Understanding Cloud Computing: A Comprehensive Guide to AWS and S3

Ever had that moment when your phone pops up, storage almost full, and you're like, "Oh, not again." So, what do you

do? You start uploading photos to Google Drive or Google Photos to clear up space, right? Or let's say you're

watching a movie on Netflix or Prime Video. No downloads, no waiting time, and everything just streams smoothly

even in HD. Have you ever wondered how all that works so seamlessly? Well, the answer behind all these is something

called as cloud computing. Cloud computing is the delivery of computing services like storage, servers and

software over the internet instead of your local device. You're not really storing the movies or those photos on

your phone. They are actually sitting on powerful computers somewhere far away and you access them through the

internet. It's like renting space on someone else computer to store your data or run your app. And guess what? In

2025, there is already a huge demand for this technology. Almost 90% of companies in the world consider themselves cloud

first and thus there are lacks of open cloud computing jobs available but the supply of skilled cloud engineers is

still very limited. This course is designed to get you skills and framework to crack cloud computing jobs and

achieve your career's objective. We will take you from the very basics of cloud computing to work on AWS hands-on. So if

you're a student, job seeker or IT professional interested in cloud, don't skip. Watch this video till the end and

take your first step into the future of tech right here on Intellipad's YouTube channel for absolutely free. Let's start

by understanding cloud computing in simple m. Meet Ravi. He's the founder of a small software company based in

Bangalore. His team builds web app for clients. They have just landed a big project, an e-commerce site for a global

site. This sounds very exciting, right? But also scary because Ravi's local infrastructure is very limited. He

doesn't have big servers, high-end GPUs or a fancy data center. And building one would take lacks of rupees, months of

setup and constant maintenance. And still there would be risk against cyber attacks, natural disaster which can whip

around losses for Ravi's company. So what can Ravi do at this moment? He came to know about cloud computing. So what

is this cloud computing? Is it like data center sitting up in the clouds? No. In simple words, cloud computing means you

don't need to own the physical hardware. You rent thing like storage, server and networking over the internet and you

only pay for what you use. And since all these resources sit virtually in the internet and can be accessed with the

use of internet, this way of accessing resources is termed as cloud computing. So simply put, computing that happens

over the internet. Let's break down how cloud computing can help Ravi with his e-commerce project. We will compare what

he would need to do for an on-promise setup versus what can he do on the cloud in any software development project.

Even before Ravi's team write a single line of code for the mobile app, they need to set up a few essential. For

example, a server to run the back end, storage for user data, images and transaction, a secure way to connect

components, a place to test features safely, tools for automatic deployment, and daily backups for recovery, and the

ability to handle sudden spikes in the user. So, let's take these attributes one by one and see how cloud computing

makes Ravi's job 10 time easier than going with physical onremise infrastructure. So first up is storage.

This is where all app data lives. Ravi's app lets user upload profile picture, store order history, save payment

records, maintain session data. So if all this has to be stored on premise, he would need to buy and configure physical

servers, attach hard drives, set up cooling system, and run backup routines all while praying the business doesn't

have a power outage. With cloud computing, Ravi just configures cloud storage units such as AWS S3, and that's

it. It's encrypted, backed up, and instantly available. Next up is compute power. The brain behind the app. So

whenever a user logs in, updates their card or stream a product video, Ravi's backend has to process those action

fast. If it has to be onromise, Ravi would have to buy physical server, install operating system, keep them on

24/7 and upgrade them whenever traffic increases, meaning he will have to buy more hardware. On the contrary, with

cloud computing, Ravi spins up virtual servers on demand using AWS EC2. He pays only what he uses and when the traffic

tips, he shuts them with zero waste. Third on the list is networking. Ravi's apps front end need to securely talk to

the back end using APIs. So if Ravi were to implement network security on onremise setup, he would have to

manually set up routers, install firewalls, open only required ports, and hire someone to monitor the threat. On

the cloud, he just have to configure a VPC, a secure isolated network where only specific services can communicate

with each other. The traffic is encrypted, everything is logged. So Ravi don't have to worry about the threats.

Next up is testing. Let's consider that Ravi has built an app and it's live. But his client wants him to add new refer

friend feature. To do this on premise, Ravi would need to replicate the entire production environment. That means more

servers, cloning the database, increasing the cost, plus the risk of accidental breakoffs. But when done on

the cloud, Ravi could just create a staging server with a click. This new feature is tested without touching the

live app. Once it is approved, it goes live instantly with new update. No drama at all. Fifth point is DevOps and

automation. So let's consider that Ravy's development team commit code every single day. For the onremise

setup, every change would mean someone like specialized DevOps engineer sitting there and doing manually builds, test,

bash scripting and deploying the app which is very slow and then again errorprone. But when relying on the

cloud, Ravi simply integrates GitHub plus AWS code pipeline. Now every code push is auto tested, auto deployed,

monitored in real time. His team focuses on coding, not babysitting the servers. Sixth point is scalability. One day this

e-commerce app goes viral. Suddenly 5,000 user becomes one lakh. If this happens in onprim, there is possibility

that Ravi's fit server might choke leading to app breakdown and clients disappointment. But when things are

worked on the cloud, Ravi could just enable autoscaling. So when the traffic rises, more servers spin in

automatically. When it falls, they shut down to save the cost. Smooth experience for customer. No panic for Ravi and the

happy client. So you see cloud computing in every step proved to be better than that of on premises. That's why almost

96% companies today call themselves cloud first and are using cloud services one way or the other. Building an app

like e-commerce without cloud computing today is like trying to run a race barefoot on broken glass. Cloud

computing is cost effective since it uses pay as you go model and provide services with just clicks whenever you

need. It's fast, it's flexible and is the backbone of modern software development. Moving on, let me walk you

through different deployment models cloud computing providers like AWS, Azure or GCP offer. First up is public

cloud. You can consider it like taking a bus. You don't own it but you share it with others. Public cloud like AWS,

Azure, GCP provide infrastructure over the internet for anyone to use. Most startups and dev prefer this. It's

affordable and easy to get started. Then we have a private cloud. Now think of a private car built and used by one

company only. Private clouds are used by big enterprise needing full control customer compliance or specific security

setup. More expensive but fully owned and operated by one company. Finally, we have the hybrid cloud. A mix of both

public and private cloud. You use public cloud for general stuff, private for sensitive workloads. This is flexible,

cost effective and popular among growing companies. So there you have it. You just understood different type of

deployment models, how cloud computing is better than on-premise setup. You discovered how it's cost effective and

easy to access and manage. You won't wonder now about why Ravi choose cloud computing. By the way, if you're

interested in pursuing cloud computing or DevOps as a career option, we can help you learn more with our strong

curriculumdriven course. You can check out the link in the description to know more. So what is cloud computing? Is it

something like computing over the clouds? Well, not exactly. Cloud computing simply means that you're using

the computing resources, be it your storage, servers or your applications that are already present over the

internet, but you are accessing it all without using a physical hardware like you don't need a separate hardware to

like access your Netflix or YouTube or whatever. You can access it from anywhere and from any device. You just

need your login ID and password. So that is what cloud in action is. Now let's just understand it with a simple life

example. For suppose you have thousands of photos and videos to store somewhere. What you can do is you can either

purchase a hard drive and store it there. But what if the hard drive get crashed or get lost and you have to

carry the hard drive all over with you to access those photos and videos. Now what you can do is you can just put all

those photos and videos into a Google drive that might be already present in your phone. Now what is uh it makes

everything so simple that you can access it from anywhere. Now now you have no worries like if it get lost or you need

some other device for it. So that is cloud in action. So cloud computing simply means that you're accessing all

those computing resources be it your storage or your server databases or apps without owning a physical hardware which

means you are just having the internet and you can access all those things in your laptop or in your device whatever

you are using. Let's take a quick review like where you are already using cloud in your day-to-day life without even

realizing it. First suppose either you are using Google Drive to store your photos online or you're using Gmail to

send or receive emails that are all done on the hosted Google servers or you're using Netflix or YouTube to stream the

daily videos whatever you want or the films that you want to have it all are already present on the servers. You just

have to access it from your devices or you're using Instagram to have like sharing the photos or scrolling the res

all are done using the cloud computing technology. Similarly, we have Zoom video calls to handle via the cloud

service. Now that we have understood that what cloud actually is and with a real life example too. Let's just

understand why do we actually need cloud. First suppose you are going into a new city and you want to roam around

the city, travel around it. So you have two options. Either you can rent a car or you can own a car. But what are the

disadvantages that come after owning a car is if you buy a car you have to pay a lot of upfront fees of course to buy a

car and then you have to pay for the insurance for the maintenance for the fuel and for the repairs that is the

second disadvantage that we have and the very important thing that you might not even use it everyday basis and but you

are still paying for it when it is not in use. Now with a real life example only we can see that if you are not

using it regularly you can just use a Uber instead like you can rent those services. What you have in this you have

no maintenance no upfront cost you only pay when you use it and you can upgrade to a better version whenever you want.

So that is the advantages that we have in the cloud also. What you do you don't need to buy those expensive servers and

manage them. You just need to rent those computing resources whenever you need and stop paying what you don't. So that

is just like Uber. It's flexible, cost efficient and stress-free. So now that we know that how much easier our life is

made using the cloud technology, I would like to tell you that back in the day we didn't have such technology. We used to

sit in a room filled with physical servers where we have to manage each of the physical server even when they are

not in use. And we have few disadvantages along with it. But that's not the point that we exactly jumped

from the traditional IT services to this uh cloud computing. We have one more important thing that is called

virtualization which is a very important topic in our cloud computing syllabus. So let's understand each one of them

step by step and how we came to the cloud computing that is our today's world scenario. For explaining you guys

what is traditional IT or what are the physical servers that we had back in the day. You can just imagine yourself

sitting in a room filled with physical servers and you have to manage each one of them individually. So what were the

problems that we had back in the day was you have to pay a high upfront cost because yes there are so many physical

servers that are present in your room. So of course you have to pay a very hefty amount for that and we have second

disadvantage that is wasted resources. Of course when you're using so many hardwares and some of them are not even

in your use. So what is this? This is the complete wastage of the resources and we have manual maintenance that you

have to manage each one of the servers and you have to take a maintenance for that. So you have a lot of charges and

you have to pay again a lot of hefty amount for that and again it was hard to scale like if you want to manage those

servers from another room you have to carry each one of them individually to another room or to another place. So it

was very hard to scale such technology. So to eradicate such problems that we had in traditional IT service what we

came up with we came up with something called virtualization. Now let's understand what virtualization was. See

virtualization you can understand it. It's like a smart hardware use. Why? Because since back in the day you had

physical servers each one of them having its different OS and you have to have one individual server for accessing one

operating system. Now that you had virtualization, you can split one physical hardware into many virtual

ones. Now let's understand it what does it mean uh using a simple diagram. If you can see this diagram, you will be

able to understand that what is actually happening inside the virtualization. First of all, we have a physical

hardware. Be it your CPU memory or your storage or network, whatever you have, this is a physical hardware that you

have. And just above that there is a virtualization layer in which we have our hypervisor. Now this is the

component that is actually used to split those physical hardware into the virtual ones where you can operate each virtual

system individually just like mentioned here. You can understand it by a simple example. For example, if you are working

in a tech domain, you understand that you are having one laptop and you're running an operating system called

Windows there. But you can also have a similar operating system that is Linux into it. Why? Because that is where

virtualization actually works. Like you can have two different operating system into one device only and you can access

both of them. So that is what a real life example is of virtualization. So let's understand that virtualization is

the process of creating a virtual version of server, desktop, storage, device or even an entire operating

system. It allows one physical system to run multiple virtual machines each behaving as if it was a separate system.

When you are using Windows and Linux both of them in a single device, what's happening? You can use both of them

individually as both of them have different software dependencies but the hardware is able to manage it. Why? All

because of the virtualization that came into the existence. Now the benefits that we had was of course there was a

better resource utilization because we have to have just one physical hardware to run so many operating systems on it.

It was easily manageable as simple as that and it was faster setup than the physical servers of course like to be

filled in a room with the different physical servers each having different maintenance and different type of

operating systems. You can just have a one physical server and maintenance is quite low in this. Now that we had

virtualization back in the day, there was still one more problem that we had that we still needed one physical

hardware to run those virtual ones. So what came into the technology was something called cloud computing that we

are working. Cloud computing simply means anywhere anytime and pay as you go. Why is that? Because for suppose

you're using AWS, Azure and GCP. Some of you might be well aware about it. So when you're using that technology what

you are doing you are just renting those servers or renting those computing powers all over the internet just for

your own purpose and in AWS when you're creating the instances that we will be doing in the videos further what we have

to do we just have to make an instant and we just have to pay the charges as much as we are using it. So that is

cloud but was it was like pay as you go like whatever the cost efficiency you had whatever the budget you had you can

use the computing resources according to that and anywhere and anytime of course you just need a ID password for it and

any device would work any device would be compatible to use it now that we have looked into the picture deeply let's

just compare each of the services step by step like how we went from ownership of like all the physical servers that we

have then to sharing the virtual servers when we add virtualization and how did we come to the complete rental system in

the cloud. So what it looked like back in the day was you have to buy physical servers for the traditional IT servers

of course that we have discussed till now. It was expensive and hard to scale at the same time. So to eradicate this

problem we came up with one device split into multiple virtual ones that was virtualization. You have to run multiple

virtual machines on a single hardware. And what was a limitation? The only limitation that it had was it was quite

flexible at the time of the day. But what was the simple thing that we had still had in the problem was that you

still needed a hardware for it. Like one hardware was still needed for it. So we came up with a simpler thing like the

very simplest thing that you don't even need a physical hardware. Now you can just rent the things and access it as

much as you want. So what is cloud? You just have to rent the services from the cloud providers that we have and you can

use it as much as you want according to your efficient bud budget. So it was most efficient and the modern approach

is cloud only. Now that we have understood like what cloud computing is and why is it so important and how we

moved from owning the complete infrastructure to sharing through virtualization and now renting it using

the cloud computing. So let's dig into what are the core characteristics of the cloud and what makes it so powerful and

so popular among us. You can use it a simple acronym called command that can be used to remember like what all the

characteristics and what all the resources that we have in cloud computing. First of all we have O that

stands for ondemand service. Now what does an ondemand service means? You can just imagine it using something like

Zumato. Like whenever you feel like you want to order something, you just launch the app from your phone. So it's the

simple as that. You just order a food from your Zomato app. So you can launch the server whenever you want. So it's a

on demand self-service criteria that you have. Next we have something called broader access. Now what does broad

network access actually means? See when you are using an Instagram, it's not important that you need to carry your

own device. You can access it from the any device that you want. You just need a mail id and your password. That's what

I'm saying from the beginning itself that the broad network access means that you can upload the files or you can

access the files. You can scroll the re whatever you want all from any device. You just need your identity as your

username and password. Now the next thing that we have that is called resource pooling. What does it mean?

That the cloud provider the groups like shares the storage and memory and CPU among the many users. You can just

understand it like the electricity broadband is shared among lot of people we have in the colony or we have in a

particular home right. So that is what resource pooling means. Next we have elasticity. Elasticity simply means that

it can expand or shrink as a balloon on its own. For suppose many of us are using the simpler server or the single

server that we are uh using. So what happens there is caused a lot of traffic inside it. Okay. So what this cloud does

it automatically add some necessary servers that are used there and it can also just after the traffic is removed

it can automatically just remove the servers when they are not in use. So this is a very important and very

impressive quality that we have in the cloud. Next we have pay as you go for suppose you are just using a 10 GB

memory. So you're paying for that 10 GB only. It's not like you're paying for 100 GB and you're just using 10 GB. So

that's what pay as you go means that you only pay for whatever the resources you want and for how much time you want. Now

that we have understood this let's just example it with a simple real life analogy that what are these things and

how we are using it in our day-to-day life. First of all we have on demand self-service. I just said that you can

use it like ordering an app from Zumato or Swiggy whatever you want. You just uh have on demand like whenever you have

the demand you have that kind of service in front of you. So that is on demand service characteristic and the real life

analogy is ordering a food from the app. Now we talk about broad network access just like Instagram you have something

called Netflix like everyone offers uh like stream on the Netflix platforms. So what happens you can access it from your

TV also and from your device also whatever wherever you are comfortable with. So that is what broad network

access means. Now elasticity just example it or just think a balloon shrinking or expanding on its own

according to your preferences. That's what elasticity means. And when we have resource pooling, it's just like sharing

electricity among the colony or among your home or it's just like sharing a hotel rooms. Like we have lots of people

using the same resources. So we kind of do something called resource pooling. Just like a car pooling like many of you

are going into the similar direction. So just resource pool it. And the next thing that we have called measure

service simply like pay as you go like you pay the electricity or water bill just like as much as you have used. So

simply whenever we are creating we will be creating a EC2 instance next in the video. So wherever we are creating it we

are just paying for the only duration of time where we are using it. So that is another example or the characteristic

that we have for it. So now that we have understood the core characteristics also and what are the all the benefits that

comes with cloud computing. Let's just understand what are the cloud services models that we have and next the what

are the cloud deployment models that we have and the key service providers that we have in cloud computing. Now what are

the cloud service models are they're simply categorized among what they have to offer to the customers or the people

that are using it. And when we talk about the cloud deployment models it just simply categorize itself like how

the cloud models are deployed over the internet. And the service providers are very famous your AWS, Azure and GCP that

are quite popular among all of us. So just start with this next section that is cloud service models. Now that I have

said that cloud service models are categorized among what they offer to you guys, to me and to whosoever is using

those technology. So the there are three types of and three main types of cloud service models that are IAS, PAS and

SAS. Now what does it means? IA is being infrastructure as a service, PA being platform as a service and SAS being

software as a service. Now let's just understand all these type of service models with the help of simple example.

We have a popular term called pizza analogy for understanding all these three terms. Okay. So what we have first

of all we have IAS that is infrastructure as a service. Now for suppose you want to have a pizza and you

want to customize it according to yourself. But for now when we are using IAS infrastructure as a service we need

a entire infrastructure and we need to rent a entire infrastructure. So what does it mean that you are renting an

entire kitchen all the utensils all the things that are present in the pantry and all the things you are utilizing and

you're renting everything like you're renting an entire infrastructure for you to make a simple pizza. In PAS what

you're doing you just saying that I don't need a entire infrastructure now I just need a platform. Now you have

popular outlets of pizza like Domino's and Pizza Hut. So what you do, you just go inside it and you just say that I

want a pizza to be made for myself and I can make it myself. I just need the dough and the toppings with it whatever

you want. Okay. So the platform is completely ready for you and you just need to access it for the pizza or

whatever the services in the computing world you need. Now when we talk about SAS that is very popular and every one

of us are already using it. What does SAS means? that the entire software is ready for you like the pizza is already

ready and you just want to order it by just a call or just using a zumato or swiggy whatever you want to have. So

what do we understand by software as a service that the app or the pizza is entirely ready. Okay. So these were the

things that we had for the cloud service models and let's just start understanding each one of them step by

step by what you get in a particular service and how you handle that and what are the real life examples that we have

talking about the is that is infrastructure as a service it's the kind of a basic building block that we

can say you have the server or storage or networking all you want right in your hand what you get in it you kind of get

a virtual machine like EC2 Azure VM that we'll be discussing in the video further and you have to get a storage like we

have examples of AWS S3 Azure blob that are quite popular among it and the networking. So these are the things that

you get when you're renting an entire infrastructure. Now what do you handle in it? Since you have the entire

infrastructure, you have the entire ownership but you have a lot of work to do also. So first of all what you

handle? You have to handle the entire OS installation that you have to do in the setup. Then you have to do the app setup

and the security patches that whatever you want to have like you have the full access and full control of the entire

infrastructure but at the same time you have to handle a lot of things in it. And what are the real life examples that

we have? We have an EC2 instance of AWS that is a very popular cloud provider. Then we have Microsoft Azure VM that is

a virtual machine. Then we have Google Cloud Compute Engine. Now all these things are kind of a real world examples

that you will be dealing with when you are diving into the cloud technology into deeper. Okay. So the next thing

that we have to discuss in detail is called platform as a service. Now simply as I told you uh what do you mean by

platform as a service is you just have the entire platform ready for you and you just don't need the system set up

but you have to like write the code, deploy the code, you have to make the pizza by yourself. Correct? So that is

what platform as a service is. It is directly made for the developers who want to just focus on their app and not

the system setup. So what you get in it and entirely like installed operating system, pre-installed frameworks and

libraries, runtime environment and autoscaling. Now what does all this means that the entire infrastructure is

already ready in this in IAS you have to like do the OS installation and different type of like you have to set

the environment all by yourself. But not in this in this you have the platform already ready and what you have to

handle it. It's just writing and deploying your code like just you have to make the pizza and take care of the

toppings that you want to have. So what are the real life examples that we have in this is Google app engine, Heroku,

Azure app service and AWS elastic beanto. Now all these are the real life examples again in the technical domain.

If you're working with key cloud providers you will be able to understand this or if not then after some time of

course you will be able to understand this as we go deeper into this conversation. Now that we have we have

software as a service that is our last and the third most important key service model. What we have in SAS it's a

complete ready software ready to use software. You don't have to do anything in this. It's a complete software ready.

No installation and no maintenance needed. You can just assume it like you're using Gmail or Zoom or like Canva

or Instagram whatever the apps you're using. All these comes under the SAS model. Why? Because it's a readyto use

software. You just have to access it. You just need to have a internet link to it and then you can use it anywhere.

What you handle in this of course just using the app via the browser or the application. So the real life examples

that we have are again Gmail, Zoom, Canva, whatever the apps that are already inbuilt in your device and you

are using it directly. Those are the apps are called software as a service. So these were the examples and these

were the features that we had in the cloud service models. So let's just compare each one of them individually.

Right here when we talk about the features that we have in the three service models, you can know that the

control that you have is highest in infrastructure because you have the entire infrastructure in your control.

But when we talk about platform, it's a little bit medium and it's very lowest in SAS because the entire software is

being ready only for suppose you are ordering a pizza, you cannot customize it now according to your preference

because the pizza are already listed in the menu and you have to order it from there only. So nothing more sort of is

in your control. When we talk about the setup time, of course is takes a lot of setup time because you have to like do

it manually by yourself. You are setting up an entire infrastructure there. So the setup time is quite long in PS it's

quite medium and it is you don't have to have any kind of setup in the SS you just need to have your device to access

those softwares. Now user type IAS is basically uh inclined towards system admins and devops and PS according to

developers because you are writing and deploying the code there and SAS is used by everyone end users means like you me

everyone whosoever is using the app it's a globally recognized app when we call about examples again the same examples

AWS EC2 instance for the IAS Heroku and app engine for the PS and Gmail zoom canva instagram Netflix whatever we have

in the SAS is so the basic difference is SAS is a readyto-use software just like your Instagram, Netflix or whatever you

have. Then we have PS it's like a developers playground like you can write and deploy code all in the platform that

is available to you and is your own cloud infrastructure like you have the entire infrastructure in your control

and whatever you want to do with it and however you want to get the control of it. So it's quite in your control. Now

that we have understood the key service models, let's just dig into the cloud deployment models like how are they

actually made available to the users like how is the cloud technology made available to the users of it. So let's

just understand it with the three basic things that we have. One is called public cloud then we have private cloud

and then we have something called hybrid cloud. Now let's just take a brief example like what is public cloud?

Public cloud is like renting somewhere like renting an apartment or renting a house for someone because the owner is

not you. You're just renting it from somewhere and it is quite public for everyone because anyone can come and go

in that building right for suppose you're living in a society you're just renting an apartment in it. So it's

quite public for everyone. Now what is private? Private cloud means your own personal space like you are owning a

house, you have owned a house, you have purchased a house, it's your private property and no one can come and go

without your access, without your permission. So that is what private cloud is. Now hybrid cloud is very

interesting among these deployment models. Why? Because hybrid cloud uses the best of the both worlds like you can

have your private details in your private section in your private cloud and when you have like different things

like your name or age whatever you want to have like whatever you want to give the access to your different people you

can have it in the public cloud. So that is how hybrid cloud uses the best of both the technologies that is public and

private. Now let us understand each one of them in detail using the real life analogies and for you to get more

advantages of the features and the examples that we have. So you can see right here on the screen that public

cloud you know the services are provided over the internet by companies like AWS Azure of course the companies are Amazon

and Microsoft or the Google cloud. So anyone can sign up and use this resources like if you talk about

particularly AWS anyone can access it correct because it's like globally uh recognized and globally distributed. So

you can access it I can access it on the same platform itself on the same login page. So what are the features that we

have? It is a shared infrastructure because you are you are working on the same platform that I'm working on and it

is cost effective because again whenever you create an EC2 instance that we will be creating in the video further

whenever you are using it you just have to pay for the only amount of time where you are using it like for the duration

of time whenever you are accessing the EC2 instance or you're doing something in that. Next we have fully managed by

the provider. Now AWS is not managed by you and me. We are just the end users of it. the manager or the provider that is

Amazon that is the kind of the owner of this uh service. So it is completely managed by Amazon and the AWS admin.

Next we have easy to scale globally of course because since one person has created everything and it is shared

among all the groups all the people who are keen to use the technology. So it is easy to scale globally. Now the examples

are hosting websites or we have storing files like your Google Drive because of course Google Drive is also used by you,

me and everyone. It is the same app that is being used by each of the people and the running applications like Netflix

and AWS. Now what happens in Netflix and AWS also just understand it with Netflix if you want to have a common real life

analogy that you are having the same Netflix I'm having the same Netflix you will be getting the same recommendations

I will be getting but what happens your source of interest and my source of interest is quite different but what we

are doing we are sharing a public platform for our interest so that is what public cloud is now let's move

towards the private cloud that we have in action private cloud is like having your own gated data center of course

either on premises or hosted third party whatever but dedicated to your particular organization or dedicated to

you. Now whosoever use public clouds are like basically banks or governments or hospitals that you know run these type

of uh services that are quite confidential for everyone. So what are the features that you have in this is

you have more secure and customizable feature like because private cloud is being used by a private organization who

have all the data of it. So it is quite secure and customizable both. When I talk about used by highly regulated

industries then again it cannot be used like it can be used by a particular person but the key providers or the key

users of it are the banks and the governments who have some sort of private details of the entire

citizenships whosoever is having it. Okay. So next we have high setup cost and maintenance. Of course because if

you are having something private to yourself or to a organization of course it will cost little bit higher because

you are having more gateways and more security rather than public and hybrid crowd. And the next thing not shared

with others. It won't be shared with others until unless we have your permission or the provider has your

permission has your accessibility to give it to others. Next we have the examples. Of course, bank running the

core financial systems or government running managing the citizenship data or we have hospitals storing the medical

records. All of this organization you can see that are very private to their own citizens data or own customers data.

So that is how private cloud is used among the organizations. Now we have the very interesting section that is called

the hybrid cloud and you will be very amazed to know that yes you are quite familiar with this cloud provider. So

what this model does it is a blend of both private and public. Now what does it mean that it can allow data to move

between the private and public cloud again and again. So what are the features that we have in this? It uses

the best of both worlds like the storing of the information that is sensitive you can store it in private and this

something that can be accessible by everyone you can store it in public. Next we have flexibility and

scalability. Using the best of the both words give you the flexibility and scalability to use the both of the

systems accordingly and of course it is used for disaster recovery or traffic spikes. Now what do we understand by

this? Suppose you have a lot of data inside you like uh for a hospital also we have a lot of patients inside. So

what do we do? We just store the sensitive information in the private cloud and that can be accessed by

everyone like the appointment details or the appointment page it can be accessed by everyone. So we keep it in the public

cloud. Now take it an example uh an e-commerce website uses the private details of customers like their names or

whatever the orders they have purchased into their private cloud but the product browsing is similar for you and me

whosoever is using it for suppose we are surfing Myntra or Amazon the products that will be displayed there will be

same for you also for me also but the information that is quite private to each one of us will be shared in the

private cloud so similarly healthcare providers using private cloud for patient data and public cloud for

appointmentuling. That is how simple it is. So these were the cloud deployment models that we have in cloud public

private and again the interesting one hybrid cloud that uses the best of both worlds. Now since we have understood it

by a real life analogy let's just understand it again that in public cloud you are renting an apartment in private

cloud you having your own house so you can have the private data to yourself and in hybrid cloud is like owning a

house and you can do a Airbnb or you can book a hotel whenever it is needed. Okay. So who uses the public cloud?

Startups and public apps. Okay. Correct. And then we have private cloud. It is used by bank and government and

enterprises. Whosoever needs the private data to theirelves. And again the hybrid cloud can be used by the similar thing

like the healthcare services or the like e-commerce websites to store the patient data and the customer data alone and the

data for the browsing or for the appointmentuling in the public cloud. So these were the things that we have

discussed till now and I hope that cloud isn't feeling so cloudy anymore to you guys. So after this we are now moving to

the very important section that will be our key cloud providers. Now what are the key cloud providers actually means

that it is a third party company that is allowing all of us to use the cloud services that are be AWS from Amazon or

Azure from Microsoft or GCP from the Google. So these are the very important cloud providers that we have and we will

be discussing each one of them in detail step by step. Now the key cloud provider is just nothing that delivers the

cloud-based infrastructure or platform or software to the people who are ready to willing to pay as you go. Okay. and

you know for the organizations to scale scale their resources or without maintaining the physical hardware

because that's the key feature in cloud that we have now from Netflix to NASA each of us are using the AWS and Azure

and GCP for different sort of purposes so let's discuss each one of them one by one so starting with the very popular

service that we have called AWS that is Amazon web services now according to the convenience of the providers whatever

the user needs it provides IAS EAS SAS as allin-one. Now what we have it's a comprehensive yet evolving cloud

platform that is provided by Amazon that provides again IAS PA and SAS according to the individual's need or the

organization need. Now the very popular service that we'll be working on first of all that is called EC2 that simply

stands for elastic cloud compute. Now what does it mean? It's just imagine itself uh like a virtual server provided

by the Amazon. So you rent those virtual servers like IAS you get the entire infrastructure you get an a hosted

virtual server where you can perform all the task whether be your devops or cloud related things. So the very first

service that we have is called EC2. Now similarly we have different sort of uh other files that we have to we know we

need to store the files in that or we need to run the code without the servers. So we have S3 to store the data

files in the cloud and we have lambda to run the cloud serverless. Of course, you don't need any server in that. Then we

have RDS to manage the relational databases and we have CloudFront for fast global content delivery. Now, all

these services are very much used by many of the organizations and many of the individuals starting with you can

see here that it is popularly used by Netflix, NASA, Twitch and Airbnb. So these were the customers that we have

for the AWS services. Similarly just as the AWS we have another platform that is called Ashure that is provided by

Microsoft. Now again it is a similar kind of cloud computing platform that offers the solution for building,

testing and deploying the websites or the apps that you are creating. Now the popular service in this is Azure virtual

machines. Uh we will see this demo in the class further. Next we have Azure blob storage to store the large amount

of datas unstructured data mainly and we have Azure functions for event driver again serverless computing. Then we have

Azure SQL databases for fully managed databases of SQL and we have Azure DevOps for the CI/CD pipelines and the

project manage managements whatever you need to do related to DevOps technology. And again the use cases we have is uh

the BMV or HSBC Adobe and the US government it's written here for the instance purpose that these are all the

customers and the organizations that uses Microsoft Assure as their primary cloud provider. Now the next and the

very important and very interesting platform that we have is GCP provided by the cloud. Now what does GCP does? It

provides a similar infrastructure to the cloud users to the users of uh its customers that it uses for itself also

like for its own products for deploying the own products they use the same kind of platform that they are providing and

the popular services that we have is compute engine to launch the virtual servers just like IAS NPS or SAS and we

have cloud storage like it's highly durable and scalable storage and we have bigquery fire store and vertx AI for the

different type of technologies like pabyte scale analytics engine or realtime NoSQL database for web mobile

and to build and deploy machine learning models we have vertex AI. So if you're getting confused in all these terms for

right now don't be panicked because this is just the fundamental video for now but when you will be learning every

technology this cloud technology in depth you'll be understanding each of them very clearly but for now we'll be

demonstrating just two types of service models that are AWS EC2 and virtual machines in Azure. For now the cloud

platform that have been using uh the organizations are Spotify, PayPal, Twitter and Snapchat. So these are some

of the customers that GCP has. These are the like loyal customers of GCP. So these were the kind of service providers

of the cloud. So here we have a quick revision or a quick comparison between all of them. So when we categorize each

one of them, we have AWS, Ashure and GCP. So the computing engine that we have for AWS it's EC2 that is elastic

cloud compute that is used to like make virtual servers or here's the like instance that we have created in EC2

there where we perform all the tasks that we have to perform in the virtual servers. Now similarly as EC2 and AWS we

have virtual machines called Azure VM in Azure and compute engine in GCP. Now talking about the storage for storage

AWS uses S3 and Azour uses blob storage and GCP uses cloud storage. For databases we have RDS and Dynamo DB for

AWS, Azure SQL and Cosmos for Azure and BigQuery and Fire Store for GCP. Again I'm repeating the same thing. If you

guys have any issues in understanding these concepts, kindly stay tuned to the video further because we will be

understanding each of the terms in detail in depth by the trainer. So for coming to the serverless engine if you

want to go serverless in any of the crowd providers we have lambda for AWS Azure functions for Azure and cloud

functions for GCP. Now serverless means that since you don't need any hardware for like having the access to AWS Azure

or GCP there are times when you go you can go serverless also like you won't be needing any kind of server here. So you

can just have the access on your local device to run all the different types of virtual machines or run the different

types of whatever the codes you are using in it. So for DevOps we have code pipeline. Similarly similarly we have

Azure DevOps for Azure and code build and code run for GCP. Now these are the leading forces like the AWS or Azure or

GCP. These are the leading forces behind the cloud providers that we have today. And knowing the all the services that we

have discussed so far will help you to like optimize the you know the right tools or the right uh options to make

the scalable solutions from all these things. So as we have moved further in the video so there's a basic

demonstration for you guys. We have AWS EC2 for the first instance and second we have virtual machine in the Azure. So

let's just take a quick demonstration of each of the following. So first of all, let's start with AWS. As soon as I click

on the video, we have a quick login page here where you can have the credentials or if you don't have, you can uh create

a new AWS account also. But for now, I'm using my personal account here. So as soon as you log from your like

credentials, what happens? This is a default page that stands in front of you where it is written EC2 because we are

trying to create a virtual server here only. We are trying to create an instance. So what I have to do I have to

just click on the EC2 instance and here I'll be searching either I can search for the instances or I can create

instance whatever you want to do. For now I have seen I'm able to see the instance that are running. So it's

showing zero because we haven't created one yet. So let's just create one by clicking on it. So you can see every

instance that would be running or that is terminated or that is has been started will be showing here itself. So

let's just create one by creating launch instance. We just have to click there and here this kind of default page

should be coming to your interface. First of all we have number of instances that we have like you can create 1 2 3

as number of instances as you want but for now for the demonstration purpose I'm just creating one. Now we have to

give some sort of name and tags for our virtual server like what kind of server I'm using. So I'm just creating my first

EC2. So this is the thing that I'm creating. Just give your name a. Okay. Now we have to create uh you have to

select the application or the operating system that you'll be working on. We have different sorts of operating

systems here. We have Red Hat, Windows, Ubuntu, Mac OS and Amazon Linux. You can use any one of them but for now I'm

using I'm selecting Ubuntu because it's quite friendly for beginner friendly for all of us. Now it will take you time to

roll. Okay. Then we have many types of VM images like whatever you want to use but for the free tier that is eligible.

I'm using the first one that is Ubuntu server. It's a confirmation page but I'm not confirming it because the thing was

already selected in here. So we have a architecture like whatever kind of architecture you want in here. So I'm

selecting a 64-bit because we are just creating it for the demonstration purpose. So here's the instance type.

Now this is very important where you're working with it because we have a lot of instances type be nano micro or you have

small medium whatever the kind of size you want for your instance. So because of the free tier availability I'm using

t3.micro and here's the interesting part that is key login. Now you can create your own key pair as per your demand

whatever is comfortable with you. So for now I can see the whatever the key pairs have been created here I can use it. For

now I'm using my own creep pair or is it not available? Let's just try anyone. So these are the existing keep pairs that

have been already created by some other users who have been sharing this platforms. It's not that it can be

shared with you and me also. It's just a kind of organization or the group that I am willing to share my key pair with. So

it's that thing. Then we have the network settings. You can allow the SSH traffic. You can allow the HTTP or HTTPS

according to your will. And after that you just have to launch the instance whatever the sort of instances you want

to create. After launching it if any issue will occur it will be showing here but if it's not that the instant will be

created. So you can see we have got a success and it's our ID that the instance ID that has been created. So we

have to again go to the instances and here we can see that our instance is ready. Just trying to wait for it. Yeah.

So here I have my first instance. Now it's not enough for us to just create an instance. We also have to connect it to

the machine. Now what happens? We have created an instance but AWS doesn't know it yet. It is showing the instance is

running but it's not connected. So to like have the access to the virtual server to like a Ubuntu type of machine

or the operating system where we will be working on. So we have to connect it first by just clicking on it and we have

to just connect it. Now you can either connect it using a public IP or a private IP. Now this is the you know

deployment model that we were talking about. Whenever we are using a private IP it will be just private for all of us

and it will be just be accessible from my own local platform also like I can open bash or c cmd prompt or whatever it

can be accessible from that also but since right now I'm just using it for the demonstration purpose I'll just

using a connecting public IP but both the IP addresses will be showing on the instance that I have been created. So

let's just connect it and see what happens further. Now as soon as I create my EC2 instance is ready to use now. So

here you can see by the time it's establishing the connection that I having both the private and the public

IPs here. So this is it. Now you can perform whatever the uh operations you want here. Either you are from DevOps or

the cloud technology whatever the instances uh has been created is free to use for every one of you. But one more

thing that you have to remember is that after it is started it is payable. Okay for whatever time you are using it it's

payable. it is having some sort of cost or you can say a value. So whenever you are done like for now we are not writing

anything in it you can just write anything for suppose I'm working on devops or I want to install docker or I

want to see if docker is already installed in here or not. So this is the command that I move with. So it's

similarly as we do in Linux or windows cmd prompt. So that's all for the installation and the demonstration part.

So we can cut it from here directly. But you have to remember that you have to terminate this instance. Why? Because if

this uh keep on running. So as you know that cloud computing is a kind of pay as you go system right. So for the whatever

time you're using it it will be chargeable. So you have to delete it after you have created it you have used

it for your purposes the whatever thing whatever demonstration you wanted to use you have done it. So just click on it

and go on the instance state and try to terminate or delete the instance. Now just terminate it from here. So yes it

has been successfully initiated the termination and you can see in the instance state that was shutting down

and the instance has been gone. So this was the part where we used AWS EC2 instance to create a virtual server to

see like whatever the things we can done in here. Now there we have one more key provider that we have that is called

Azure that is again very popular. So like this then I'll just I have just skipped the login page part. You just

have a login page where you sign up or login using your credentials. So this is the default page that opens right here.

Now we knew that in AWS we were creating an EC2 that is elastic cloud compute instance to create a virtual server. For

here we have a virtual machine. See you can see here all the services that have been provided here. But for working on a

like cloud server for working on a different operating system we just create an another resource that is

called a virtual machine. Either you can click it here or just click create a resource or just click on virtual

machines. So as we were having like EC2 instances in AWS here we are having virtual machines. So the similar type of

thing like you can see that as you saw in the EC2 instance all the things were happening here itself. So the similar

thing all the virtual machine will be created here and the steps are quite simple. You just have to create uh one

virtual machine and you have all the options but we are working on a like hosted platform. So we'll be creating

one virtual machine here and we we will be having the similar steps that we had in that. Well, now you have the resource

group whatever you want to use whatever the name you want to give to the virtual machine the name can be provided the

security type the architecture here there we were using 64-bit here you can also have the same sort of architecture

then we have the administration account you can either use SSH public key or you can use a password like it can be your

username your password and whatever you want so after this you just click on review and create as soon as you do it

what does a does it will review it automatically like if there's some sort of problems or you haven't put something

right so it will display it right on your screen and you will be directly redirected to this page only. So when

you just review and create you will create an entire virtual machine similarly as an EC2 instance that we

created in the AWS. So this was it for the demonstration part that we had in the AWS and Azure because these were

very quite a popular platforms that we had in our minds. So this was the demonstration part. Now as we are coming

to the last section of our video, we have something interesting for everyone of us that is benefits, challenges and

the career paths that we have after learning cloud computing. So let's just dig into it. Now let's just first of all

talk about the benefits that we have along with it. We already know cloud is a kind of like ready to use software or

you can say that it's a very beginner friendly or everyone's like to use this type of technology when we have. Okay.

So coming to the benefits that we have first of all it's costsaving of course as we have seen in the EC2 and Azure

virtual machines also like for the time you are for the duration you are using it or you are accessing it you have just

have to pay for that that amount only it's just like having a 10 GB storage and you are paying for the 10 GB only

not for the 100 GBs like you used to do back in the days when you were having physical IT servers so that's the thing

and it's uh see is the same meaning that you pay only for the time you use and there is no upfront hardware investment

and the real life analogy is simply like having an Uber instead of owning a car when you are new to a city. Now talking

about speed and agility, you see how easily we were able to like launch an instance or launch a virtual machine. So

it's that much easy to launch a resource whenever you want to work with the cloud technology. It just like ordering in

food from the app. Now the scalability see we have seen like whenever for suppose you and me both are using the

AWS EC2 instances there are lot of instances created there. So what does AWS servers does it just automatically

like grows or add the servers to like maintain this much traffic and when the traffic is low like only one or two

instances are there it just automatically reduces the traffic like that. So this is the very good you know

benefit of having a cloud service that it can like expand or shrink like a balloon according to their service. You

don't have to worry about anything in that. Next we have global access. So of course you can use it from anywhere like

you can open your EC2 instance right there or you can open an Instagram just for the instance if you want to have a

clearer version you can open the Instagram anywhere like if you are going to traveling to some other place there

also you can open an EC2 instance or Instagram just like you want. So it's a ready to go system. You can use it

anywhere, anytime at any device. So just like your Netflix, Gmail or your popular app called Instagram. So next we have

security and backup. See cloud providers offer advanced security whether it's being an EC2. So you have a keep your

login area to keep the things very private and very uh you can say secured. So similarly we have in virtual machines

we have username and passwords that we didn't create but you can create one. So it will keep your things in the virtual

machine secured and private to you. So that is the important thing that cloud provides and it's just like keeping your

valuables in the back. So what happens is see the benefit the major benefit that clouds come with it is it doesn't

make it faster. It makes it the innovation very cheaper and very scalable and very global to use. So

these are the benefits that comes along with the cloud. Now since you know that cloud is powerful it's kind of uh having

lots of benefits but it's not the magic okay so we have some sort of challenges in this also talking about the

challenges as we discussed even the security is very much highly provided in this but there are some sort of security

risk that we have in this because we can be having like misconfigured services that can expose the data of one country

to another or one bank to another that is quite a challenge to be secured about. The example can be like public S3

buckets being leaked like the S3 buckets in AWS which is used to store the data and the files can be leaked at times if

not kept properly and if not like kept under the eye. So this is a one of the major challenge that we have in cloud

computing. Now cost averance a very simple example can be an EC2 instance like if you have created an EC2 instance

and you have kept it running like you have done your time but even if you kept it running for a day or two it will be

like causing you a hefty amount to pay because that's the thing like if you're overusing it and if you're not making it

available at the time when it is needed. So you can just overuse your spike bill this so it can spike your bills and the

lack of monitoring can make you pay hefty amounts at times. So again the example is same that leaving your EC2

instance at running. Now compliance and legal it's just a simple thing that some data must stay within the certain

countries like financial systems or the healthcare or the government data should be kept under one government like the

Indian government is having some sort of data that shouldn't be get leaked to the American or Chinese government. So

that's all about it. So it's the compilers and legal terms that we need to take care about when we are dealing

with cloud computing especially if you're working as a key cloud provider. Talking about vendor lockin, see

migrating from one cloud to another can be a struggle at times like EC2 instance or there's few types of services, a few

type of apps that are AWS friendly but you kind of have will be having some sort of issues while working it with

Azure. Why? Because AWS handled by some other company and Azure is being handled by some other companies. These two

things have the some different sort of features or different sort of technologies. So it can be a issue that

when we are working with the AWS friendly app it can be little difficult to work with the Azure in that. Next we

have downtime in environment. Now what do we understand by downtime and internet? See you know that the entire

cloud computing is physical hardwareless like everything that you need is on the servers on the internet. So the very

important thing that you have to be highly dependable on is called internet. If your connectivity is slow or the

cloud provider uptime is being reduced or exceeded so it can impact the real world times. Okay. What does it means

that for suppose you have uh less internet connection while you're running an EC2 instance or a virtual machine. So

you can list you know make the connection server break or few of the commands that you have written in it

might not be able to be saved. So these are the things that can impact the realtime apps in the Azure or AWS

whatever you are working with. So again it is powerful cloud is very much powerful but you have to handle it like

you need to be smart and you need to have a good setup to like make it uh cost control and security proof. So

these are the challenges that we have in cloud computing. Now the last part and the very interesting part for everyone

of us that what are the roles that we have to offer when you learn cloud computing. So you see if you are into

cloud engineering, you love to build and manage cloud infrastructure like you love to like have a cloud infrastructure

and you like to build something out of it, something new or something relatable for everyone. So you can be a cloud

engineer after learning the skills that are AWS, Azure, Linux and Terraform. So Terraform is a kind of a DevOps topic

and similarly Linux is a different technology but it's again an operating system and AWS Azure again that we have

worked on it. So this is the things that you need to be a cloud engineer. Now if you're into DevOps and you like to like

automate deployments on CI/CD pipelines, what is CI/CD? Continuous integration and continuous deployment. So if you

like to have those suit of pipelines automation, so you can be a DevOps engineer. All you have to learn is

genkins, Docker and Kubernetes but very well. Now you can be a cloud architect if you like to design end to-end cloud

systems like you can have end to-end users or end to-end systems that are designed for a particular kind of

provider or a customer. So you can have be a cloud architect in that and you have to learn architecture and deep

cloud skills for that. So that is another thing. Then we have a cloud engineer who handle the data pipelines

and storage and you can see that you have to learn bigquery and azure data factory for that. Now you can learn

anything and everything in detail if you are clean into the cloud and if your fundamentals are quite clear at the

beginning. So talking about the very popular term and very popular job role that is among all of us that is AI and

ML engineer but that to cloud dominant like you train and deploy the models on the cloud. So you need to learn vertx AI

SageMaker and very important language that is in data science AML is Python. So these all are the things that you

need to have for the a IML engineer. Now similarly we have another two job roles that are quite familiar that is cloud

support and cloud security analyst. In cloud support engineer what you do you just manage cloud bus and billing of the

setup. For that you need basic cloud and customer handling and for being a cloud security analyst you do monitor and

secure the cloud environments and for that you need IM firewalls and thread detection. So these are all the job

roles. If you're intrigued into learning cloud more DT, you have to like understand all the skills that have been

mentioned here that you have to kind of be very patient and very skillful with all these skills if you want to have a

career in all of these roles that have been mentioned here. So if you are still interested in cloud with be uh you have

to learn cloud in very depth because these were just the fundamentals that we have covered till now. So that's a wrap

up for this video. I hope that cloud doesn't feels cloudy anymore because we have understood all the fundamentals

that were essential till here. So you know that cloud is not just a trend. It's the backbone of today's digital

world and the digital power for the tomorrow's innovation. So if you're learning cloud make sure you're giving

all the time and attention it needs for from you. So you can learn cloud as much as you can and from this point onwards

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technology. We discussed about the data center sprite. uh we discussed that an

organization would require data center and those data centers will hold the will have the servers inside them right

so the servers are are deployed inside the data centers servers are deployed via within the data centers now the

question comes in that what about the data centers which are owned by Amazon web services because your organization

for example you you work for a company like Accenture Vipro HCL L, Infosys, JP Morgan, AIG, Apple. Right now when when

they when these companies start using cloud computing vendors like AWS, Microsoft Azure, GCP, Salesforce, these

companies become their customers. For example, Apple says we want to use Microsoft Azure to uh to deploy our uh

workloads and applications, right? So uh in that case Apple would be the customer of Microsoft Azure or Microsoft. Okay.

So think of yourself as as a customer or or uh you are the employee for working in that organization who a who's the the

customer of any one of these three providers. The next question that comes in is that how exactly you leverage that

infrastructure which is owned by your cloud vendor. Let's suppose you're working for Apple or let's suppose

you're working for uh Netflix. Netflix is is a customer of AWS. Now Netflix uh is running all its various as the

applications workloads on AWS. Now being a part of Netflix you have to understand exactly that how Amazon Web Services has

scattered its data centers or how it is managing its data centers in different parts of of the world because Netflix

doesn't offer its own services only in US. It offers you services in a lot of countries including India, right? So you

have to make sure that how you understand its global infrastructure of AW players. You understand that how they

place the data centers in different parts or or on different countries or different continents. That's where we

disc that's where we the the concept of the global infrastructure comes into play. Global infrastructure means then

you understand exactly that how a cloud provider which is Amazon has placed this data centers and cluster those data

centers in a different uh location or what's exactly not exactly location but exactly how uh these things have been

placed in in let's suppose in Africa and India and US and Europe how they have clustered their data centers in in in

these different countries. So in this case we need to understand concept that's called global

infrastructure. Let's try to understand that. Okay. So we're trying to understand first topic I would say that

of of AWS which is the actual topic. The name of the topic is AWS global infrastructure.

Now it consists of different components different parts like regions everybody zones edge locations. uh we have uh for

example local regions or local zones I'm sorry local zones regions local zones availability zones uh we also have edge

locations but there will be two things I'll be discussing with you right now regions and availability zones edge

locations local zones we'll discuss afterwards okay let's discuss the AWS global infrastructure

let's try to understand that okay So the very first component or the part of this infrastructure includes a

region. Okay. What is an AWS region? An as region is nothing but it's a

geographical region. It's a geographical location or a geographical region or a piece of land

which consists of which consists

of a cluster of data centers. is

owned and managed by AWS.

Okay. What's a cluster? What do you mean by cluster? Some people ask me this question. What do you mean by cluster?

Cluster means group, right? So, a region is nothing but it's a geographical location. It's a basically it's a piece

of land. It can be uh be on the name of any city uh or maybe for example most of most of these are based on

cities or named be after countries. Uh so it can be any name. It can be based on a city like for example in in India

there are two regions Hyderabad and Mumbai. Uh for in in Australia Sydney and Melbourne are two regions. For UAE

they have a separate region. Uh for let's suppose for South Africa, Cape Town there's a there's a separate

region. Singapore is a separate region. Right? Japan is a separate region. A region is nothing but it's a

geographical location which consists of a group of data centers which are being owned and managed by Amazon web services

which is which is a cloud provider. We are the customers right like we let's suppose we work for Netflix we work for

JP Morgan we we use AWS to deploy our resources into so those custom data centers are used by us right but who

owns and manages those data centers or cluster data centers it's the cloud provider okay so a region is nothing but

it's a piece of land it's a geographical location where the cluster of data centers the group of data centers which

are being owned and managed by Amazon web services exist over there. I would say it's a geographic location or it's a

piece of land where Amazon's owned and managed data centers run and they are being operated by Amazon. So Amazon Web

Services says let's suppose in Cape Town I have my three data centers running. So I mark Cape Town as a region right. So a

region is a geographical location which consists of data centers a chain of data centers. Now in these cluster of data

centers are being denoted by a special term. Okay. So what what is that special term that we use over here? This cluster

of data centers that we these cluster of data centers are denoted by a term that is called availability zones.

What's that? It's called availability zones, right? Okay. Availability zones in the short form are called as.

These are the data centers or these are the facilities um consisting

of racks of servers. These are data centers only. Right? So these are the facilities which houses

racks of servers. Right? These are the facilities which consist of racks of servers. Now one

availability zone or one a is equal to one or more data centers.

A single a can have one or more data centers. Okay. And in each region

there are at least three a right to make your data more redundant

to make your work uh applications more available. So basically these are the two terms you have to remember and

learn. A region is a geographical location which consist of a cluster of data centers. These cluster of data

centers are called availability zones. So everybody zones are the data centers only or they the facilities which

consist of rack of servers. One a equates to one or more data centers and each region will have at least three a

there could be more than three a but you'll find minimum three availability zones. Fine.

These are the two terms you have to remember. I'll just give a few examples over here

so that you understand that in uh understand this uh concept in and out. Okay. Now I've just logged into my

YouTube sp console uh to my account. You can be seeing one thing is that once I just go to the top right hand corner

right I'm talking about this thing where you see my uh this cursor over there. Uh in this case you're going to be seeing

that these are the listed regions over here. North Virginia, Ohio, California, Oregon, Hyderabad, Melbourne, Mumbai,

Soul, Singapore, Sydney, Tokyo, Canada, Frankfurt, Europe. These are the existing regions, right? Frankfurt,

Ireland, London, Paris, uh uh Stockholm, uh we have Cape Town, Hong Kong, Jakarta, Milan, Spain, Zurich, right?

Right. So these are the regions. It shows exactly the regions and it gives the the details of the regions and

the availability zones which are owned by AWS. Okay. So in this case if I just go back and show you exactly this is the

map. So as of now they have 31 large regions. So uh presently when when I'm talking to you they have 31 running

regions which are running to 24 + 7 right this is the map that shows up on this map the green dots that you can see

these are the existing regions that's why we say a region is a physical location it's a geographical location

it's a piece of land for example so the green dots you can see those green dots represent regions for example this green

dot dot. This green dot represents Sydney. This one Melbourne. Uh this one Jakarta, Hyderabad, Mumbai, UAE, Parin,

uh Spain. Uh this is for example North Virginia. Uh this is for example Milan, Spain, Ireland. Right? So the green dots

represent existing regions. Each region is a physical location which consists of a chain of data centers or a group of

data centers and those group of data centers are called as availability zones. Now the one that you can see in

the uh in the form of red dots these are the upcoming they are coming soon which means that they will be set up in the

next few months. It's work in progress. Amazon is still setting them up uh because uh launching a chain of data

centers take a lot of time uh and um it is still in progress and very soon you're going to be seeing these data

centers being showing up. So as of now you can see the exact details. There are 99 availability zones. Now each

availability zone can be one or more data centers. Generally we assume it's one data center. Okay. So let's suppose

there are 99 data centers. There could be more than 99 99 data centers in 31 geographic regions. All right. With

announced plans for 15 more data centers or more than 15 could there could be a possibility that one a because in there

few as we consist of two data centers. So 15 or more availability zones in five more regions in Canada, Israel,

Malaysia, New Zealand and Thailand. So I think by the end of this year you'll be seeing most of these uh the

regions being deployed. Okay. I think Canada will show up because uh uh they announced Canada uh region and Montreal

few months back but let's see. Okay. So these are the the the regions which exist and some of the regions they are

still in plan. They will be deployed very soon. Fine. Now um I can also show the the the definition just in case if I

just go this this other link. Um okay so you can see that AWS has a concept of a region which is a physical

location around the world where we cluster the data centers. We call each group of logical data centers as an

availability zone. So that's why I said an availability zone can be one or more data centers and and there are three

availability zones at least in one region. Okay. So AWS has a concept of region which is nothing but it's a

physical location around the world where we cluster the data centers and uh this group of logical data centers are called

as availability zone. Each region consist of a minimum of three isolated physically separate aes within a

geographic area. So each region will consist of three availability zones within a geographical area or in a

region. So that it uh uh they isolate any hardware failures, any power outage. So I think there's a distance of around

50 to 60 km between each each of um the easy that's the the minimum distance. So if if one easy um so the distance

between two easys is at least 50 to 60 kilometers right. So because if if one easy goes

down because of an power outage u maybe because of floods natural disaster you can easily have other regions other

availability zones uh serving you uh the services in form of uh workloads and applications running inside them. Now

what what is an availability zone? And a variability zone in the short form we call as an a is one or more discrete

data centers with the redundant power networking connectivity in an as region right so it's a kind of a an is equal to

one or more data centers which has its own power networking connectivity inside that region okay let me just give you

two two three examples then then I take the questions forward let's take uh one or two examples first thing first we

need to understand that Each region is given a special name. For example, uh the one which is labeled as US East one,

that's the North Virginia. What's that? North Virginia. So basically, they don't go with this uh with the geographical

names. They give their own special names. For example, uh the one which is the US East one. US East one means that

they're talking about the Northern Virginia, right? So for California, it's okay. How they labeled US East one?

North Virginia is on the east coast of US, right? And this was the very first

region on the east coast of US. So it they labeled as US East one. Now by the way, US East one is the very first

region Amazon set up when they started giving AWS uh as or when they they started as a cloud provider. So this is

the Amazon's web services first region. So this this is the on the east coast of US the very first region. So they

labeled as USC one. Ohio is the is the second region on the east coast of US. So it's USC 2. On the west coast the

first region uh is uh California US west one and US west 2 is is Oregon the second region on the west coast.

For example, let's let's take in India, we have AP South one. AP stand for Asia Pacific. In the southern region, the

very first region was Mumbai, AP South one and the second was Hyderabad. So, it's AP South 2. You don't have to learn

these names. So, they have labeled these names. They've given us uh the abbreviation or special names for these

different regions. Okay. So, for example, let's go with US East one which is North Virginia. Okay. Let's let's

take this one. Uh let's go with Mumbai. Okay. Mumbai was very first region uh in India. Launched few years back. I think

2017 or 2018. I'm not sure about the exact date but anyhow every region you have every region is a

separate infrastructure on its own. It is independent from other regions. Fine. For example, if your deployment

resources in Mumbai, they will stay in Mumbai only. They will not be visible. I would say they will not be the part of

Hyderabad or California or Virginia. So assume that every region is its is a complete infrastructure

on its own by itself. So for example, if I use Mumbai and deploy my resources in Mumbai, they stay in Mumbai. Of course I

can access them remotely from other location but they would be the part of Mumbai region that's why you have to

switch dashboards between regions right for example right now I'm in I'm in Mumbai dashboard so I can access my

resources in Mumbai similarly if I switch to California so in this case I'll be uh I'll be accessing my

resources in California understood so each region is its own uh it's it's infrastructure on its own. I would say

it is a complete infrastructure where it's independent from other regions. That's the reason reason you have to

switch back and forth between different regions to access the individual dashboards. So if I deploy my resources

in California, they stay in California. If I have to let's suppose access my sources in Sydney, I have to switch to

the to Sydney's dashboard. That's reason uh that's the the reason once I switch between different regions the link or

the URL changes at the top right so every region is is isolated or it's kept separate from other regions uh if I say

uh it it is a separate entity this means that it it has its own identity right so to access and deploy resources in Sydney

I have to explicitly go to Sydney switch to the dashboard and start launching my resources inside Sydney. I can't deploy

resources uh in Sydney while just using Melbourne dashboard. I can't do that. Okay. So that this thing you have to

understand. Okay. Let's let's take the example of Mumbai. I was trying to give you some examples.

Mumbai is labeled as AP South one. This is a special name assigned to it. Okay. Now let's suppose I want to show you uh

we I I want to see the availability zones in Mumbai. I need to see the availability zones inside Mumbai. So I

go to EC2. E2 is stand for elastic compute cloud which helps me to deploy the virtual machines in the Amazon's

cloud. So if I want to deploy my virtual machines or instances or EC2 instances in the cloud, I use E2 dashboard which

stand for elastic compute cloud. Very well. Now if I just go to Mumbai right now, let me show you the Mumbai region.

Okay. So in this case, this is the region of Mumbai which is labeled as AP South one. What's that? It is AP South

1. Okay. Inside AP South one, I have three availability zones. AP South 1 A, AP South 1 B and AP 1 C. Right. So what

is APO 1? It is the the region of Mumbai. This is the one. So APO 1 A, 1 B and 1 C are the three availability zones

which are interconnected with highspeed fiber optic cables. Okay. So these are the three clustered interconnected

availability zones which operate inside Mumbai. Fine. I'll give you two two or three examples uh two or three more

examples to give you some more clarity. Uh let's go to Sydney. Sydney is labeled as AP Southeast 2.

Okay, let's go there. Now AP Southeast 2 is which region out there? AP Southeast 2 is is the region which is the S uh

Sydney. So uh AP southeast 2 is Sydney uh or the region of Sydney. So AP southeast 2 A which is this one 2 A 2 B

and 2 C these are the three interconnected regions sorry availability zones what

are these I'm sorry of time these are what are these these are the three availability zones or three a fine these

are three which are interconnected with highspeed fiber optic cables And where are they being deployed? They launched

inside this region where Sydney is AP Southeast 2. So AP Southeast 2 is the region of Sydney which consist of three

interconnected variability zones. AB Southeast 2A, AP Southeast 2B and AB Southeast 2C. Let's

take one more example. Let's uh jump to the next region which is Frankfurt. Frankfurt is EU Central one. If you

click on that, you will see that immediately the page will change. The details will change automatically.

So Frankfurt is represented using this term which is EU central one. It's the central part of Europe. Frankfurt in

Germany. So EU central one. It consists of three interconnected availability zones. They're labeled as U center 1 A,

E 1 B and U center 1 C. So these are the three as interconnected and located inside EU central one which is a

Frankfurt region. So a region is a is a it's a geographical location which consist of at least three as or

availability zones. These availability zones are represent group of data centers. There are at least three as

inside a region at least. Um I'll show you North Virginia consist of most of the ACS. If I go to North Virginia, the

very first region which was set up by Amazon Web Services. So North Virginia is labeled as US East

one. What is that? It's the US East one. Fine. It consists of these six availability zones.

1 A 1 B 1 C 1 T 1 E 1 F. So six availability zones inside the region of North Virginia where is US east one.

Okay. So this is the concept of regions and availability zones. Now the thing is uh I know this question will come up um

that uh how we achieve high vibility between them. Can we use all the regions or all the

availability zones? The answer is yes. Um we have to make use of some tools like load balancing, global accelerator,

route 53, autoscaling to disperse and scatter your resources across these as regions and use them as

a part of a single application. How they cluster the data center? Uh so basically the data centers are

interconnected with highspeed fiber optic cables. That's how they cluster them.

Okay, I guess this is clear now. How to make use of all of them or some of them? We're going to be discussing the

services based on the services that we discuss. We're going to be understanding each one of these different uh u I would

say how to use them. Right now we we just seeing them how that these are the list of regions, these are the list of

availability zones. But how to make use of them? We'll be discussing that when we start uh with the process of

launching of services. Right? For example, if I deploy the servers or virtual machines, I can explicitly

choose the region of my choice and the availability zone of my choice. I can I can do both. But once we start uh with

the launching process, we start understanding that stuff how to use them. Okay. So to access the

availability zone, you have to go to EC2 dashboard and there's the service health status or service health dashboard. This

is where you can see a list of availability zones inside the region. All right, that's about the the stuff.

Very well. So guys, let's get started with the next topic which is quite important for us to understand which is