when doing anything container-related work, like pushing or creating containers, and it almost always starts with a manifest. So, a Docker file and Cloud Foundry would be a manifest channel.
Next, which we’ll do, is create the actual image itself. The last thing you end up with is an actual container itself. You know, that contains all the runtimes, libraries, and binaries needed to run an application. That application runs on a very similar setup to the VMS.
The difference here is Instead of a hypervisor, we’re going to have something like a runtime engine. Next, let’s think about containerizing this technology. The great thing is these are going to be much more lightweight, so deploying out multiple containers. Since you don’t have to worry about a guest OS this time, just have the libraries as well as the application itself.
What Is The History Of Containers And VMS?
let’s go back and talk about how things were before VMs and containers. So, the traditional way that a company or a business operates is by having applications running on servers, and each server would just have one application running, whether that application is running a website, a database, or e-mail.
So, it would be one application on one server. This was because the operating systems on these servers, such as Linux and Windows, couldn’t run multiple applications securely on a single server.
So, with each new application that a company or a business offered, they would have to buy a new server for it to run on. On top of that, the application wouldn’t be able to take full advantage of the server’s capability because modern servers today are so powerful that oftentimes the server is only running at 10% of its capacity. So, running one application on one server turned out to be a big waste of money and on the server’s full potential. So, to fix this problem, engineers developed Virtual Machines.