AWS & Cloud Computing for beginners | 50 Services in 50 Minutes

Summary

In this informative video, Ranga Karnam, a 10x certified cloud expert, guides viewers through the complexities of AWS, offering insights into various services for deploying cloud applications. From EC2 instances and Elastic Beanstalk for compute needs, to RDS and DynamoDB for databases, and S3 coupled with CloudFront for static content delivery, the video simplifies the AWS landscape. It also touches on security, networking with VPCs, and the importance of DevOps practices in the cloud, making it an invaluable resource for beginners looking to understand or attain cloud certifications.

Takeaways

• 🚀 Rangana Karnam is a 10x certified expert in AWS, Azure, and Google Cloud, offering courses to help thousands of learners achieve cloud certifications.
• 🛠️ The video aims to provide an understanding of AWS services using a simple application example involving a front-end, REST API, and database.
• 📚 AWS offers over 50 different services, which can be explored through practical examples to understand their applications better.
• 💻 For deploying a REST API, AWS suggests using EC2 (Elastic Compute Cloud) for compute, ELB (Elastic Load Balancer) for load balancing, and ASG (Auto Scaling Group) for scaling EC2 instances.
• 🌐 To ensure high availability, AWS leverages Regions and Availability Zones, which distribute resources geographically to prevent downtime.
• 📈 Managed services like Elastic Beanstalk simplify the deployment process by handling the operational details, allowing users to focus on code deployment.
• 🐳 The shift towards Docker containers has led to the popularity of container orchestration services like EKS (Elastic Kubernetes Service) and ECS (Elastic Container Service) in AWS.
• 🎯 AWS Lambda is a serverless computing service that runs code without managing servers, scaling automatically and charging based on request volume.
• 🔍 Choosing between SQL (relational) and NoSQL (non-relational) databases depends on the application's need for structure, scalability, and transaction management.
• 📊 AWS provides managed database services like RDS (Relational Database Service) for SQL databases, Aurora for high scalability, and DynamoDB for NoSQL needs.
• 📈 For analytical processing, AWS Redshift is recommended, allowing for high-performance queries on large data volumes.
• 🌍 To serve front-end applications, AWS S3 (Simple Storage Service) can be used for static website hosting, combined with Route 53 for domain management and CloudFront for content distribution.

Q & A

What is the primary focus of the video script?

The video script focuses on providing an overview of various AWS services and how they can be used to deploy and manage applications in the cloud.

What does Ranga Karnam claim to be certified in?

Ranga Karnam claims to be 10x certified in AWS, Azure, and Google Cloud.

What is the example application scenario discussed in the script?

The example scenario is a simple full-stack application with a front-end application communicating with a REST API, which in turn fetches data from a database, along with a reporting workflow.

What AWS service is used for compute services?

AWS EC2 (Elastic Compute Cloud) is used for compute services in AWS.

What is the purpose of an Elastic Load Balancer in AWS?

An Elastic Load Balancer in AWS is used to distribute incoming application traffic across multiple EC2 instances.

What is an Auto Scaling Group in AWS and why is it used?

An Auto Scaling Group in AWS is used to automatically scale the number of EC2 instances up or down according to demand, ensuring application availability and managing costs.

What does the script suggest for deploying a REST API in AWS?

The script suggests using services like EC2, Elastic Load Balancer, Auto Scaling Group, Elastic Beanstalk, or even serverless options like AWS Lambda for deploying a REST API in AWS.

What are the main differences between using EC2 and Elastic Beanstalk for deploying applications?

EC2 requires manual setup of instances, load balancing, and scaling, whereas Elastic Beanstalk is a managed service that automatically handles the deployment, scaling, and management of the application.

What service in AWS is recommended for deploying Docker container images?

AWS Elastic Beanstalk is recommended for deploying Docker container images in AWS, as it supports container images and manages the deployment process.

What does the script mention about AWS Lambda in the context of serverless computing?

The script mentions that AWS Lambda is a popular service for serverless computing, where you only need to provide the code, and AWS handles the infrastructure, scaling, and execution based on the number of requests.

What AWS services are discussed in the script for managing relational and NoSQL databases?

The script discusses AWS RDS (Relational Database Service) for managing relational databases, Amazon Aurora for regional and global relational databases, and Amazon DynamoDB for NoSQL databases.

What is the role of AWS Redshift in the context of databases?

AWS Redshift is an analytical database service designed for running complex queries and processing large volumes of data with high performance.

How does AWS Data Pipeline fit into the data management scenario described in the script?

AWS Data Pipeline is used for creating data pipelines that can move data from transactional databases to analytical databases like Redshift, facilitating data integration and business intelligence processes.

What AWS service is used for object storage and can also serve static websites?

Amazon S3 (Simple Storage Service) is used for object storage in AWS and can also be used to serve static websites by hosting the website's files in an S3 bucket.

What is the significance of a Virtual Private Cloud (VPC) in AWS?

A Virtual Private Cloud (VPC) in AWS is significant for security purposes, allowing users to isolate their resources and control the traffic flowing into and out of their applications and databases within the AWS cloud.

What AWS services are mentioned in the script for DevOps practices?

The script mentions AWS CodePipeline, AWS CodeBuild, AWS CodeDeploy, AWS OpsWorks, AWS CloudFormation, Terraform, AWS CDK, and AWS CloudWatch for DevOps practices, including CI/CD, infrastructure as code, and observability.

What service in AWS is used for sending notifications and handling pub/sub messaging?

Amazon SNS (Simple Notification Service) is used for sending notifications, and Amazon SQS (Simple Queue Service) is used for handling pub/sub messaging and queuing services in AWS.

What does the script suggest for someone who wants to get cloud certified?

The script suggests checking out beginner-level cloud certification courses such as AWS Cloud Practitioner, Azure Fundamentals (AZ-900), or Google Cloud Digital Leader for those who want to get cloud certified.

Outlines

00:00

🚀 Introduction to AWS Cloud Services

Ranga Karnam introduces himself as a 10x certified expert in cloud technologies, including AWS, Azure, and Google Cloud. He outlines the goal of the video: to provide an educational journey through AWS services using a simple application example. The example involves a front-end application, a REST API, and a database, which are typical components of a full-stack application. The video promises an exploration of over 50 different AWS services, starting with the deployment of a REST API using EC2 for compute, Elastic Load Balancer for traffic distribution, and Auto Scaling Groups for instance management. The importance of high availability through regions and zones in AWS is also mentioned.

05:01

🛠 Compute Services and Managed Options in AWS

This paragraph delves into the complexities of setting up a REST API on AWS, including the use of EC2 instances, Auto Scaling Groups, and Elastic Load Balancers. It discusses the challenges of managing infrastructure and introduces managed services like Elastic Beanstalk, which simplifies deployment by handling scaling and load balancing. The paragraph also touches on the evolution to containerization with Docker and the use of Elastic Beanstalk for deploying container images, as well as the options for microservices architectures with Elastic Kubernetes Service (EKS) and Elastic Container Service (ECS). It contrasts these with serverless deployment using AWS Fargate, which eliminates the need for cluster management.

10:01

📚 AWS Database Services: RDS, Aurora, and DynamoDB

The script shifts focus to database services in AWS, explaining the distinction between SQL (relational) and NoSQL (non-relational) databases. It highlights Amazon RDS for relational databases, supporting engines like MySQL, Oracle, and SQL Server, and Amazon Aurora for global databases that require high scalability and availability. For NoSQL use cases, Amazon DynamoDB is presented as a document database suitable for applications requiring high transaction rates and scalability. The importance of choosing the right database service based on the application's needs is emphasized.

15:03

📊 Analytical Databases and Business Intelligence with AWS

The paragraph discusses analytical databases for handling large-scale data queries and business intelligence tasks. It mentions AWS Redshift as a popular solution for analytical databases, capable of managing petabytes of data with high performance. The use of AWS Data Pipeline for transferring data from transactional databases to analytical databases is highlighted, along with business intelligence tools like AWS QuickSight for querying and gaining insights from analytical data.

20:03

🌐 Front-End Hosting and Storage Services in AWS

The focus moves to front-end web applications and the various ways they can be hosted on AWS, including using EC2 instances or object storage like Amazon S3. The paragraph explains the use of Elastic Block Store for VM storage, Elastic File Store for shared file systems, and object storage for storing and serving static website content. It also introduces AWS services like Route 53 for domain management and CloudFront for content distribution and caching.

25:04

🔒 Networking and Security in AWS Cloud

Networking and security are the central themes of this paragraph. It discusses the importance of Virtual Private Cloud (VPC) in creating a secure and isolated network environment within the AWS cloud. The use of subnets for organizing resources into public and private sections is explained, along with the use of VPN and Direct Connect for establishing secure connections between on-premises data centers and AWS VPCs.

30:05

🔁 DevOps Practices and Services in AWS

The script covers DevOps practices in AWS, emphasizing the importance of automation in infrastructure provisioning, application deployment, and observability. It introduces AWS CodePipeline, CodeBuild, and CodeDeploy for CI/CD processes. The paragraph also discusses Infrastructure as Code using AWS CloudFormation, Terraform, and AWS CDK, as well as configuration management with AWS OpsWorks. The importance of monitoring and observability is highlighted with AWS CloudWatch for metrics and logs, and AWS X-Ray for tracing.

35:06

📬 Messaging and Notification Services in AWS

This paragraph introduces messaging and notification services in AWS, such as Amazon SQS for queueing services and SNS for simple notification services. It explains how these services facilitate asynchronous communication between applications and components within the AWS ecosystem.

40:07

🎓 Conclusion and Cloud Certification Courses

In the concluding paragraph, Ranga summarizes the video's goal of providing a high-level overview of AWS services and encourages viewers to pursue cloud certifications through courses offered for AWS, Azure, and Google Cloud. He expresses confidence in the ease of learning cloud technologies and invites viewers to engage with the content by liking, sharing, and subscribing. Ranga also invites feedback on difficult cloud topics, promising to address them in future videos.

Keywords

💡AWS

AWS, or Amazon Web Services, is a comprehensive and widely adopted cloud platform. It is central to the video's theme as it provides a range of services for computing, storage, databases, and more. The script discusses various AWS services such as EC2 for virtual machines, S3 for object storage, and Lambda for serverless computing.

💡EC2 (Elastic Compute Cloud)

EC2 is a service within AWS that provides scalable computing capacity in the cloud. In the video, EC2 is discussed as a foundational service for running applications, with the ability to create virtual machines and handle compute requirements for applications like REST APIs.

💡Elastic Load Balancer (ELB)

An Elastic Load Balancer is used to distribute incoming application traffic across multiple instances. The script mentions ELB in the context of evenly distributing user requests to EC2 instances, ensuring reliability and availability of applications.

💡Auto Scaling Group

Auto Scaling Group is a concept in AWS that allows automatic scaling of EC2 instances up or down based on demand. The video explains how this service can be used to maintain application performance and cost-effectiveness by adjusting the number of active instances.

💡Regions and Zones

In AWS, Regions and Zones refer to the physical locations where data centers reside. The script uses this concept to explain the importance of geographical distribution of resources for high availability and disaster recovery purposes.

💡Elastic Beanstalk

Elastic Beanstalk is a service in AWS that simplifies the deployment and scaling of applications. The video describes it as a managed service that abstracts away much of the infrastructure management, allowing users to focus on their applications rather than the underlying AWS resources.

💡Containers

Containers are a lightweight, standalone, and executable package of software that includes everything needed to run an application. The script discusses the evolution towards containerization as a way to simplify application deployment and management within AWS, mentioning Docker as a popular container runtime.

💡EKS (Elastic Kubernetes Service)

EKS is a managed service in AWS that makes it easy to run Kubernetes, a container orchestration system. The video mentions EKS as a service for managing and scaling containerized applications across a cluster of nodes.

💡Serverless

Serverless computing refers to the execution of code in response to events without the need to explicitly manage the underlying server infrastructure. AWS Lambda is highlighted in the script as a serverless service that runs code in response to events and scales automatically.

💡RDS (Relational Database Service)

RDS is a managed database service in AWS that simplifies the process of setting up, operating, and scaling a relational database. The video discusses RDS as a way to create and manage SQL databases such as MySQL, PostgreSQL, Oracle, or Microsoft SQL Server.

💡DynamoDB

DynamoDB is a fully managed NoSQL database service provided by AWS. The script explains it as a service for applications that require high scalability and flexibility, allowing for storage and retrieval of large volumes of data without the need for complex database management.

Highlights

Introduction to AWS services through a simple application example.

Explanation of Full Stack Application components in AWS.

Deployment of REST API using EC2, Elastic Load Balancer, and Auto Scaling Group.

Concept of Regions and Zones for high availability in AWS.

Introduction to Managed Services like Elastic Beanstalk for simplified deployment.

Evolution to Docker Containers and AWS services supporting them.

Elastic Kubernetes Service (EKS) and Elastic Container Service (ECS) for container orchestration.

Serverless architecture with AWS Lambda for code execution without server management.

Decision-making between SQL and NoSQL databases in AWS.

AWS RDS and Aurora for relational databases, and DynamoDB for NoSQL databases.

AWS Redshift for analytical databases and data warehousing.

AWS Data Pipeline for moving data from transactional to analytical databases.

Serving front-end applications using EC2 instances or S3 for static websites.

Elastic Block Store (EBS) and Elastic File Store (EFS) for VM storage solutions.

S3 as an object storage service for files and static website hosting.

Use of Route 53 for domain naming and CloudFront for content distribution.

Importance of security and networking in AWS with Virtual Private Cloud (VPC).

DevOps practices in AWS with services like CodePipeline, CodeBuild, and CodeDeploy.

Infrastructure as Code with AWS CloudFormation, Terraform, and CDK.

Observability in AWS using CloudWatch for metrics and logs, and X-Ray for tracing.

AWS services for asynchronous communication: SQS and SNS.

Encouragement for viewers to pursue cloud certifications and the presenter's confidence in their ability to succeed.

Transcripts

i'm ranga karnam i'm 10x certified in

aws azure and google cloud as well

our courses are helping thousands of

learners do their cloud certifications

in aws azure and google cloud

in this video let's learn aws we will

take a simple example and understand all

the different services which are present

in aws we'll be exploring more than 50

different aws services with this

specific example

are you ready to get on a ride to learn

aws let's get started the example we are

going to use is a very very simple

application right you have a front-end

application which is talking to a rest

api which is fetching the data from a

typical database and you also have a

reporting workflow let's not really

worry about the reporting workflow right

now let's start with thinking about how

we can

actually implement this specific

front-end application talking to a rest

api talking to a database this is

typically called a full stack

application right so how do we implement

this in aws that's the first thing that

we would start with right now now let's

start with focusing on the rest api part

of it right you'd want to deploy a rest

api

to aws let's say this is a java

application or a python application or a

node.js application which is

part of your rest api what do you need

to run your specific rest api

let's say you are running it in your

data center typically what you need is

something called a virtual machine you

need some kind of compute to be able to

run your application this is what is

called a virtual machine will just one

virtual machine be sufficient

what if this virtual machine goes down

your application will go down and that's

why

in the cloud typically you will not just

have one virtual machine what you'll

have is a group of virtual machines so

you'll have a group of virtual machines

where you would deploy your application

to and when you have a group of virtual

machines what do you need you need to be

able to load balance between them so you

need to set up a load balancer to load

balance the requests between all these

things so you need to have something on

top of this this is nothing but a load

balancer so all the requests from the

user would go to the load balancers

and then from the load balancer they

would flow down to your vms all the

virtual machines

on this virtual machine is where you can

deploy your application maybe if it's a

python application you would install

python and then deploy it in there this

is kind of a simple architecture you can

get started with and if you're

implementing this kind of an

architecture in aws what you can make

use of is something called ec2 elastic

compute cloud elastic compute cloud is

the compute service in aws and

if you'd want to do load balancing what

you would need to do is to use something

called elastic load balancer elastic

load balancer will help you to load

balance between different ec2 instances

one of the things that we have seen in

here is the fact that we want to create

a group of ec2 instances we want to

create a group of virtual machines how

can you do that to be able to create a

group of virtual machines what you need

to do is you would need to actually make

use of

a

concept in aws called auto scaling group

typically when i just need to create one

virtual machine ec2 is sufficient

elastic compute cloud is sufficient

however if i would want to increase the

number of ec2 instances if i would want

to create a group of ec2 instances

that's when i would go for an auto

scaling group

and you'd use an elastic load balancer

to

distribute the load among different ec2

instances which are part of an auto

scaling group so that's how you can

deploy your rest api to aws

one of the things that you can do is you

would want to increase the availability

of your application right what if this

specific vm goes down if this specific

vm goes down your

application also goes down and you don't

want your applications to be down your

application should always be available

to your users how can you ensure that

your applications your vms which are

deployed don't go together down right

they should not go down

both of them together all of them

together right so that's the reason

aws provides you with concepts called

regions and zones what are regions and

zones

let's write them down

regions

and zones what's the concept behind

regions regions and zones typically

whenever you have an enterprise maybe

they have just one data center if you

deploy all your vms to this data center

if this data center goes down your

application goes down completely and

that's the reason why you don't want to

deploy your vms to just one data center

you might want to deploy your vms to

multiple data centers and you don't want

to deploy two data centers in a single

region right this might be let's say in

london you don't want to deploy just to

london

if you want your applications to be

highly available you want to be able to

geographically distribute them as well

maybe you'd want to set up something

similar in new york as well so you'd

want to have something in london

something in new york something in

sydney something in mumbai

and you'd want to create your vms in

there so

this is just the concept of regions and

zones

in aws each of these london for example

new york for example maybe there are

multiple other regions as well aws

offers around 26 different regions

around the world

what these regions allow you to do is to

deploy these vms in different parts of

the world thereby your applications

don't go down

even if the entire geographic location

is going down even if your data center

completely goes down your applications

are still available

so what a asg allows you to do is to

distribute your ec2 instances across

multiple zones so in a single region you

can deploy your ec2 instances across

multiple zones now one of the things

that you would have been seeing until

now is the fact that there is a lot of

complexity that is associated with

setting up a simple thing all that i am

doing in here is i want to set up a rest

api for a python application and already

we are talking about a lot of different

concepts related to aws we are talking

about ec2 instances asg we are talking

about elbs we are talking about region

zones

you might be wondering why do i need to

worry about all this do cloud providers

make it simple for me

yep the cloud providers do make it

simple for you and that's where you can

go for some of the managed services

which are present in the cloud platforms

instead of creating ec2 instances

manually instead of creating auto

scaling groups instead of creating

elastic load balancers you can tell aws

hey aws this is the code i would want to

deploy

if the number of requests come in if a

high load of requests come in then

increase the number of instances if low

if there are less requests coming in

then decrease the number of instances

can you do that automatically for me i

don't want to worry about installing

python i don't want to worry about

installing my application on each of

these vms that's a lot of work for me i

don't want to worry about those

operational details i'll just give you

something like a jar or a war file or a

python deployable unit or a container

image and can you deploy that for me

automatically and can you manage

everything for me that's where main age

services come into picture the main

services which are present for compute

in aws if you just want to set up a

simple setup like this if you want to

like create a load balancer distribute

the load between multiple ec2 instances

in those kind of situations you can go

for this specific service in abs called

elastic bean stock

with elastic bean stock all that you

need to specify

is hey aws can you take this piece of

code and can you deploy this in such a

way that

this is deployed to these many instances

you can also configure auto scaling

basically you can say increase the

number of instances based below based on

the load and decrease the number of

instances based on the load as well so

that's elastic beam stock for you it's a

managed service for compute in aws you

don't really need to worry about load

balance setting up the load balancer

setting up the auto scaling groups

setting up the metrics for it setting up

the ec2 instances you don't need to

worry about what run time what runtime

needs to be available on the ec2

instances you don't need to

worry about that all that you need to do

is to go to elastic bin stock and say i

would want to deploy a java application

here is the jar or a var here is the

container image for it and elastic bean

stock would run it for you so if you

have a simple application simple java

based python based node.js based or any

other language based application you can

use elastic bean stock to deploy to aws

without worrying about managing it you

don't need to worry about availability

scalability you don't need to worry

about increasing the number of instances

and things like that elastic bean stock

takes care of everything for you

one of the other important evolutions in

the last few years is the evolution to

docker containers right instead of

actually trying to create a vm with

multiple layers right so whenever we are

trying to set up an application in the

vm there are a lot of things that you

need to set up first is the underlying

infrastructure of the vm let's not

really worry about it on top of it is

where your os is on top of it is where

your application run time if i would

want to have java application then i

would need to create a java runtime

and on top of it is the code you'd also

need to be able to uh

deep like configure enronment variables

and things like that

right so deploying an application

typically involves a lot of different

steps so if i want to deploy something

to a vm there are a lot of manual steps

involved and to avoid that

we started going towards containers so

we started going towards a container

image so instead of

instead of doing this on the vm what we

can do is we can create a container

image and the container image contains

the os it contains the runtime it

contains the configuration you need and

it also contains the deployable unit or

the code which you would want to be able

to run and once you have a container

image you can go ahead and run this

anywhere you can run it on your local

machine you can run it in the cloud you

can run it on the data center

that's

the concept of containers and docker is

one of the most popular container

runtimes right so docker specifies a

format where

how it specifies how your container

image should be structured and also it

specifies the standards for the

container runtime so it tells this is

how your container run time should be as

well and in aws if you have docker

images you can use elastic bean stock to

run them as well so elastic bean stock

not only supports jars bars python

applications and things like that you

can also give it a container image and

it would ensure that it is deployed in

the right way in an efficient way and it

also enables auto scaling it enables

easy operations and all that stuff

however let's say you have a micro

services architecture where you have a

number of small micro services which are

talking to each other some enterprises

have 10 micro services some enterprises

have 100 micro services some enterprises

have thousands of micro services right

in that kind of a scenario what you can

do is you can go for something

more than just a simple manage service

when you have just one application to

manage elastic bean stock is a really

good thing to go for however when you

would ne when you have multiple

applications multiple micro services to

manage that's when you would need

something complex maybe your rest api is

not just one rest api you have a number

of rest apis which are being exposed in

that kind of situations you can go for

container orchestration solutions which

are present in the cloud if you look at

container orchestration one of the most

popular container orchestration tools do

you want to guess that

yup it is kubernetes right so kubernetes

is the most popular container

orchestration tool today and in aws if

you want to run kubernetes you can say

you can make use of elastic kubernetes

service

and

aws also provides its own container

orchestration service it's called

elastic container service

actually elastic container service is

something which came in even before

kubernetes

so

a lot of customers are making use of ecs

especially aws customers are making use

of ecs

and some of them are actually shifting

towards kubernetes as well so aws offers

both these options elastic container

service and elastic kubernetes service

in elastic kubernetes service and

elastic container service what you need

to do is you need to first create a

cluster

and in the cluster there are multiple

nodes

and to this cluster you can deploy your

applications that's basically the

concept of container orchestration you

create a cluster and you can tell the

cluster i would want this many instances

of this specific container microservice

one five instances microservice two six

instances microservice three ten

instances so on and so forth

in eks and ecs you need to manage the

cluster so you need to take care of

adding nodes to the cluster removing

nodes from the cluster all that would

become your responsibility however if

you want to be able to run something

like this in a serverless way you don't

need to worry about managing the cluster

at all in those kind of situations you

can go for far gate

aws target is a serverless version of

ecs

so you can run ecs in a serverless way

you can run a container in a serverless

way by going for far gate

so until now to run your rest api we

talked about multiple options the first

one which which we talked about is to

create an elastic load balancer create

elastic compute

instances ec2 instances and

use a

asg to create a group of ec2 instances

and use elb to distribute load between

them that's the first option however it

involves a lot of maintenance lot of

headache for you

instead of that you can go for elastic

bean stock

if you have a lot of applications that

you would want to manage maybe you want

to go for container orchestration

solutions that's when you would go for

eks and bcs

in the last couple of decades there is

one more approach which is becoming

popular whenever we talk about

applications we talk about how to deploy

them

how to create the cluster

how to create a load balancer how to

create multiple instances how to install

applications on the server how to

install a runtime how to

deploy the application there and all

those kind of things what if you don't

need to worry about servers so do not

worry

about

servers

that concept is what is called

serverless in serverless you don't worry

about your servers

all that you do is you would give a

piece of code so you give a piece of

code and you tell aws hey aws this is a

piece of code i might get 10 requests i

might get 10 000 requests handle it for

me i don't really want to worry about it

that approach is what is called

serverless approach

and in aws the most popular service to

be able to do that is aws lambda

if you look at the serverless world i

would say

in the serverless functions world aws

lambda is the number one service

i would say almost 80 percent of the

customers who are making use of

serverless functions are running them

using aws lambda

as we talked about earlier when you're

going for aws lambda you don't need to

worry about servers all that you need to

give aws is this is the code this is the

runtime i would want to make use of and

you'll be able to

scale it to whatever limits do you want

aws lambda can't handle that for you if

there are 10 requests it can handle that

for you if there are 10 000 requests it

will handle that for you and the other

important thing is you'll pay by volume

of your request let's say there are 10

000 requests that's what you would pay

for let's say there are zero requests

coming in you don't need to pay anything

at all so if you want to be able to run

your rest api in a serverless way that's

when you would go for aws

lambda

so until now we looked at some of the

main aid services for hosting your

compute related things for hosting your

web application for hosting your rest

api and things like that the options

which we looked at are ec2 elastic load

balancer

we also looked at elastic bean stock you

can go for container orchestration with

eks ecs or you can go for serverless

container option which is target or you

can go for the serverless function

option which is aws lambda i hope this

was very very useful for you let's now

go in into the other world let's go into

the database world right even running

databases is not easy a lot of people

think databases are easy to run however

databases are very very difficult as

well let's say i would want to install a

database on a specific vm i need to

first set up a os i would need to set up

the database runtime oracle or whatever

then i would need to create my database

and then create my data right so

managing a database is also not easy and

doing operations for databases also is

very very tough if you want to take a

backup of this if you want to ensure

point in time recovery right let's say

some problem happened and i would want

to be able to recover to a state my

database was in yesterday that is what

is called point in time recovery your

databases typically you need point in

time recovery and you don't want to lose

data so you want high durability for

your databases and in addition you would

want high availability there might be a

lot of applications which are talking to

your database and your database should

be highly available setting up high

availability setting up scalability

setting up

operations everything for your database

is very very complex and that's the

reason why you don't want to create an

ec2 instance and set up a database on it

if you create a ec2 instance install

database set it up you need to also take

care of availability you might want to

create another database another copy of

it in maybe another zone

or another region and those kind of

things become really really complex you

don't really want to be doing that when

you go to the cloud that's where you

would go for managed database services

so just like there are managed compute

services there are managed database

services also present in the cloud these

manage database services help you to

easily create databases and

run them in the cloud

whenever you want to create a database

the first option that you need to think

about is do i want to create a sql

database or do i want to create a nosql

database right

i'm using sql as an abbreviation for

relational databases

right so you might want to create a

relational database tables relationships

foreign keys primary keys and all that

fun stuff or you want flexibility i

would want huge scalability right that's

when you go for nosql databases when you

go to relational databases there is

perfect structure so there is a

structure in which you need to

create your data

there are proper relationships

it is not really flexible and

relational databases typically can scale

only to a limited extent however nosql

databases don't have any structure

typically they are very very flexible

with this structure but they provide you

with high scale

so depending on your specific use case

you would want to go for a relational

database or a nosql database if you have

a banking application and you are

managing banking transactions in those

kind of situations transaction

management is very very important in

those kind of situations you would go

for relational databases let's say i

have a social media application or

like let's say i have linkedin or

twitter or facebook in this kind of

situations

transactions might not be so important

little bit of cons inconsistency in the

data might be okay if i'm posting a

tweet it might not go at the same time

to all the people that's okay

in those kind of situations we would go

for nosql databases when we go for nosql

databases we need high scale we would

want millions of transactions per second

right so that's the situations in which

you go for nosql databases in aws the

most popular relational database is rds

relational database service if you want

to run mysql or oracle or sql server

that's where you'd go for rds there is

another option which is very very

popular in aws which is called aurora

it's also called amazon aurora

so if you want a regional database and

if you want to scale only to a certain

extent maybe the maximum typically

allowed is 64 terabytes so if your data

fits in with these requirements and if

you just want a regional database then

you can go for rds with mysql or rds

with postgresql

or rds with sql server or oracle but if

you want a global relational database in

those kind of situations you can go for

aurora this provides you with

99.9 percent availability which is

considered to be really really really

high

it provides transactions it provides

high scalability and all the things that

you typically need from a relational

database

so that's one of the options for your

database so depending on the type of

application you are creating you might

choose between relational database or

nosql databases if you go for relational

databases in aws you have the option to

go to aws ids or you can go for rora

now let's say you want to go for a nosql

database for your transactional

application let's say you are creating a

social media application for you

consistency is not so important but

scale is very very important you would

want to be able to scale it to millions

of transactions per second in those kind

of situations you would go for nosql

databases and typically the database you

would go for in aws is dynamo db

dynamodb is the most popular nosql

service in aws this is something called

a document database you would store your

data as json documents and

you can actually create indexes on

specific elements of your documents and

you also have a lot of flexibility a

specific document might have certain

details a specific another document in

the same table might not really have the

same amount of details

so these are some of the important

database options when it comes to

transactional applications right

transactional applications make small

changes like small updates small deletes

ads and things like that these are

typically online applications a web

application is typically a transactional

application right a shopping application

or a banking application these are all

transactional applications

now are there just transactional

applications

no you might have some reporting

applications some business intelligence

relation related applications as well

that's when you would go for analytical

databases

for example one of the most popular

analytical solutions is something called

hadoop right you can run hadoop in aws

as well and aws provides its own

solutions as well in aws if you want to

run analytical database one of the

recommended options is to go for

redshift

aws redshift is one of the popular ones

you can actually have petabytes huge

volumes of data and you can actually run

compute or queries against this huge

volume of data with very very high

performance

right whenever we talk about a

relational database or actually a

transactional database versus analytical

database the difference is

in terms of the operations which are

performed in the case of a transactional

database there would be a small amount

of

large number of transactions right so

what we are talking about in here is

there would be small updates maybe one

row is updated or three rows are updated

ten rows are updated or five rows are

inserted four rows are basically deleted

so these kind of these are the kind of

operations which are performed on

transactional databases however when we

are talking about analytical databases

typically you load the data in bulk you

will take all the data from a

transaction database and load it in bulk

into the analytical database but what

you would be doing from here is running

a lot of queries lot of very very

complex queries you'd want to get

intelligence so when when it comes to

analytical databases you have one-time

loads maybe once a day or once a week or

things like that and you have huge

volumes of reads you have queries which

are running which are very very complex

and that's the reason why analytical

databases are optimized for reads huge

volumes of reads across huge volumes of

data and in aws the recommended option

is redshift you'd go for this when you

have analytical workloads that you'd

want to run in aws

now how do you get the data from your

relational database or from your

transactional database into your

analytical database that's when

you can go for a data pipeline so aws

provides

a

service called aws data pipeline

aws data pipeline can create data from

your database

from your transaction database and load

it into an analytical database as well

and aws also provides business

intelligence solutions so you can use

something like aws quick site or

something of that kind to read from your

analytical database and get intelligence

to be able to run queries and all that

stuff around this

right so

after focusing on the compute part this

is basically rest api is in the compute

part

we shifted our attention to the database

part we talked about how you can run

databases in aws we talked about

relational databases

rds aurora and we talked about nosql

databases one of the most popular ones

is dynamodb and we also talked about

analytical databases redshift you can

also run hadoop using a managed service

in aws as well and we also talked about

business intelligence

for example something like aws quick

site

now let's shift our attention to the

front end right until now this is the

part which we did not really talk about

so let's say we have

a web application that we want to serve

a react application or a angular

application that's what we would want to

serve

in the front end one of the options you

have is to use ec2 instances as well so

over here you can create an ec2 instance

you can put the web application there

and you can also set up load balances to

serve this static application which is

deployed onto ec2 instance or you can

actually set up a web server on the ec2

instance and serve it from your elastic

load balancer so that's one of the

options you always have when you want to

serve a front-end application but it

again is a lot of operational details

and that's where aws provides another

service which is actually not related to

running applications at all but it also

helps you to

expose a static website now before we

get there let's talk a little bit more

about storage services which are present

in aws why do we need storage

let's say i have a virtual machine right

i have a virtual machine

i would want to attach a hard disk with

it i would want to attach a simple hard

disk with it what is the service you can

make use of in aws

in aws to create virtual machines you

can make use of ec2 and when you are

creating a virtual machine with ec2 what

happens is a hard disk is automatically

created for you

and the service which is used to create

this hard disk for you is called elastic

block store

so elastic block store is the service

which is used to create a hard disk and

attach to it with your vm

you can also create file shares so if i

want to create a file share and share it

between multiple ec2 instances multiple

maybe instance from my data center in

those kind of situations i can go for

something called efs

elastic file store

so what we are talking about over here

are storage devices which are attached

to your vms so there are a number of

storage devices you have and you can

attach it with multiple vms whenever we

talk about elastic block store we are

talking about something like a hard disk

a hard disk at a particular point in

time can only be attached to a single vm

however whenever we're talking about

elastic file store what we are talking

about is something which can be shared

so this one if you are creating using

efs can be shared between multiple

devices

now this is one kind of a use case where

you want to attach storage with your

virtual machines

let's talk about a few other use cases

related to storage let's say you have

users who are uploading files to a

website and you would want to store all

those files in a particular place you

can use a database but databases are not

optimized for storing files let's say

these are large video files or large

audio files are large images things like

that so these are all objects you'd want

to be able to store this with a key

value pair so the value is the

file itself and the key is a unique

thing you give to identify a specific

thing

right so when you want to go do some

things like that that's when you go for

something called object storage

so in object storage you can create

buckets and you can store value store

objects using key value pairs so you can

say this is the key this is the value

and you can store text files you can

store images you can store

video files audio files any kind of

files can be stored in object storage

using a simple rest api so this provides

you with a rest api and you can use the

rest api to upload objects to retrieve

objects using their keys and values

and object storage also provides a lot

of other use cases you can store archive

files in here if you are migrating data

from let's say an on-premise to the

cloud you can use object storage as a

temporary store you can first load the

data into

create an archive for your database put

it into object store and from there you

can load it into your specific database

in the cloud so there are a lot of

purposes which an object storage can be

used for

one of the other purposes which it can

be used for is to create a static

website if you upload all your static

files your css files images your html

content all of them if you create it if

you create a bucket and upload it into

an object storage you can expose it from

your

object storage as a website so once the

content is there in an object storage

you can even expose a static website and

when it comes to aws this is the most

preferred way of

exposing a static website what you can

do is you can make use of s3 so you can

use the s3 which is the object storage

service it's also called simple storage

service s3 is one of the actually most

popular aws services because it's one of

the first aws services as well

so you can use s3 and you can actually

deploy

your front end into a bucket in s3 and

you can serve it from there and if you

want to actually give a name let's say

you want to expose it at a website so i

would want to expose it at

www.in28

minutes.com

then i can even

you i can make use of some a service in

aws called route 53 so route 53 is the

domain naming service in aws and let's

say i would want to cache the content

this is static content which can be

cached

in those kind of situations i can make

use of cloud front cloudfront

can be used

to cache and distribute your content to

around the world right the content in s3

you'd want it to be available for users

across the globe

from different continents what you can

do to make latency lower is to

distribute it across the world and

that's what cloudfront can do for you so

you can use cloudfront as a distribution

mechanism for your static content to

distribute it around the world you can

use route53 to name your website

until now we talked about a varied range

of services which are present in aws we

talked about rest api which is your

compute we talked about different

compute services we talked about

different

relational database services which are

typically used for transactional

applications we talked about analytical

databases as well

and we talked about business

intelligence as well and right now in

the last few minutes we were talking

about the front-end application which is

typically deployed to object storage

in aws which is s3 and we also talked

about

how you can actually give it a name

www.inqtmintz.com you can do that in

route53 you can buy a domain name you

can associate it with your

content which is present in s3

and we also talked about cloud front

which is used to distribute your static

content across the world so that users

get

low latency so that kind of at a high

level

some of the important services we wanted

to touch upon

one thing which we did not really talk

about at all is security right security

is very very important one of the most

important things that you need to

realize is the fact that

aws is a shared cloud platform whenever

you make use of infrastructure in aws

that infrastructure is shared between

multiple enterprises so if you are

creating a vm it might be on the same

hardware as we have as some other

customers so security is very very

important you want to be able to

separate the traffic which is going into

your application from other applications

which belong to other enterprises let's

say

i have a simple

application

which is talking to a database

the traffic which is going on between

them will not be visible to outside

world if you are running it within a

data center but over here in the cloud

we are running it in a cloud

and there might be other applications

which might be deployed over here and

that's where you want to separate the

traffic out you want to control the

entire traffic which is going into your

devices

and to your databases how can you do

that that's where you can go for a

concept called vpc

so what we can do is we can create a vpc

virtual private cloud networking is a

concept which a lot of us as a

programmer might not be familiar with

please bear with me understanding

networking is very very important when

you go to the cloud because

we don't understand networking as well

right when you go to the cloud security

becomes really really important inside

the data center all the applications are

belonging to one enterprise so security

might not be so important but once you

go into the cloud security becomes

really really important because we are

making use of shared infrastructure and

the way you can actually implement

security the way you can actually

control traffic which is going into your

applications is through these concepts

called vpcs and subnets

so

if you create a vpc you can control all

the traffic which is going inside the

vpc and all traffic which is going

outside the vpc you can set up rules

saying this traffic is allowed this kind

of traffic is not allowed

right so basically

a vpc

has rules

route tables where you can define the

different rules and also there might be

different kinds of applications which

are present in a vpc let's say this is a

web application and i would want to be

able to access this from the internet so

there'd be users could be accessing it

over internet however this database i

don't want it to be accessed from the

internet i only want it to be accessed

from other applications or from other

devices which are part of this network

only

so there are different use cases for

different kinds of resources you create

in a specific vpc and that's where we

can go for subnets subnets allow you to

configure different rules

for different things so you anything

that you create within a private subnet

so

let's call this a private subnet

and let's call this a public subnet

anything you can you create in the

public subnet

can be accessed from the outside world

directly anything you create in a

private subnet cannot be out access from

outside world you should either con talk

to them from another resource which is

present in the private subnet or you can

talk to it from

the public subnet and you can configure

rules to allow what is allow actually to

you can configure rules to decide what

is allowed and what is not allowed as

well so

you can separate resources which are

present into vpc in the vpc into

different groups by using subnets you

would put all the things which you want

to allow access from internet in a

public subnet you'd want you would put

all things which you don't want to allow

access from the internet in a private

subnet

so typically a web application something

you'd want to be allowing access from

internet will be going into a public

subnet and

in the private subnet is where you put

all the things like a database for

example or any storage devices you don't

want to allow access from outside so all

those things would be put inside a vpc

now you might be creating a number of

resources in the cloud right

you might also have your own data center

so you might have your own data center

which is being made use of by your

corporate and you want to establish

connection between different resources

so you would want to be able to have

your resources which are near data

center talk to resources which are

present inside your vpc how can you do

that

that's where we go for a concept called

vpn vpn is over internet so you

establish a connection between your

cloud

between your vpc which is present in the

cloud and your data center by making use

of managed vpn in aws

however one thing to remember is that

this traffic goes over internet and

that's why the traffic is encrypted

using ipsec protocol

however you might be thinking hey i

don't want to i love traffic over

internet i would want to create a

dedicated connection

in those kind of situations you can also

create a dedicated connection this is

called direct connect so you can

establish a direct connect from

your data center

to

the aws cloud to the specific region

where your vpc is present in

until now we touched upon some of the

important aspects related to aws we

talked about a lot of aws services now

before we conclude i'll talk about a

couple of more aws services which might

be interesting for you let's say this

rest api wants to talk to a queue so you

might have other applications which are

listening on this queue and they are

consuming the messages which are coming

in here the popup queueing service in

aws is sqs amazon sqs is a queuing

service typically whenever we talk about

applications you would want to prefer

asynchronous communication so sqs

provides you asynchronous communication

sometimes let's say a object is uploaded

on s3

you want to get an email or you'd want

to like receive a notification in those

kind of situations you can go for sns

sns is simple notification service

so what we are talking about are high

level some of the important services

which are related to setting up your

applications

one aspect which we did not talk about

until now is

the devops aspect right so whenever we

talk about

uh applications and whenever we talk

about deploying them to the cloud devops

becomes really really important you

would want to automate everything

related to provisioning of your

infrastructure deploying your

application and all the things related

to that and that's what is typically

called devops whenever we talk about

devops we talk about a lot of things

right we talk about continuous

integration continuous deployment we

talk about infrastructure as code how do

you automate the creation of your

infrastructure how do you automate the

provision configuration of your virtual

servers which are created in the cloud

and we also talk about observability we

would want to be able to see what's

happening in your infrastructure you

want to be able to get metrics logs

traces and all those kind of things

right let's quickly look at all the

services which are related to that if

you want to do ci cd if you want to do

devops in aws the service is aws

pipeline you can use aws pipeline to

create

pipelines there is also a service called

code build

and we have a service called code deploy

so if you want to build a docker image

or a jar file or a wire file you can

make use of aws code build and if you

want to deploy it to elastic bean stock

or if you want to deploy it to any other

maintenance service which is present in

aws or if you want to deploy to a ec2

instances you can make use of code

deploy so you can make use of these two

as part of your pipelines to deploy your

applications in aws

now infrastructure as code typically has

two parts one is provisioning the

infrastructure so let's say earlier we

talked about

creating a vpc creating subnets

creating an application maybe a ec2

instance or elastic beam stock and maybe

creating a database and then

allowing them to talk to each other

configuring the rules related to that

right so you need to create the

infrastructure

you don't want to do that manually

because in typically there are multiple

environments they have qa stage

production

the moment you do it manually the chance

that you make mistakes are very very

high you don't want that to happen and

that's where you want to automate the

provisioning of infrastructure

if you want to automate the provisioning

of infrastructure there are three

different options

one is cloud formation cloud formation

is one of the

first

infrastructure provisioning tools which

was provided by aws basically you write

a lot of complex scripts to provision

the infrastructure typically these

scripts even for simple applications can

be running into thousands of lines and

that's where a cloud neutral solution

called terraform became really really

popular with terraform you can write

simple scripts

to provision your infrastructure and an

alternative which aws provides now is

something called cdk in cdk you can

write java programs python programs or c

programs to provision your

infrastructure

the other option you can also make use

of

in infrastructure as code is

configuration management what is

configuration management let's say i

have 100 vms i would want to install a

security patch on them or let's say i

have a lot of vms on which i would want

to update the application software in

those kind of situations we make use of

configuration management if you look at

if you look at the open source world

some of the popular ones are ansible

chef

and puppet

and in aws the main service is aws ops

works

so you can manage multiple vms you can

install software do a lot of things

around that using your aws ops works so

these are the things which are related

to infrastructure as code now when it

comes to observability typically we talk

about a lot of different things right so

we have

tracing

we have logs

and we have metrics

cpu consumption or cpu utilization on

specific em that's a metric

logs which are coming from your

applications logs which are coming from

your managed services logs which are

coming from your load balancers these

are all logs

your applications might be going across

multiple microservices right so your

request sorry your request can be going

across multiple micro services and

that's where you would want to trace the

request across multiple micro services

just having a piece of log might not be

sufficient what i would want to be able

to do is to use that piece of log and to

be able to trace the request across

multiple micro services that's where

tracing becomes really really important

in aws the services for the service for

metrics and logs is aws cloud watch

so aws cloudwatch is for metrics aws

cloudwatch logs is for logs so this is a

centralized place where you can send all

the logs from your applications from all

the managed services in

aws as well and metrics all the metrics

around your cpu utilization your

application related metrics all of them

can be sent to airbus cloudwatch and for

tracing

you can send all your tracing

information to aws x-ray this is the

tracing service in aws okay those are

some of the important aspects related to

devops in aws the idea of this specific

video was to give you a high level

overview around aws typically we are

used to deploying applications in our

data centers i just wanted to take one

of such examples and give you a high

level overview of how you can do things

uh with aws in uh

in a lot of high level detail right it's

not really detailed i mean we did not

really set up anything manually we did

not create anything in aws but the idea

was to give you a 10 000 feet overview

of everything in aws i hope this was

really really useful if you are able to

make sense of at least 50 to 60 of this

video i think that's good success for me

and if you actually made uh like if 50

to 60 of this video made sense then i

think you are ready to go for a cloud

certification i would recommend you to

check out any of our aws azure or google

cloud certification courses at least the

beginner ones may be something like

azure fundamentals az 900 or even

something like uh cloud practitioner aws

cloud practitioner might be a good place

to start

if you're going for google cloud google

cloud digital leader might be a good

place to start typically if you are able

to understand some of the stuff which is

present in here about 50 to 60 of this

stuff which is present in this specific

video i think you can complete the cloud

certifications in about two to four

weeks

uh i i was so confident that somebody

can

clear cloud certifications easily that i

call my az900 certification as az 900 in

a weekend so i call it azure

fundamentals in a weekend that's how

confident i am that learning the cloud

is very very easy so hopefully

i made them as simple as possible the

goal was to just uh come up come on like

draw a picture kind of make it easy for

you to understand aws because once you

understand the big picture once you

understand things at the high level you

can dig in and find out things in a much

much easier way and

over the last few years i've been

working with aws a lot i thought

it would be great if somebody can create

something like this which would be

useful for beginners especially if you

are really really beginner to the cloud

to get the high level landscape of the

cloud so that's the goal of this

specific video i hope you liked it

i'm sure you had a great time watching

this video

do not keep it to yourself tell your

friends and tell youtube as well how do

you do that

like share and subscribe if you are

looking to get cloud certified check out

our cloud certification courses in aws

azure and google cloud and do not forget

to check out the other videos in this

series of videos on cloud fundamentals

if there is a cloud topic that you are

feeling it very very difficult to

understand do post it in the comments

and we will make it simple for you i am

sure you had a great time watching this

video and i'll see you again very very

soon until then here's bye from ranga at

in 28 minutes see you soon