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Pass Amazon AWS Certified Cloud Practitioner Exam in First Attempt Easily

Latest Amazon AWS Certified Cloud Practitioner Practice Test Questions, Exam Dumps
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Amazon AWS Certified Cloud Practitioner Practice Test Questions, Amazon AWS Certified Cloud Practitioner Exam dumps

Fundamentals of Cloud Computing Platform

1. Introduction to Cloud Computing

Hey everyone and welcome back. In today's video, we'll be discussing the introduction to cloud computing. Now, cloud computing has become one of the major buzzwords that you will see in any organization that you are working with. Now, earlier, people used to assume that cloud computing would only impact the system administrators or the DevOps guy because it would change the way they provision the servers, the way they do networking, et cetera. But that is not the right case. Cloud computing has not only impacted the system administrator, but it has also impacted the software developers. It has impacted the security engineers, the auditors, and even the programmer managers. So recently I just got a call from one of my colleagues, he is a software developer.

So he just said, hey Steve, can you just suggest the right path to do the cloud certification? Because in any organization that he's applying to, everyone has a mandate for a developer to have knowledge about the cloud services. And he is actually going to start his cloud certification just for that. And many of the cloud providers like AWS have a dedicated certification specifically for developers as well. So this basically tells on how much impact cloud computing has made in today's organizations. So before we go ahead and understand more about what cloud computing is, it is necessary for us to step a little back and see what was there before cloud computing really came into the big picture. So let's go ahead and understand that era.

So let's discuss the use case where the data centre era was really prominent. Now there's a requirement that your company wants to host the website. Now, typically, if you want to host a website, you will need a server, and within the organization, it is the responsibility of the system administrator to take care of the entire server provisioning, et cetera. Now, the system administrator will have a responsibility associated with this requirement, and he needs to arrange the following things. The first one is that he needs to choose either between a data centre or a hosting provider. Now, typically, if you go to a data center, you can either buy your own server or you can go ahead and rent one that has been provided by the data center.

If you are going with the hosting provider, you pay for the server on a monthly basis. So let me quickly show you this. So currently I'm in my ebay andyou see this is a physical server. So I still remember that time in my first organization, where I used to work as a system administrator, and we had a similar requirement there that a new website needed to be created. So the first thing that we went shopping for was a server, and we were discussing which was the right server that we needed to buy. And this, in fact, takes a lot of time. This is one approach in which you can either buy the server or rent it from the data center.

Also, the second option is that maybe you can go ahead with the hosting provider. So in the case of a hosting provider, what you basically do is pay for the server on a monthly basis. So if you see this MG 256, it has the following specifications and it starts at $365 per month. So you basically pay on a monthly basis, or it's typically one of the very famous providers for a dedicated service. And now also they have moved to cloudier. So it really shows the impact cloud computing is having everywhere. Now, after you decide that you are going for the server or for the rent, the second part that typically used to happen was to send the inquiry. Now typically once you decide that you are going for the specific server or specific data center, you typically have to send the inquiry towards the datacenter on what would be the cost associated. Because if you typically look into the data center, a data center can have hundreds of thousands of servers, and it's not just that you put the server within a stack; you also need to have a networking part.

Also you need to have an internet connectivity, you need to have a proper cooling system so that your server do not get heat up. You need to have a proper power backup because if the power goes out, your server will go down, and that will impact your website. And there are a lot of factors that are involved if you are hosting your server in a data center. So all of those inquiries about the requirements need to be sent to the data center: how much power backup they have, what kind of internet connectivity they have. And once you come up with a data center that you want to go with, then comes the price negotiation. So this entire cycle used to take a lot of time. Now one of the disadvantages of putting the server in a datacenter is that if something goes wrong, you have to run and see what the issue is. So I remember during the first organization, in the middle of the night, when we discovered that our website had stopped working and figured out that there was a problem.

So we had to take a cab in the middle of the night, go to the data center, inspect the server, and realize that there was an issue with the hardware chip related to memory. So we went to the office, got a new memory stick, connected it to the server, rebooted it, and it started working again. So that is a big pain, and I really enjoy it now because most of the organizations have now moved to the cloud and all of these issues are being taken care of by the cloud service provider. Now, in order to differentiate between the datacenter model and the cloud service provider model, let's understand this with a simple example. Now let's say that due to a big promotion, your server capacity needs to be increased from four Ram to 32GB Ram. Now, if you are in a data center, what you need to do is buy a 32GB RAM stick from eBay, Amazon, or whatever source you have, go to the data center, and install that RAM stick within your server. So that is the first way. In terms of hosting providers, if you choose OVH, you will typically need to open a support ticket, and you can expect a response time of 15 minutes to 12 hours.

And then you get the data center guys to resize your server, depending on the requirements that you have. And in the cloud, all you do is stop the server and change the instance size. That takes less than 1 minute, or close to 2 minutes, to do that. So let me quickly show you this. So I'm in my AWS management console and you see I have one server which is present, which is KP Labs One. Now this server is of type T-2 micro, which basically means that it has 1 GB of RAM. Now, if I want to change the size, let's say I want a 64 GB RAM or even a 256 GB RAM, all I have to do is go to Actions, go to Instance Settings, change instance type, and here I can just select which instance type I want.

So if you typically see this specific instance type, which is 524 bytes large, this is like 768 GB of RAM. And as soon as I click on Apply, my server will be changed from 1 GB of RAM to 768 GB of RAM within just less than 1 minute. And this is the true power of cloud computing. And this is the exact reason why a lot of organizations are now moving to cloud computing way. Now, going by the definition, cloud computing is a model in which computing resources are available as a service. Now, in order to understand cloud computing, there are three important characteristics that you need to understand about a typical cloud service provider. Now, the first one is on demand and self service.What this basically means is that a customer should be able to launch things without manual intervention. Now, typically, if you look into the older approach where you have a hosting provider and you want to change the instance type of a dedicated server, you have to raise a ticket to the team, and they will respond maybe in 15 minutes or 12 hours, or if it's a weekend, they'll respond after 24 hours. So your manual intervention is required. So within cloud computing, the first characteristic states that it should be self-serviced. Like, if I want to increase from 1 GB of RAM to 30 GB of RAM or 700 GB of RAM, I should be able to do it at my own time without any manual intervention. And this is something that wealready saw in our AWS console.

Like, if I wanted to change the instance app, I could do it right away. Now the second important characteristic of a cloud computing provider is elasticity. That basically states that you can scale up and scale down at any time. So this is a very important characteristic, and basically, it also impacts your cost. So we were discussing the use case where there is a brick promotion. So what this basically means is that the promotion might last for 24 hours. So what you might want to do is, during the 24 hours, increase the capacity of your service, and after the 24 hours are over and your promotion is over, you can scale down to the normal traffic. So that is also referred to as elasticity. The third is measured service. Measured service basically states that you should only pay for what you use. So if you use a 256GB RAM server for 10 hours, then you should only pay for those 10 hours and nothing more.

Now, typically, specifically for OVH, I still remember that you have to just pay $365 per month outright. Even if you just keep your server in a shutdown state for half a month, you will still have to pay the full $365 per month. and this does not really constrain the measured service. You are not paying for what you use. In terms of AWS, if my server is stopped, then my billing will also stop. Then I won't have to pay for the servers that are shut down. I only pay for what I use over here. So along with that, AWS is not the only cloud service provider; in fact, there are a lot of other cloud service providers that are available. And any cloud service provider who is providing cloud computing services has to adhere to these important characteristics, which are demand, elasticity, and measured service. So one of the other very famous cloud providers is Digital Ocean. In fact, this is one of my favorite cloud service providers. Now, if you typically look into the pricing here for one GB of RAM, one vCPU, and a 25GB SSD disk, you pay $5 per month or you pay $0.7 per hour. So basically, you are paying on an hourly basis. Let's say that you use this specific server for 10 hours, after which you terminate it. So you will only pay for those 10 hours. You will not pay for the entire month. And this is what a measured service is all about.

2. Cloud Computing Models

Hey everyone and welcome back. In today's video, we will be going deeper into the area of cloud computing by understanding the cloud computing models. So let's get started. So there are three types of cloud computing models that are available via this software as a service. The second is platform as service, and the third is infrastructure as service. Now, "software as a service" is basically whatever software that you are running. Let's say Microsoft Office is something most of you might be familiar with. Now typically, Microsoft Office is something that you would have to install on your laptop, and you also have to look into the system requirements of Microsoft Office.

And if your laptop does not suffice to meet the system requirements, you will not be able to use it. And along with that, if you're using a different kind of operating system like Linux, then Microsoft Office is not really supported. So what happens in the software-as-a-service model is that you can run your software in terms of a service, and it can be typically accessible via a web browser. So one of the examples for that is Google Docs or Office 365. Let me quickly show you this. So here you see, I have Microsoft PowerPoint up and running, and this is completely within my browser. Now if I want to use Microsoft Word or Microsoft OneNote, then I can use it directly from here. So let's switch to Word now, and you can see you have a perfectly working Word over here. Now, one of the great things about this type of model is that you don't really have to worry about whether your laptop will support it or not, or whether your operating system will support it or not.

All you need is a browser here, and you can definitely pay on a monthly basis for these services. Along with that, you don't really have to worry about upgrading. Let's say Microsoft Office has some kind of security vulnerability, so you have to download the latest patches and all that. You don't really have to worry about all of those things. The cloud service provider, whichever provider is providing you with this type of service, will handle all aspects of upgrading, security, error handling, and so on. So this type of model is referred to as "Software as a Service." Now the second model here is "Platform as Service." "Platform as Service Essentially, if you have, say, a Java application, you now want to deploy that Java application within your server.

So the first thing you'll need is a server. The second thing on top of server you need to have certain packages like Open JDK or Oracle Java, which that platform is required for your application to run. So, again, managing that platform can be challenging because you have to take care of upgrades, you have to take care of security, et cetera. Platform as a service enables you to have the platform ready and available from a cloud service provider. All you have to do is you have to upload your application. That's it. Now, one of the famous examples for platforms a service is Google App Engine. Now, let me show you this as well. So this is Google App Engine documentation. And you see, you have documentation for various languages.

You have Go, Java, Net, and Nodes, and typically if you go into the App Engine console, you can just select the language that you want your platform to be. Let's say you are writing your application in Java. You can just select your platform as Java, and then you can go ahead and upload your application, and it will be up and running. So you don't really have to manage the servers, you don't really have to take care of the platform by itself. All you have to worry about is your application. Now, the third type of cloud computing model, which is used very extensively, is infrastructure as a service. Now, infrastructure basically means server, so it can be load balancers, servers, databases, et cetera. Now, typically AWS, Lineo, and Digital Lotion are some of the very big providers that offer infrastructure as a service. Definitely, if you talk about AWS, it is one of the very big cloud service providers, and it also offers software as a service as well as platform as a service offering along with infrastructure as a service offering as well.

So this is my AWS Management Console, and this is basically the easy console. So you can launch the servers here. And if you typically look at the services that AWS has, they are really vast. So this service ranges from infrastructure to platform as well as software, and depending on what your organisation needs, you can select one of the services that AWS has. Now, typically, when your organisation is moving to the cloud, it is very important that you choose the right cloud provider depending upon your requirements. Now, we already discussed that AWS is one of the most comprehensive cloud providers in terms of service offerings. Now, it basically provides all the type of models. when it comes to AWS. You have software as a service, platforms as a service, and infrastructure as a service. However, there are other good providers as well, like Digital Ocean or Line. They might not provide all of the computing models, but they definitely provide the infrastructure as a service. So you can launch your servers. Typically, you can have elasticity, scalability, et cetera. Now, do remember that if you just depend on AWS for everything, then you will typically lose a lot of money. AWS is a little expensive. You have Digital Ocean and Line Out, which are much cheaper when compared to a S. And it is for this reason that I have seen many startups migrate from AWS to Digital Ocean solely for cost reasons. So again, it depends upon which service you want to use. If you want to use a certain software as a service, which only AWS offers, then you need to stick with AWS. However, you can launch your service on Digital Ocean, and for the software as a service, you can use AWS. So that is more of a hybrid cloud platform, which you can also use.

3. Architecture of Cloud Environments

Hey everyone and welcome back. In today's video, we will be discussing the architecture of cloud environments. Now, if you take a look at the subtitle here, it states that a cloud is not on the clouds. Now, typically, I wrote this subtitle in response to one of the interviews with a minister. So when a media journalist asked him what his concern was with respect to the cloud environment, his concern was what would happen to the data and the servers if it started to rain. So it was quite funny. Anyways, coming back to the topic, let's go ahead and understand more about the architecture of a cloud environment. To your surprise, cloud computing is only available in the backend data center. So this is quite important to understand here.

Let's say that you have a data centre over here that has multiple physical servers. So all of these are the physical servers. Now on top of these physical servers you have the virtualization environment, and on top of the virtualization environment you have the virtual service. So typically, if you talk about infrastructure as a service or any cloud computing environment, virtualization is one of the most important aspects of the infrastructure as a service-based cloud computing model. Now, because of virtualization, you are able to get a lot of benefits because we were discussing some of the important characteristics of a cloud computing environment, which are on-demand and self-service elasticity and paper use. And all of this can be achieved quite easily if you have a virtualization layer. And the cloud service providers typically have a virtualization layer. Which virtualization layers they have now is determined by the cloud service provider.

So there are a lot of virtualization software options available, like VMware, KVM, and Zen. You have VirtualBox and much more. Now, typically, virtualization allows us to run multiple operating systems on a single piece of hardware. This is one of the great benefits that virtualization software allows you to achieve. Now, when it comes to Amazon Web Services (AWS), they are very heavily reliant on Zen. Now they are also moving to KVM. But Zen is one of the very heavily used virtualization layers that AWS has used. Now, let me quickly show you the virtualization part before we conclude. Now, I am running a VMware workstation on top of my VMware workstation. So this is a virtualization layer. So you can consider this server my laptop.

On my laptop, I have installed VMware. You also have various other programs. So this VMware acts as a virtualization layer, and on top of the virtualization layer I can install and run multiple operating systems. So in my case, I have installed a Linux operating system. So, if I quickly do a full screen and an LS IP boot, you can see that we have both the bootloader and the kernel. So this is a full-fledged operating system that is running on top of virtualization. Now, virtualization allows for a great number of benefits. So let's say that I want to change the amount of RAM, the amount of CPU, maybe add a network interface, or remove certain hardware.

You can do it from your virtual console. So let's say I go to VM, go to settings, and go within the memory. Currently, if I want to increase or decrease the memory, this is something that I can do. So I can just type the amount of memory that I want in this present location, and it will scale up or down. Similarly, for processors You can also specify the number of codes and processors that can be assigned to this virtual machine. Now, again, you cannot give unlimited amounts because the hardware itself has limited resources. So whatever it is, depending upon the resources that your hardware has, So let's say you have a server with 1 GB of RAM. So then you can give 900 or 950 GBRAM to various virtual machines that are running. You can even add certain hardware over here. So let's say I want to add a hard disk, and you can add a hard disc over here.

Simply specify a SATA or a scuzzy. And then if you do a net, it basically asks you: What is the maximum disc size that you need? So all of these are basically virtualization layers. Now, typically, if you look into the cloud environment, let's consider the AWS environment. Within the AWS environment, you have similar features; it's just that the way in which you do things would be a little different. So in AWS, let's say if I want to add a hard disk, I go to volumes, I create a volume, I specify the volume size here, I specify the volume type, and I create a volume. So in terms of VMware, you need to go to settings, you have to click on "Add," then you have to select "Hard." The way in which the GUI is designed is a little different, but the overall concept would remain the same across the virtualization layer and AWS at a very high designed is a lSo generally what happens is that I have seen a lot of people who understand the virtualization layer in detail, then they move to cloud environments, and that allows them to understand various infrastructures as a service-based concept in a much faster way because they understand this virtualization layer. As a result, they can better understand cloud computing, specifically infrastructure as a service.

4. On-Demand & Self Service - Characteristics of Cloud

Hey everyone and welcome back. In today's video, we will be discussing one of the characteristics of cloud computing, which is on-demand and self-service. Now, when it comes to on-demand and self-service, one important part to remember is that whenever a person is using a cloud service provider, he should be able to provision resources in the cloud whenever needed without requiring any human interaction with the service provider. This is very important because I still remember many years back, close to seven, eight years back, if you wanted to have some modification, like if you want to have servers from two GB Ram to four GB Ram, we had to raise the ticket, we had to wait for24 hours and sometimes it used to take even more.

So at that there was a human interaction which was present and there was also dependency on the service provider over there. Now, on-demand really makes self-service with automation possible in a seemingly effortless way. But do remember I have also added this as a subtitle here that cloud is not unlimited. We already discussed that the cloud behind the scenes is a data center. So there are servers that are running, and on top of that you have the virtualization layer. When you try to launch the server in AWS, you will frequently see this specific error, which states that the error is starting instances with insufficient capacity. So do remember that even the cloud provider has a higher limit. It may be much, much higher, but there is always a limit, even for the cloud service provider. Now, typically, let me show you this with an example.

Now this is my Linux virtual machine. Now, the amount of RAM, processor, and hard disc space that I can assign to my virtual machine is entirely dependent on how much resource I have on the underlying hardware. So currently, this virtualization layer is running on top of my laptop. Now my laptop has 24 GB of RAM. So that does not mean I can assign hundreds of gigabytes of RAM to my virtual machine. That should not be possible, and that is not possible. So, in a similar vein, when discussing cloud computing, because cloud computing is run in data centers, data centers are servers. The server has RAM; it has a CPU; and it also has a hard disc drive. There are limits to the resources that can be allocated.

5. Characteristic of CSP – Elasticity

Hey, everyone, and welcome back to the Knowledge Portal video series. So, continuing our journey of understanding the characteristics of a cloud environment, today we will be discussing more about elasticity. So we already had our own overview of what elasticity is, but in today's lecture, we'll go a bit deeper and understand more about elasticity, as well as some real-world applications where the elasticity property is used. So, going by a very simple definition again, elasticity deals with adding and removing capacity whenever needed in the environment. So, let's say your organization has a big promotion tomorrow and you're able to scale up and then scale down after the promotion is over. So that property of scaling up and scaling down is generally referred to as elasticity. Now, when we talk about capacity, capacity generally refers to two important components, which are processing and memory.

Now, processing refers to the CPU, and memory refers to RAM. Now, in order to explain elasticity, I generally take a very simple example of a rubber band. So I've got a rubber band over here. So it was not the best rubber band, but it took me like 15 to 20 minutes to find a rubber band. So, what happens when you apply load to the rubber band? It stretches out, and when the load is removed, it returns to its original position. So this particular property of scaling up or stretching out and going back to the original position or scaling down is called the elasticity property. Right? Now, there is one more term called scalability, which is generally used in the cloud environment. So scalability is very similar to elasticity. Now, sometimes these words or these two terms are used interchangeably.

So just make sure specifically that if you're in a cloud environment, you will not find the term "elasticity" being used. You will find the term "scalability" being used. Now, talking about scalability, there are two types of scalability. One is horizontal and one is vertical. Now, this can be best explained with the help of a diagram. What happens in vertical scalability is that we assume this small server you see has two GB of RAM. Now, due to a promotional challenge, there is a capacity increase that needs to be done where the two GB RAM needs to be upgraded to an eight GB RAM server. So what happens in vertical scaling is that this server with two GB of RAM is scaled up to support the eight GB of RAM.

So the RAM requirement of the server has been changed from two GB to eight GB. But still, only a single server is present. Now, what happens in horizontal scalability is that this is a two-GB RAM server. Now, instead of scaling the same server resource to eight GB of RAM, you create three more servers, each with two GB. So you have two GB, you have four GB, you have six GB, and you have eight GB. So in total, you have eight GB of RAM capability. And here, too, you have eight GB of RAM capability. Now, both vertical and horizontal scalability have their own advantages and disadvantages. Now, let's look at the disadvantage of vertical scaling. You are in between promotions, let's say, and you have a single eight GB RAM server. And due to some reason, the server went down. Some malfunctioning happened in the kernel, and the server went down. As a result, the entire website has gone down. Okay? So this is one ofthe disadvantages of vertical scaling.

Talking about horizontal scaling, even if one server goes down over here, you have three more servers available that can support the increase in load. So ultimately, our website is not going down as far as horizontal scalability is concerned. Now, again, horizontal scalability cannot be used in all the applications. So there are applications in which vertical scalability is preferred, for example, databases. So database use cannot generally be scaled out, specifically the master database. So during scalability, I would say during vertical scalability, in applications like databases, vertical scaling is preferred. However, horizontal scalability is preferred for applications such as servers and simple applications found on your server. Now, servers on demand are a real thing.

It is not like a marketing team comes up to you and says, "Okay, tomorrow is promotion." Make sure that all the servers are scaled up. So you manually go and resize the server. So that is the whole thing. The real deal is on-demand scaling. So, as a system administrator or solutions architect, I don't really have to do much. The servers should be configured in such a way that they should scale up or scale down automatically. In this case, if the CPU load exceeds 70%, the system will scale up to two more servers. As a result, whenever the CPU load exceeds 70%, two new servers are added to the horizontal scalability. Now, as soon as the CPU load goes down to less than 30%, the two new servers that were added will be terminated.

So again, this particular scalability is in terms of CPU requirements. You can configure various things, like a network or various other parameters. So, this is a very simple use case scenario. But this type of use-case scenario is generally used in many real-world production environments. So this is a simple auto-scaling configuration. So auto-scaling is one of the services that AWS provides for horizontal scalability. Now here, if you see this, this is the auto-scaling configuration where you have scaled between one instance and five instances. So the maximum scaling that will happen is five servers. And how will the scaling happen? The scaling will happen based on a metric called average CPU utilization. And if the average CPU utilization grows to the target value of 70%, then the scaling will happen from one instance to two, or maybe from two to three. three, four, and five So five is the maximum scaling of servers that will happen.

6. Elasticity - part 02

Hey, everyone, and welcome back to the Knowledge Portal video series. Now, in the previous lecture, we spoke about elasticity. Now, I really wanted to show you one interesting thing, because this is something that will help you. Now that VMware is up and running, I've sent to a server running VMware Fusion. So let me just connect to the sent file on a server. Now, if I just want to see what the available memory is in this particular virtual machine, it is around one GB. So one GB of RAM is available. And if I want to investigate processors, I'll run Catcpu Proc four times.

Okay, you see that I have only one processor that is available. So processor zero. So this is the first processor that is available. So essentially, what I have is 1 GB of RAM, and I have one core processor available in my virtual machine. Now, there is a promotional activity that we have already discussed that is coming up. Now, as far as vertical scaling is concerned, in infrastructure, as a service, under normal scenarios, what happens is that if I want to scale this up, I have to shut down the virtual machine. now, so I'll just show you. So you see, I have 100:24 MB of RAM, and I have one core processor. Now, if I want to scale, or if I want to increase or decrease the resource for the particular virtual machine, you see, I'm not able to do that. And there is a warning saying that the settings on this page cannot be changed until the virtual machine is shut down.

And this is one of the challenges as far as the servers are concerned. So if you want to vertically scale, for example, an EC2 server or a digital ocean droplet, then you have to shut down the server. Then either increase or decrease the capacity and then start the server. So that is one of the challenges that you will find as far as the scalability is concerned. Now, AWS has recently come up with "vertical scaling" as far as RDS instances are concerned. So maybe this will be improved in later years. But as of today, you cannot really scale the servers up or scale the servers down without shutting them down. So let me do one thing. Let me just shut down this particular server. Okay, I'll just say hold. Okay, so the server has shut down. Now, if I go to the virtual machine settings and click, you'll see both of these options are now available. So let me just increase the processor to two cores, and let me increase the RAM to four GB. Okay. Around 4 GB of RAM are there.

I'll close the screen, and I'll start the server again. So the server has started. Let me show you some interesting things. So generally, the messages that you see over here, right, the message is in black color. So basically, you can see that in cloud environments. So in the cloud, you don't really have the console, right? So if you just right-click on a particular server, you go to get the system log, and you will see all those messages present in the system log. Anyways, we'll be discussing this in great detail whenever the right opportunity comes. I just wanted to show you so let me just go to full screen, okay? Let me just type in If I open the terminal, let's see the RAM capacity. Now, if I run a free Hyphen amp, you can see the RAM capacity has been increased.

And also, if I do a Cat Rock CPU info, you'll see that now I have two processors. So this is the processor zero and this is the processor one. So, what we have now is we have two code processor and we have four GB of Ramp. Now, one thing that we have learned is that if we want to scale the servers vertically, we have to shut them down, increase the capacity, and then we have to start the server. Now, as I am showing you in the virtual machine, the same can be applied as far as the cloud environment is concerned. Now, if the servers are shut down currently and you can see it, I can change the instance type from T to Micro to whatever instant type is available over here.

But when I just start this server—let me just start this server—we generally discuss that most of the properties or settings of a virtual environment are replicated in a cloud environment. When I start the server, you see that the change instance type button has been you cannot really click, it has been erased out. So you see, whenever the server is started in a cloud environment or even in a virtual machine as of now, there is no way for you to vertically scale it other than shutting it down, scaling it up, and starting the server after that. So, this is something that I really wanted to show you. I hope this has been informative for you. And due to this challenging vertical scaling, as far as servos are concerned, a horizontal scalability approach is generally used in cloud environments. So I hope this has been informative for you, and I'd like to thank you for bearing with me.


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