Cloud Computing Full Course 2026 | Cloud Computing Tutorial | Cloud Computing Course | Simplilearn

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Cloud computing is quickly changing the tech world and cloud engineers are great in demand. As more businesses move online, the need for expert who knows the cloud is growing fast and by 2025 this field will explode with opportunities. That means good pay, many job options and a chance to work with the newest technology. Sounds exciting, right? In this course, we'll guide you from the basics of cloud computing to advanced topic like cloud security and comparing top platforms like AWS and Azure. You'll also get hands-on projects and tips on certifications to help you get noticed by employers. Before we begin, if you are interested in getting certified in cloud, check out SimplyLearn's cloud architect certification program. built expertise in AWS Microsoft Azure and GCP with our cloud architect certification course. Plus, we have included an exam voucher for any one Azure course so you can get certified hassle-free. Gain access to official AWS authored self-arning content and master the ins and out of cloud architecture principles. Learn how to design and develop scalable services on various cloud platforms all in one comprehensive course. Let's build your cloud expertise today. Before cloud computing existed, if we need any IT servers or application, let's say a basic web server, it does not come easy. Now, here is an owner of a business. And I know you would have guessed it already that he's running a successful business by looking at the hot and fresh brewed coffee in his desk and lots and lots of paperwork to review and approve. Now he had a smart not only smartlooking but a really smart worker in his office called Mark. And on one fine day he called Mark and said that he would like to do business online. In other words, he would like to take his business online and for that he needed his own website as the first thing and Mark puts all his knowledge together and comes up with this requirement that his boss would need lots of servers uh database and softwares to get his business online which means a lot of investment. And Mark also adds that his boss will need to invest on acquiring technical expertise to manage the hardware and software that they will be purchasing and also to monitor the infrastructure. And after hearing all this, his boss was close to dropping his plan to go online. But before he made a decision, he chose to check if there are any alternatives where he don't have to spend a lot of money and don't have to spend acquiring technical expertise. Now that's when Mark opened this discussion with his boss and he explained his boss about cloud computing and he explained his boss the same thing that I'm going to explain to you in some time now about what is cloud computing. What is cloud computing? Cloud computing is the use of a network of remote servers hosted on the internet to store manage and process data rather than having all that locally and using local server for that. Cloud computing is also storing our data in the internet from anywhere and accessing our data from anywhere throughout the internet. And the companies that offer those services are called cloud providers. Cloud computing is also being able to deploy and manage our applications, services and network throughout the globe and manage them through the web management or configuration portal. In other words, cloud computing service providers give us the ability to manage our applications and services through a global network or internet. Example of such providers are Amazon web service and Microsoft Azure. Now that we have known what cloud computing is, let's talk about the benefits of cloud computing. Now I need to tell you the cloud benefits is what is driving cloud adoption like anything in the recent days. If I want an IT resource or a service now with cloud, it's available for me almost instantaneously and it's ready for production almost the same time. Now this reduces the go live date and the product and the service hit the market almost instantaneously compared to the legacy environment and because of this the companies have started to generate revenue almost the next day if not the same day. Planning and buying the right size hardware has always been a challenge in legacy environment. And if you're not careful when doing this, we might need to live with a hardware that's undersized for the rest of our lives. With cloud, we do not buy any hardware. But we use the hardware and pay for the time we use it. If that hardware does not fit our requirement, release it and start using a better configuration and pay only for the time you use that new and better configuration. In legacy environments, forecasting demand is an full-time job. But with cloud, you can let the monitoring and automation tool to work for you and to rapidly scale up and down the resources based on the need of that R. Not only that, the resources, services, data can be accessed from anywhere as long as we are connected to the internet. And even there are tools and techniques now available which will let you to work offline and will sync whenever the internet is available. Making sure the data is stored in durable storage and in a secure fashion is a talk of the business and cloud answers that million-doll question. With cloud the data can be stored in an highly durable storage and replicated to multiple regions if you want and uh the data that we store is encrypted and secured in a fashion that's beyond what we can imagine in local data centers. Now let's bleed into the discussion about the types of cloud computing. Very lately there are multiple ways to categorize cloud computing because it's ever growing. Now we have more categories. Out of all these six sort of stand out you know categorizing cloud based on deployments and categorizing cloud based on services and again under deployments categorizing them based on how they have been implemented. You know is it private is it public or is it hybrid and again categorizing them based on the service it provides. Is it infrastructure as a service or is it platform as a service or is it software as a service? Let's look at them one by one. Let's talk about the different types of cloud based on the deployment models. First, in public cloud, everything is stored and accessed in and through the internet. And um any internet users with proper permissions can be given access to some of the applications and resources. And in public cloud, we literally own nothing. Be it the hardware or software, everything is managed by the provider. AWS, Azure and Google are some examples of public cloud. Private cloud on the other hand with private cloud the infrastructure is exclusively for an single organization. The organizations can choose to run their own cloud locally or choose to outsource it to a public cloud provider as managed services. And when this is done, the service the infrastructure will be maintained on a private network. Some examples are VMware cloud and some of the AWS products are very good example for private cloud. Hybrid cloud has taken things to the whole new level. With hybrid cloud, we get the benefit of both public and private cloud. Organizations will choose to keep some of their applications locally and some of the application will be present in the cloud. One good example is NAZA. It uses hybrid cloud. It uses private cloud to store sensitive data and uses public cloud to store and share data which are not sensitive or confidential. Let's now discuss about cloud based on service model. The first and the broader category is infrastructure as a service. Here we would uh rent the servers network storage and we'll pay for them in an hourly basis but we will have access to the resources we provision and for some we will have root level access as well. EC2 in AWS is a very good example. It's a WM for which we have root level access to the OS and admin access to the hardware. The next type of service model would be platform as a service. Now in this model the providers will give me a pre-built platform where we can deploy our codes and our applications and they will be up and running. We only need to manage the codes and not the infrastructure. Here in software as a service the cloud providers sell the end product which is a software or an application and we directly buy the software on an subscription basis. It's not the infra or the platform but the end product or the software or a functioning application and we pay for the hours we use the software and in here the client maintains full control of the software and does not maintain any equipment. Amazon and Azure also sell products that are software as service. This chart sort of explains the difference between the four models starting from on premises to infrastructure as a service to platform as a service to software as a service. This is self-explanatory that uh the resource managed by us are huge in on premises that towards your left as you watch and it's little less in infrastructure as a service as we move further towards the right and further reduced in platform as a service and there's really nothing to manage when it comes to software as a service because we buy the software not any infrastructure component attached to it. Now let's talk about the life cycle of the cloud computing solution. The very first thing in the life cycle of a solution or a cloud solution is to get a proper understanding of the requirement. I didn't say get the requirement but said get a proper understanding of the requirement. It is very vital because only then we will be able to properly pick the right service offered by the provider. Getting a sound understanding the next thing would be to define the hardware. Meaning choose the comput service that will provide the right support where you can resize the compute capacity in the cloud to run application programs. Getting a sound understanding of the requirement helps in picking the right hardware. One size does not fit all. There are different services and hardwares for different needs you might have like EC2 if you're looking for is and lambda if you're looking for serverless computing and ECS that provides containerized servers. So there are a lot of hardware available. Pick the right hardware that suits your requirement. The third thing is to define the storage. Choose the appropriate storage service where you can back up your data and a separate storage service where you can archive your data locally within the cloud or from the internet and choose the appropriate storage. There is one separately for backup called S3 and there is one separately for archival that's for glacier. So you know you knowing the difference between them really helps in picking the right service for the right kind of need. Define the network. Define the network that securely delivers data, video and applications. Define and identify the network services properly. For example, VPC for network, route 53 for DNS and direct connection for private P2P line from your office to the AWS data center. Set up the right security services. IM for authentication and authorization and KMS for uh data encryption at rest. So there are variety of security products available. We got to pick the right one that suits our need. And there are a variety of deployment and automation and monitoring tools that you can pick from. For example, cloudatch is for monitoring. Autoscaling is for being elastic and cloud formation is define the management process and tools. You can have complete control of your cloud environment if you define the management tools which monitors your AWS resources and or the custom applications running on AWS platform. There are variety of deployment automation and monitoring tools you can pick from like cloudatch for monitoring, autoscaling for automation and cloud formation for a deployment. So knowing them will help you in defining the life cycle of the cloud computing solution properly. And similarly there are a lot of tools for testing a process like codear and code build and code pipeline. These are tools with which you can build, test and deploy your code quickly. And finally once everything is said and done pick the analytic service for analyzing and visualizing the data using the analytics services where we can start quering the data instantly and get a result. Now if you want to visually view the happenings in your environment you can pick attenna and other tools for analytics or EMR and which is elastic map produce and cloud search. Thanks guys. Now we have Samuel and Rahul to take us through the full course in which they will explain basic framework of Amazon Web Services and explore all of its important services like EC2, Lambda, S3, AM and cloud formation. We'll also talk about Azure and some of its popular services. Hello everyone. Let me introduce myself as Sam, a multiplatform cloud architect and trainer. And I'm so glad and I'm equally excited to talk and walk you through this session about what AWS is and talk to you about some services and offerings and about how companies get benefited by migrating their applications and infra into AWS. So what's AWS? Let's talk about that. Now before that let's talk about how life was without any cloud provider and in this case how life was without AWS. So let's walk back and picture how things were back in 2000 which is not so long ago but lot of changes lot of changes for better had happened since that time. Now back in 2000 a request for a new server is not an happy thing at all because lot of uh money lot of uh validations lot of planning are involved in getting a server online or up and running. And even after we finally got the server it's not all said and done. A lot of optimization that needs to be done on that server to make it worth it and get a good return on investment from that server and uh even after we have optimized for a good return on investment the work is still not done. There will often be a frequent increase and decrease in the capacity and you know even news about our website getting popular and getting more hits. still an bittersweet experience because now I need to add more servers to the environment which means that it's going to cost me even more. But thanks to the present-day cloud technology, if the same situation were to happen today, my new server, it's almost ready and it's ready instantaneously. And with the swift tools and technologies that Amazon is providing in provisioning my server instantaneously and adding any type of workload on top of it and making my storage and server secure, you know, creating a durable storage where data that I store in the cloud never gets lost with all that features. Amazon has got our back. So let's talk about what is AWS. There are a lot of definitions for it but u I'm going to put together a simple and a precise definition as much as possible. Now let me iron that out. Cloud still runs on an hardware. All right. And uh there are certain features in that infrastructure in that cloud infrastructure that makes cloud cloud or that makes AWS a cloud provider. Now we get all the services, all the technologies, all the features and all the benefits that we get in our local data center like you know security and compute capacity and uh databases. And in fact you know we get even more cool features like uh content caching in various global locations around the planet. But again out of all the features the best part is that I get or we get everything on a pay as we go model. The less I use, the less I pay. And the more I use, the less I pay per unit. Very attractive, isn't it? Right. And that's not all. The applications that we provision in AWS are very reliable because they run on an reliable infrastructure and it's very scalable because it runs on an ondemand infrastructure and it's very flexible because of the designs and because of the design options available for me in the cloud. Let's talk about how all this happened. AWS was launched in uh 2002 after the Amazon we know as the online retail store wanted to sell their remaining or unused infrastructure as a service or as an offering for customers to buy and use it from them you know sell infrastructure as a service the idea sort of clicked and uh AWS launched their first product first product in 2006 that's like 4 years after the idea launch and In 2012, they held a big-sized customer event to gather inputs and concerns from customers and they were very dedicated in making those requests happen. And that habit is still being followed. It's still being followed as u reinvent by AWS and at 2015 Amazon announced its revenue to be 4.6 billion. And in 2015 through 2016, AWS launched products and services that help migrate customer services into AWS. Well, there were products even before, but this is when a lot of focus was given on developing migrating services. And in the same year, that's in 2016, Amazon's revenue was 10 billion. And not but not the least as we speak Amazon has more than 100 products and services available for customers and get benefited from. All right, let's talk about the uh services that are available in uh Amazon. Let's start with this product called S3. Now S3 is an great tool for internet backup and it's it's the cheapest storage option in the object storage category. And not only that, the data that we put in S3 is retrievable from the internet. S3 is really cool. And we have other products like migration and data collection and data transfer products. And here we can not only collect data seamlessly but also in a realtime way monitor the data or analyze the data that's being received that there cool products like uh AWS data transfers available that helps achieve that. And then we have products like uh EC2 elastic compute cloud that's an resizable computer where we can anytime anytime alter the size of the computer based on the need or based on the forecast. Then we have simple notification services systems and tools available in Amazon to update us with notifications through email or through SMS. Now anything anything can be sent through email or through SMS if we use that service. could be alarms or uh it could be service notifications if you want stuff like that. And then we have some security tools like KMS key management system which uses AES 256bit encryption to encrypt our data at rest. Then we have Lambda a service for which we pay only for the time in seconds. Seconds it takes to execute our code. And uh we're not paying for the infrastructure here. It's just the seconds the program is going to take to execute the code. So if it's a short program, we'll be paying in milliseconds. If it's a a bit bigger program, we'll be probably paying in uh 60 seconds or 120 seconds. But that's lot cheap, lot simple and lots cost effective as against paying for service on an hourly basis, which a lot of other services are. Well, that's cheap, but using lambda is a lot cheaper than that. And then we have services like uh route 53, a DNS service in the cloud. And now I do not have to maintain an DNS account somewhere else. and my cloud environment with AWS. I can get both in the same place. All right, let me talk to you about um how AWS makes life easier or how companies got benefited by using AWS as their IT provider for their applications or for the infrastructure. Now, Uni liver is a company and um they had a problem, right? And they had a problem and they picked AWS as a solution to their problem, right? Now this company was sort of spread across 190 countries and they were relying on a lot of digital marketing for promoting their products and their existing environment their legacy local environment proved not to support their changing IT demands and uh they could not standardize their old environment. Now they chose to move part of their applications to AWS because they were not getting what they wanted in their local environment. And since then you know rollouts were easy, provisioning your applications became easy and even provisioning infrastructure became easy and they were able to do all that in push button scaling and uh needless to talk about uh backups that are safe and backups that can be securely accessed from the cloud as needed. Now that company is growing along with AWS because of their swift speed in rolling out deployments and uh being able to access secure backups from various places and generate reports and in fact useful reports out of it that helps their business. Now on the same lines let me also talk to you about Kelloggs and how they got benefited by using Amazon. Now Kelloggs had a different problem. It's one of its kind. Now their business model was very dependent on uh an infra that will help to analyze data really fast right because they were running promotions based on the analyzed data that they get. So they being able to respond to the analyzed data as soon as possible was critical or vital in their environment and luckily SAP running on Hannah environment is what they needed and uh you know they picked that service in the cloud and that sort of solved the problem. Now the company does not have to deal with maintaining their legacy infra and maintaining their heavy compute capacity and maintaining their database locally. All that is now moved to the cloud or they are using cloud as their IT service provider and and now they have a greater and powerful IT environment that very much complements their business. Hi there, I'm Samuel, a multiplatform cloud architect and I'm very excited and honored to walk you through this learning series about AWS. Let me start the session with this scenario. Let's imagine how life would have been without Spotify. For those who are hearing about Spotify for the first time as Spotify is an online music service offering and it offers instant access to over 16 million licensed songs. Spotify now uses AWS cloud to store the data and share it with their customers. But prior to AWS, they had some issues. Imagine using Spotify before AWS. Let's talk about that. Back then, users were often getting errors because Spotify could not keep up with the increased demand for storage every new day. And that led to users getting upset and users cancelling the subscription. The problem Spotify was facing at that time was their users were present globally and were accessing it from everywhere and uh they had different latency in their applications and Spotify had a demanding situation where they need to frequently catalog the songs released yesterday, today and in the future. And this was changing every new day and the songs coming in rate was about 20,000 a day. And back then they could not keep up with this requirement and needless to say they were badly looking for way to solve this problem and that's when they got introduced to AWS and it was a perfect fit and match for their problem. AWS offered a dynamically increasing storage and that's what they needed. AWS also offered tools and techniques like storage life cycle management and trusted advisor to properly utilize the resource so we always get the best out of the resource used. AWS address their concerns about easily being able to scale. Yes, you can scale the AWS environment very easily. How easily, one might ask. It's just a few button clicks. And AWS solved Spotify's problem. Let's talk about how it can help you with your organization's problem. Let's talk about what is AWS first and then let's bleed into how AWS became so successful and the different types of services that AWS provides and what's the future of cloud and AWS in specific. Let's talk about that and finally we'll talk about a use case where you will see how easy it is to create a web application with AWS. All right, let's talk about what is AWS. AWS or Amazon web services is a secure cloud service platform. It is also pay as you go type billing model where there is no upfront or capital cost. We'll talk about how soon the service will be available. Well, the service will be available in a matter of seconds. With AWS, you can also do identity and access management that is authenticating and authorizing a user or a program on the fly. And almost all the services are available on demand and most of them are available instantaneously. And as we speak, Amazon offers 100 plus services. And this list is growing every new week. Now that would make you wonder how AWS became so successful. Of course, it's their customers. Let's talk about the list of well-known companies that has their IT environment in AWS. Adobe. Adobe uses AWS to provide multi-ter operating environments for its customers. By integrating its system with AWS cloud, Adobe can focus on deploying and operating its own software instead of trying to, you know, deploy and manage the infrastructure. Airbnb is another company. It's an community marketplace that allows property owners and travelers to connect each other for the purpose of renting unique vacation spaces around the world. And uh the Airbnb community users activities are conducted on the website and through iPhones and Android applications. Airbnb has a huge infrastructure in AWS and they're almost using all the services in AWS and are getting benefited from it. Another example would be Autodesk. Autodesk develops software for engineering, designing and entertainment industries. Using services like Amazon RDS or relational database service and Amazon S3 or Amazon simple storage service, Autodesk can focus on deploying or developing its machine learning tools instead of spending that time on managing the infrastructure. AOL or American online uses AWS and using AWS they have been able to close data centers and decommission about 14,000 in-house and colloccated servers and move mission critical workload to the cloud and extend its global reach and save millions of dollars on energy resources. Bit Defender is an internet security software firm and their portfolio of softwares include antivirus and anti-spyear products. Bit Defender uses EC2 and they're currently running few hundred instances that handle about 5 terabytes of data and they also use elastic load balancer to load balance the connection coming in to those instances across availability zones and they provide seamless global delivery of service. Because of that, the BMW group, it uses AWS for its new connected car application that collects sensor data from BMW 7 series cars to give drivers dynamically updated map information. Canons offers imaging products division benefits from faster deployment times, lower cost, and global reach by using AWS to deliver cloud-based services such as mobile print. The office imaging products division uses AWS such as Amazon S3 and Amazon RA 53, Amazon CloudFront and Amazon IM for their testing, development, and production services. Comcast, it's the world's largest cable company and the leading provider of internet service in the United States. Comcast uses AWS in a hybrid environment. Out of all the other cloud providers, Comcast chose AWS for its flexibility and scalable hybrid infrastructure. Docker is a company that's helping redefine the way developers build, ship, and run applications. This company focuses on making use of containers for this purpose and in AWS, the service called Amazon EC2 container service is helping them achieve it. The ESA or European Space Agency. Although much of ESA's work is done by satellites, some of the programs, data, storage, and computing infrastructure is built on Amazon Web Services. ESA chose AWS because of its economical pay as you go system as well as its quick startup time. The Guardian newspaper uses AWS and it uses a wide range of AWS services including Amazon Kinesis, Amazon Redshift that power an analytic dashboard which editors use to see how stories are trending in real time. Financial Times FT is one of the world's largest leading business news organization and they used Amazon Redshift to perform their analysis. A funny thing happened. Amazon Red Shift performed so quickly that some analysis thought it was malfunctioning. They were used to running queries overnight and they found that the results were indeed correct just as much faster. By using Amazon Red Shift, FD is supporting the same business functions with costs that are 80 percentage lower than what was before. General Electric GE is at the moment as we speak migrating more than 9,000 workloads including 300 desperate ERP systems to AWS while reducing its data center footprint from 34 to 4 over the next 3 years. Similarly, Harvard Medical School, HTC, IMDb, McDonald's, NAZA, Kelloggs and lot more are using the services Amazon provides and are getting benefited from it. And this huge success and customer portfolio is just the tip of the iceberg. And if we think why so many adapt AWS and if we let AWS answer that question, this is what AWS would say. People are adopting AWS because of the security and durability of the data and end-to-end privacy and encryption of the data and storage experience. We can also rely on AWS way of doing things by using the AWS tools and techniques and suggested best practices built upon the years of experience it has gained. Flexibility. There is a greater flexibility in AWS that allows us to select the OS language and database. Easy to use swiftness in deploying. We can host our applications quickly in AWS. Be it a new application or migrating an existing application into AWS. Scalability. The application can be easily scaled up or scaled down depending on the user requirement. Costsaving. We only pay for the compute power, storage, and other resources you use and that to without any long-term commitments. Now, let's talk about the different types of services that AWS provides. The services that we talk about fall in any of the following categories you see like you know compute storage database security customer engagement desktop and streaming machine learning developers tools stuff like that and if you do not see the service that you're looking for it's probably is because AWS is creating it as we speak now let's look at some of them that are very commonly used within compute services we have Amazon EC2 Amazon elastic beantock Amazon light sale and Amazon lambda Amazon EC2 provides compute capacity in the cloud. Now this capacity is secure and it is resizable based on the user's requirement. Now look at this. The requirement for the web traffic keeps changing and behind the scenes in the cloud EC2 can expand its environment to three instances and during no load it can shrink its environment to just one resource. Elastic beantock it helps us to scale and deploy web applications and it's made with a number of programming languages. Elastic beantock is also an easytouse service for deploying and scaling web applications and services deployed be it in Java.net net, PHP, NodeJS, Python, Ruby, Docker and lot other familiar services such as Apache, Passenger and IIS. We can simply upload our code and elastic beantock automatically handles the deployment from capacity provisioning to load balancing to autoscaling to application health monitoring and Amazon lights is a virtual private server which is easy to launch and easy to manage. Amazon lightsale is the easiest way to get started with AWS for developers who just need a virtual private server. Light includes everything you need to launch your project quickly on a virtual machine like SSD based storage, a virtual machine, tools for data transfer, DNS management and a static IP and that too for a very low and predictable price. AWS Lambda has taken cloud computing services to a whole new level. It allows us to pay only for the compute time. No need for provisioning and managing servers. And AWS Lambda is a compute service that lets us run code without provisioning or managing servers. Lambda executes your code only when needed and scales automatically from few requests per day to thousands per second. You pay only for the compute time you consume. There is no charge when your code is not running. Let's look at some storage services that Amazon provides like Amazon S3, Amazon Glacier, Amazon EBS, and Amazon Elastic File System. Amazon S3 is an object storage that can store and retrieve data from anywhere. Websites, mobile apps, IoT sensors, and so on can easily use Amazon S3 to store and retrive data. It's an object storage built to store and retrive any amount of data from anywhere. With its features like flexibility in managing data and the durability it provides and the security that it provides, Amazon simple storage service or S3 is a storage for the internet. and Glacier. Glacier is a cloud storage service that's used for archiving data and long-term backups. And this Glacier is an secure, durable, and extremely lowcost cloud storage service for data archiving and long-term backups. Amazon EBS, Amazon Elastic Block Store provides block store volumes for the instances of EC2. And this elastic block store is highly available and a reliable storage volume that can be attached to any running instance that is in the same availability zone. ABS volumes that are attached to the EC2 instances are exposed as storage volumes that persistent independently from the lifetime of the instance and Amazon elastic file system or EFS provides an elastic file storage which can be used with AWS cloud service and resources that are on premises and Amazon elastic file system it's an simple it's scalable it's an elastic file storage for use with Amazon cloud services and for on premises resources it's easy to use and offers offers a simple interface that allows you to create and configure file systems quickly and easily. Amazon file system is built to elastically scale on demand without disturbing the application growing and shrinking automatically as you add and remove files so your application have the storage they need and when they need it. Now let's talk about databases. The two major database flavors are Amazon RDS and Amazon Redshift. Amazon RDS it really eases the process involved in setting up operating and scaling a relational database in the cloud. Amazon RDS provides costefficient and resizable capacity while automating time consuming administrative tasks such as hardware provisioning, database setup, patching and backups. It sort of frees us from managing the hardware and sort of helps us to focus on the application. It's also cost effective and resizable and it's also optimized for memory performance and input and output operations. Not only that, it also automates most of the services like taking backups, you know, monitoring stuff like that. It automates most of those services. Amazon Redshift. Amazon Redshift is a data warehousing service that enables users to analyze the data using SQL and other business intelligent tools. Amazon Red Shift is an fast and fully managed data warehouse that makes it simple and cost-effective analyze all your data using standard SQL and your existing business intelligent tools. It also allows you to run complex analytic queries against pabyte of structured data using sophisticated query optimizations and most of the results they generally come back in seconds. All right, let's quickly talk about some more services that AWS offers. There are a lot more services that AWS provides, but we're going to look at some more services that are widely used. AWS application discovery services help enterprise customers plan migration projects by gathering information about their on- premises data centers. You know, planning a data center migration can involve thousands of workloads. They are often deeply interdependent. Server utilization data and dependency mapping are important early first step in migration process. And this AWS application discovery service collects and presents configuration, usage, and behavior data from your servers to help you better understand your workloads. Route 53, it's a network and content delivery service. It's an highly available and scalable cloud domain name system or DNS service. And Amazon Route 53 is fully compliant with IPv6 as well. Elastic load balancing, it's also a network and content delivery service. Elastic load balancing automatically distributes incoming application traffic across multiple targets such as Amazon EC2 instance containers and IP addresses. It can handle the varying load of your application traffic in a single availability zones and also across availability zones. AWS autoscaling it monitors your application and automatically adjusts the capacity to maintain steady and predictable performance at a lowest possible cost. Using AWS autoscaling, it's easy to set up application scaling for multiple resources across multiple services in minutes. Autoscaling can be applied to web services and also for DB services. AWS identity and access management. It enables you to manage access to AWS services and resources securely using IM. You can create and manage AWS users and groups and use permissions to allow and deny their access to AWS resources. And moreover, it's a free service. Now let's talk about the future of AWS. Well, let me tell you something. Cloud is here to stay. Here's what in store for AWS in the future. As years pass by, we're going to have variety of cloud applications born like IoT, artificial intelligence, business intelligence, serverless computing and so on. Cloud will also expand into other markets like healthcare, banking, space, automated cars and so on. As I was mentioning some time back, lot or greater focus will be given to artificial intelligence and eventually because of the flexibility and advantage that cloud provides, we're going to see a lot of companies moving into the cloud. All right, let's now talk about how easy it is to deploy an web application in the cloud. So the scenario here is that our users like a product and we need to have a mechanism to receive input from them about their likes and dislikes and uh you know give them the appropriate product as per their need. All right. Though the setup and the environment it sort of looks complicated. We don't have to worry because AWS has tools and technologies which can help us to achieve it. Now we're going to use services like route 53 services like cloudatch EC2 S3 and lot more. And all these put together are going to give an application that's fully functionable and uh an application that's going to receive the information uh like using the services like route 53, cloudatch, EC2 and S3. We're going to create an application and that's going to meet our need. So back to our original requirement, all I want is to deploy a web application for a product that keeps our users updated about the happenings and the new comingings in the market. And to fulfill this requirement, here is all the services we would need. EC2 here is used for provisioning the computational power needed for this application and EC2 has a vast variety of family and types that we can pick from for the types of workloads and also for the intents of the workloads. We're also going to use S3 for storage and S3 provides any additional storage requirement for the resources or any additional storage requirement for the web applications. And we're also going to use Cloudatch for monitoring the environment and cloudatch monitors the application and the environment and it uh provides trigger for scaling in and scaling out the infrastructure. And we're also going to use route 53 for DNS and route 53 helps us to register the domain name for our web application. And with all the tools and technologies together, all of them put together, we're going to make an application, a perfect application that caters our need. All right. So, I'm going to use Elastic Beantock for this project. And the name of the application is going to be, as you see, GSG signup. And the environment name is GSG signup environment one. Let me also pick a name. Let me see if this name is available. Yes, that's available. That's the domain name. So, let me pick that. And the application that I have is going to run on NodeJS. So let me pick that platform and launch. Now as you see elastic beanto this is going to launch an instance. It's going to launch u the monitoring setup or the monitoring environment. It's going to create a load balancer as well and it's going to take care of all the security features needed for this application. All right, look at that. I was able to go to that URL which is what we gave and it's now having an default page shown up meaning all the dependencies for the software is installed and it's just waiting for me to upload the code or in specific the page required. So let's do that. Let me upload the code. I already have the code saved here. That's my code. And that's going to take some time. All right, it has done its thing. And now if I go to the same URL, look at that. I'm being thrown an advertisement page. All right, so if I sign up with my name, email, and stuff like that. you know, it's going to receive the information and it's going to send an email to the owner saying that somebody had subscribed to your service. That's the default feature of this app. Look at that email to the owner saying that somebody had subscribed to your app and this is their email address, stuff like that. Not only that, it's also going to create an entry in the database. And Dynamo DB is the service that this application uses to store data. There's my Dynamob. And if I go to tables right and go to items, I'm going to see that a user with name Samuel and email address so and so has said okay or has shown interest in the preview of my site or product. So this is where or this is how I collect those information. Right. And some more things about the infrastructure itself is it is running behind an load balancer. Look at that. It had created a load balancer. It had also created an autoscaling group. Now that's the feature of elastic load balancer that we have chosen. It has created an autoscaling group. And now let's put this URL. You see this it's it's not a fancy URL, right? It's an Amazon given URL, a dynamic URL. So let's put this URL behind our DNS. Let's do that. So go to services, go to route 53, go to hosted zone, and there we can find the DNS name. Right? So that's a DNS name. All right. All right, let's create an entry and map that URL to our load balancer. Right, and create. Now, technically, if I go to this URL, it should take me to that application. All right, look at that. I went to my custom URL and now that's pointed to my application. Previously my application was having a random URL and now it's having a custom URL. So what did we learn? We started the session with what is AWS. We looked at features and tools, technologies, products that AWS provides and we also looked at how AWS became very successful. Again we looked into the benefits and features of AWS in depth. And we also looked at some of the services that AWS provides in random. And then we picked particular services and we talked about them like EC2 elastic beantock light sale lambda storage stuff like that. Then we also looked at the future of AWS what AWS holds in the store for us. We looked at that and then finally we looked at a lab in which we created an application using elastic beanto and all that we had to do was a couple of clicks and boom an application was there available that was connected to um the database and that was connected to the simple notification system that was connected to cloudatch that was connected to storage stuff like that what is Azure what's the big cloud service provider all about so Azure is a cloud computing platform provided by Microsoft Now it's basically an online portal through which you can access and manage resources and services. Now resources and services are nothing but you know you can store your data and you can transform the data using services that Microsoft provides. Again all you need is the internet and being able to connect to the Azure portal. Then you get access to all of the resources and their services. In case you want to know more about how it's different from its rival which is AWS, I suggest you click on the top right corner and watch the AWS versus Azure video so that you can clearly tell how both these cloud service providers are different from each other. Now, here are some things that you need to know about Azure. It was launched in February 1st, 2010, which is significantly later than when AWS was launched. It's free to start and has a pay-per-use model, which means like I said before, you need to pay for the services you use through Azure. And one of the most important selling points is that 80% of Fortune 500 companies use Azure services, which means that most of the bigger companies of the world actually recommend using Azure. And then Azure supports a wide variety of programming languages. The C, NodeJS, Java, and so much more. Another very important selling point of Azure is the amount of data centers it has across the world. Now it's important for a cloud service provider to have many data centers around the world because it means that they can provide their services to a wider audience. Now Azure has 42 which is more than any cloud service provider has at the moment. It expects to have 12 more in a period of time which brings its total number of regions it covers to 54. Now let's talk about Azure services. Now, Azure services have 18 categories and more than 200 services. So, we clearly can't go through all of them. It has services that cover compute, AI and machine learning, integration, management tools, identity, DevOps, web, and so much more. You're going to have a hard time trying to find a domain that Azure doesn't cover. And if it doesn't cover it now, you can be certain they're working on it as we speak. So, first, let's start with the compute services. First, virtual machine. With this service, what you're getting to do is to create a virtual machine of Linux or Windows operating system. It's easily configurable. You can add RAM, you can decrease RAM, you can add storage, remove it. All of it is possible in a matter of seconds. Now, let's talk about the second service cloud service. Now, with this you can create a application within the cloud and all of the work after you deploy it. deploying the application that is is taken care of by Azure which includes you know provisioning the application load balancing ensuring that the application is in good health and all of the other things are handled by Azure. Next up let's talk about service fabric. Now with service fabric the process of developing a micros service is greatly simplified. So you might be wondering what exactly is a micros service? Now a micros service is basically an application that consists of smaller applications coupled together. Next up, functions. Now, with functions, you can create applications in any programming language that you want. Another very important part is that you don't have to worry about any hardware components. You don't have to worry what RAM you require or how much storage you require. All of that is taken care of by Azure. All you need is to provide the code to Azure and it'll execute it and you don't have to worry about anything else. Now, let's talk about some networking services. First up we have Azure CDN or the content delivery network. Now the Azure CDN service is basically for delivering web content to users. Now this content is of high bandwidth and can be transferred or can be delivered to any person across the world. Now these are actually a network of servers that are placed in strategic positions across the world so that the customers can obtain this data as fast as possible. Next up we have express route. Now with this you can actually connect your on-premise network onto the Microsoft cloud or any of the services that you want through a private connection. So the only communication that happens is between your on-premise network and the service that you want. Then you have virtual network. Now with virtual network you can have any of the Azure services communicate with each other in a secure manner in a private manner. Next we have Azure DNS. So Azure DNS is a hosting service which allows you to host their DNS or domain name system domains in Azure. So you can host your application using Azure DNS. Now for the storage services. First up we have disk storage. With this storage you're given a cost-effective option of choosing HDD or solidstate drives to go along with your virtual machines based on your requirements. Then you have blob storage. Now this is actually optimized to ensure that they can store massive amounts of unstructured data which can include text data or even binary data. Next you have file storage which is a managed file storage and can be accessible via the SMB protocol or the server message block protocol. And finally you have Q storage. Now with Q storage you can provide durable message queuing for an extremely large workload. And the most important part is that this can be accessed from anywhere in the world. Now let's talk about how Azour can be used. Firstly for application development. It could be any application mostly web applications. Then you can test the application see how well it works. You can host the application on the internet. You can create virtual machines. Like I mentioned before with the service you can create these virtual machines of any size or RAM that you want. You can integrate and sync features. You can collect and store metrices. For example, how the data works, how the current data is, how you can improve upon it. All of that is possible with these services. And you have virtual hard drives which is an extension of the virtual machines where these services are able to provide you a large amount of storage where data can be stored. Talk about Azure in great length and breadth. And if you're looking for a video that talks and walks you through all the services in Azure, then this could be one of the best video you could find in the internet. And without any further delay, let's get started. Everybody likes stories it. So let's get started with a story. In a city not so far away, a CEO had plans to expand his company globally and called one of his IT personnel for an IT opinion. And this guy has been in the company for a long time and is very seasoned with the company's infra and he nicely answered the questions with what he foresaw and he said I have a good news and a bad news for us to go global. And he starts with the good news. He said, "Sir, we're well on our way to become one of the world's largest shipping company." And the bad news is, however, our data centers have almost run out of space and setting up new ones around the world would be too expensive and very timeconuming. Now, the IT personnel, let's call him Mike, now he explains the situation from how he saw it. But the CEO had done some homework about how he was going to do it and he answered Mike saying, "Don't worry about that, Mike. I've come up with a solution for a problem and it's called Microsoft Azure." Well, Mike is an hardworking and honest IT professional working for that company, but he did not spend time on learning the latest technologies. And he asked this question very honestly. Oh, how does it solve a problem? And the CEO begins to explain Azure to Mike and he starts with what is cloud computing and then he goes on and talks about Azure and the services offered by Azure and why Azure is better than the other cloud providers and what are the great companies that uses Azure and how they got benefited out of it and then he winds it all up with the use cases of Azure. So he begins his explanation saying Microsoft Azure is known as the cloud service provider and it works on the basis of cloud computing. Now Microsoft Azure is formerly known as Windows Azure and it's uh Microsoft's public cloud computing platform. It also provides a range of cloud services including some of them are compute analytics storage and networking. We can always pick and choose from these services to develop and scale our applications or even plan on running existing applications in the public cloud. Microsoft Azure is both a platform as a service and infrastructure as a service. Let's now fit their conversation out and let's talk about what is cloud computing Azure services offered by Azure. How is Azure leading when compared to other cloud service providers and what are the companies that are using Azure? Let's talk about that. In simple terms, cloud computing is being able to access compute services like servers, storage, database, networking, software analytics, intelligence and lot more over the internet which is the cloud. with the uh flexibility of the resources that we use like anytime I want a resource I can use one and it becomes available immediately and anytime if I want to retire an resource I can simply retire a resource and not pay for it and we also typically pay only for the services that we use and this helps greatly with our operating cost to run our infrastructure more efficiently and scale our environment up or down depending on the business needs and changes. And all the servers and stoages and databases and networking all that are accessed through the network of remote systems or remote computers hosted in the internet typically in the provider's data center which is Azure in this case. Now we don't use any physical server or an onremises server here. Well, we still use physical servers and VMs, you know, hosted on a hardware or a physical server, but they're all in the provider environment and none of them sit on premises or in our data center. We only access them remotely. It looks and feels the same except for the fact that they are in a remote location. we access them remotely, do all the work remotely and when we're done we can shut it down and not pay for them. So some of the use cases some of the use cases of cloud computing are creating applications and services. The other use cases are storing or using cloud for storage alone. If there is one thing that ever grows in an organization is the storage. Every new day there is a new storage requirement and it's very dynamic. It's very hard to predict and if we go out and buy a big storage capacity up front until we use the storage capacity fully the empty stoages you know we're wasting money on them. So instead I can go for a storage which scales dynamically that's in the cloud. Put storage or put data in the cloud and pay only for what you're storing. And for the next month if you have deleted or flushed out some files or data pay less for it. So it's a very dynamic storage in the cloud and a lot of companies are getting benefited from storing data in the cloud because of its u dynamic in nature and the cost that comes along with it the cheap cost that comes along with it and also they give a lot of the providers like Azure they give a data replication for free they promise an SLA along with the data we store in the cloud so there's an SLA attached to it and they also O provide data recoveries as well. If in case something goes wrong with the physical disk where our data is stored, Azure automatically makes our data available from the redundant or other places where it had stored our data because of the SLA they wanted to keep. The other use case for Azure is hosting websites and running blogs using the compute service. Be it storing music and letting your users stream the music. Azure is a good place to store music and stream the music with the benefit of CDN content delivery network which allows us to stream video or audio files with great speed. You know with that with Azure our audio or video application works seamlessly because they are provided to the client with very low latency and that improves the customer experience for our application. Azure comput service is a good place for delivering software on demand. There are a lot of softwares embedded softwares that we can buy using Azure and everything on a pay as you go service model. So anytime we need a software, we can go out and immediately buy the software for the next 1 hour or 2 hour let's say and use them and then return it back. We're not bound to any yearly licensing cost by that. Azure computing services has analytic available for us with which we can analyze get a good visualization of what's going on in a network be logs be the performance be the metrics you know instead of looking at logs and searching logs and trying to do manual things over the heaps and heaps of logs that we have saved Azure Analytics Services helps us to get a good visual of What's going on in the network? Where have we dropped? Where have we increased or what's causing what's the major driver? What is the top 10 errors that we get in the server in the application? Stuff like that. Those can be easily gathered from the Azure analytic services. Now cloud is really a very cool term for the internet. A good analogy would be looking back. Anytime we look at a diagram when we do not know how things are transferred, we simply draw a cloud. Right? For example, a mail gets sent from a person in one country to a person in the other country. A lot of things happening in between from the time you hit the send button and the time the other person hits the read button. Right? And we the simple and the easiest way of putting it in a picture is simply draw a cloud and on the one end one person will be sending the email and on the other end the other person will be reading the email. So a cloud is a really cool term for the internet. Now that's some basics about cloud computing. Now that we've understood about cloud computing in general, let's talk about Microsoft Azure as a cloud service. Now, Microsoft Azure is a set of cloud services to build, manage, and deploy applications on a network with the help of Microsoft Azure's frameworks. Now, Microsoft Azure is a computing service created by Microsoft basically for building, testing, deploying, and managing applications and services through a global network of Microsoft managed data centers. Now, Microsoft Azure provides SAS which is software as a service and PAS which is platform as a service and IAS infrastructure as a service and they support many different programming languages tools and framework and those tools and framework include both Microsoft specific and third party software. Now let me pick and talk about a specific service for example management. Azure automation provides a way for us to automate the manual long running and frequently repeated task that are commonly performed tasks both in cloud and enterprise environment. It saves us a lot of time and increases the reliability and it kind of gives a good administrative control and even schedules the task automatically to be performed on a regular basis. To give you a quick history of Microsoft Azure, it was launched on 1st February 2010 and it was awarded or it was called an industry leader for infrastructure and platform as a service by Gartner. Now Gartner is the world's leading research and advisory company. This Microsoft Azure supports a number of programming languages like C, Java and Python. All these cool services we get to use and pay only for how much we use. For example, if we use for an hour, we only get to pay for an hour. Even the costliest system available. And if we use them for an hour, we only pay for that particular hour. And then we're done. No more billing on the resource that we have used. Microsoft Azure has spread itself more than 50 regions around the world. So it's quite easy for us to pick a region and you know start provisioning and running our applications probably from day one because the infrastructure and the tools and technologies needed to run our application are already available. All that we have to do is commit the code in that particular region or build an application or launch it in that particular region and they become live starting day one. Now because we have 50 regions around the world, we can very carefully design our environment to provide low latency services to our customers. All right? Instead of in traditional data center let's say you know customers will have to or their request will have to travel all the way around the globe to reach a data center which lives in the other side of the planet and this adds more latency to it and it is really not feasible to build a data center uh near each customer location because of the cost involved but with Azure it's possible. Azure already has data centers around the world and all that we have to do is just pick a data center, build an environment there. They're available starting day one. Number one, and also the cost is considerably saved because we are using a public cloud instead of an physical infrastructure to serve those customers from a very local location. And the services that Azure is offering is ever increasing. As of now, as we speak, we have like 200 plus services offered and uh they span through different domain or different platform or different technologies available within the Azure console portal. Now, we're going to talk about that later in this section. So, hold your breath till we talk about it. But for now, just know that we have like 200 plus services offered by Azure. Let's now talk about different services in Azure. Starting with artificial intelligence plus machine learning where we have a lot of tools and technologies. So the wide variety of services available on Azure includes artificial intelligence plus machine learning plus analytic services to get an or to give us a good visual of how the data or how the application is performing or the type of the category of data stored and to read from the logs. and variety of compute services, different VMs with different size and different operating systems, different containers available, different type of databases available, a lot of developer tools that are available for us and identity service to manage our users in the Azure cloud and those users can be integrated or federated with let's say Google, Facebook, you know, LinkedIn. So there are some external federation services they can be used to integrate with our identity system IOT's IoT services IoT tools and technologies available and management tools to manage the users you know creating identity is one and then managing them on top of it is a totally different thing and we have tools technologies to manage the uh users cool services for data migration data migration is now made simple tools and technologies available for mobile application uh development and I can plan my own network in the cloud with the networking services I can implement my own security both Azure provided and third party security services on Azure cloud that's now possible and lot of storage options available in the cloud so these are just a glimpse of the big list of services available in Azure cloud So that was a glimpse of what's available in the cloud. Let's talk about the services in a specific. Let's take compute for example. You know whenever we're building a new application or deploying existing ones. The Azure compute service provides the infrastructure we need to run and maintain our application. We can easily tap in the capacity that Azure cloud service has and we can scale our compute requirement on demand. We can also containerize our application. We have the option of choosing Windows or Linux v machine and take the advantage of the flexible options Azure provides for us to migrate our VMs to Azure and lot more. And these compute services also include a full-fledged identity solution meaning integration with active directory in the cloud or an on premises and lot more. Let's look at some of the services that this compute domain provides. Some of the services the compute domain provides are virtual machines. And this Azure virtual machines gives us the ability to develop and manage a virtual computer environment or a virtualized environment inside Azure's cloud environment that do in a virtual private network. Now we will talk about virtual private network at a later point but as of now just uh know that there are a lot of services available in Azure compute service that we can get benefited from. We can always choose from a very wide range of uh compute options. For example, you know we have an option to choose the operating system. We have the option to choose whether the system should be in on premises or in the cloud or do we want to maintain the environment both in on premises and in the cloud. we have the option of choosing the operating system whether we want to use our own operating system with some software attached uh to it or do we want to go and buy the operating system from the cloud from Azure marketplace and these are just a few of the options available for us when we want to buy the compute environment and these compute environments are easily scalable meaning we can easily scale our VM instances from one instance to thousands thousands of virtual machines in a matter of minutes or simply put in a couple of button clicks and all these services are available on a pay for what we use model. Meaning there is no upfront cost. We use the service and then pay for the services that we have used. There's no literal or long-term commitment when it comes to using virtual machines in the cloud. And these most of the services are built on a pay-per-inut billing basis. All right. And at no point because of the pay-per- minute billing model, at no point we will be overpaying for any of the services. That's that's attractive, isn't it? Now, let's talk about batch service. Now, batch service is always independent. Regardless of whether you choose Windows or Linux, it's going to run fairly well. And with batch service we can take advantage of the uh environment's unique features and not only that in short the batch service helps us to manage the whole batch environment and also it helps to schedule the jobs. Now this Azure batch service is actually runs on a large scale parallel and high performance computing. Because of that batch jobs are highly efficient in Azure. And when we run batch services, this Azure batch creates a pool of computer nodes and uh installs the needed applications that we want to run and then it schedules jobs to those individual nodes in those pools. As a customer, there is no need for us to install a cluster or there is no need for us to install a software that actually schedules the jobs or even to manage or even to scale those infrastructure or the uh software because everything is managed by Azure. And this batch service is a platform as a service. There is no additional charge for using this batch service except for I mean the only charges that we'll be paying is for the virtual machines that this service uses and uh the storage that we will be using of course and uh the networking services that we will be using for this batch service. Let's summarize this batch service. We have a choice of operating system that we can pick and use and it scales by itself. Now the alternative for the batch would be cues but in cues we'll have to pre-provision and pay for the infrastructure even if we're not using it but with a batch we only pay for what we use and this batch service helps us to manage uh the application manage the scheduleuling as a whole as if they are just one thing as next thing in compute domain let's talk about this fabric service now this fabric service is actually a distributed system platform that helps us to package, deploy and manage a scalable and a very reliable micros service and containers. And what does it help? This Azure fabric service helps us or it helps the developers and administrators so they can avoid the complex infrastructure problems and they can focus only on implementing workloads or taking care of their development taking care of their application instead of spending time on infrastructure. So what's service fabric? service fabric. It provides runtime capabilities and uh life cycle management to applications that are composed of microservices. No infrastructure management at all. And with service fabric we can easily scale the application to tens or hundreds or even to thousands of machines. Here machines represent containers. As next thing in compute domain, let's talk about virtual machine scale set. Now this virtual machine scale set it lets us to create a group of identical load balanced VMs. I just want to mention it again. It helps us to manage a group identical and load balanced VMs. The number of instances or the number of VM instances in an in a scale set can increase or decrease in response to uh the demand or in response to a schedule that we define. you know the resources needed on a Monday morning is not the same as that would be required on a Saturday or a Sunday morning. All right. And even within the day the resources that would be needed in the beginning of the business hour is not the resources that would be needed at noon or you know after 8 or 9 in the evening. So the demands could actually vary in the environment and the scale set helps us to take care of the varying demand or take care of the uh different infrastructure requirement at a different schedule throughout the day throughout the week throughout the month or could be throughout the year as well. The scale set also allows us to provide high availability to our applications and it helps us to uh centrally manage configure and update a large number of VMs as if they they are just one thing. Now you might ask well virtual machines are enough why would we need a virtual machine scale set? Just like I said this virtual machine scale set helps us uh with uh a greater redundancy and improved performance for our applications and those applications can be accessed through a load balancer that actually distributes uh the requests to the application instances. So in a nutshell this virtual machine scale set it helps us to create a large number of identical virtual machines. number one. And with scale set, we can increase or decrease the virtual machines. With virtual machine scale set, we can centrally manage and configure and update a big group of VMs. And it's a great use case when it comes to big data or container workloads. As next thing in compute domain, uh let's talk about cloud services. Now, this Azure cloud service is actually a platform as a service and it's very friendly. In fact, it is designed for applications that support scalability or an application that requires scalability or reliability and and on top of it, you want them to be very inexpensive to operate. So, Azure cloud service provides all these. So, where would this cloud service run? Well, it runs on a VM, but it's a platform as a service. VMs are infrastructure as a service. And when we run applications on VM through cloud service, it becomes platform as a service. So here is how you got to be thinking with infrastructure as a service like VMs. We first create and configure the environment and then we run applications on top of it. Let's look at the responsibility. The responsibility for us in VM is that we manage everything end to end like uh you know deploying new patches, picking the versions of the operating system and making sure they are uh intact and all that stuff. It's all managed by us. But on the contrary with platform as a service it's I mean it's as if the environment is already ready. All that you have to do is deploy your application in it and manage the platform. I mean manage the platform not as an administrator because all the administration is taken care by Azure like uh you know deploying new versions of the operating system. It's all handled by the Azure. So we deploy the application and we manage the application. That's it. infrastructure management is handled by Azure. So what does cloud service provide? This cloud service provides a platform uh where we can uh write the uh application code and we don't have to worry about hardware. Simply hand over the code and cloud service takes care of it. So no worry on the hardware at all. So responsibilities like patching, what do we do if something uh crashes, how do I update the infrastructure, how do I uh manage uh the maintenance or the downtime in the underlying infrastructure. All that is handled by Azure. It also provides an testing environment for us. You know, we can simply run the code, test it before it's actually released to the production. I want to expand a bit on these testing applications. So this Azure cloud service it actually gives us an staging environment for testing a new release without it affecting the existing release which actually reduces the customer downtime. So we can run the application, test it, and anytime that's ready for production, all that's needed for us to do to move it to production is simply to swap the staging environment into the production environment and the old production environment will now become the new staging environment where we can uh add more to it and then swap it back at a later point. So it it kind of gives us an swappable environment for testing our applications and not only that it gives us health monitoring alerts. It helps us to monitor the health and availability of our application. uh that is a dashboard we can benefit from uh when we use Azure cloud services and that shows the key statistics all in one place and we can also set up realtime alerts to warn when a service availability or a certain metrics that we are concerned about degrades as next thing in compute domain let's talk about functions now functions are serverless computing many time if you heard about Azure being serverless a lot of time they are referenced refing or the person who's talking to you is referencing to serverless uh computing or Azure functions which is a serverless computing service hosted on Microsoft Azure. The main motive of u function is to accelerate and simplify application development. Functions helps us to run code on demand without we need to pre-provision or manage any Azure infrastructure. So, Azure functions are script or a piece of code that gets run in response to an event that you want to handle. So, in short, we can just write a code that you need for a problem at hand without actually worrying about the whole application or the infrastructure that will be running uh that code. And the best of all the best is when we use functions, we only pay for the time that our code runs. So what does functions provide or what does Azure functions provide? Azure functions allow users to build applications using serverless uh simple functions with a programming language of our choice. So the current programming languages that are supported is C, F, NodeJS, Java and PHP. So here we really don't have to worry about provisioning or uh maintaining servers. If a code requires more resource, yes, Azure functions handles or it provides the additional resources needed by the code. And the best part is we only pay for the amount of time the functions are running. Not the resources but the amount of time the function is running. As next thing and moving to the new domain, let's talk about the container domain in Azure. Now the container domain or the container service, it allows us to quickly deploy a production ready Kubernetes or a Docker swarm cluster. Now what's a container? A container is a standard unit of software that packages of code and all its dependencies. So the applications run quickly and reliably from one computing environment to another. It could be testing uh to staging to developing development environment to staging to production or from one production to another production or on premises uh to cloud or one cloud to another cloud vice versa. Now imagine we had an option not to worry about the VM and just focus on the application. Well, that's exactly what containers helps us achieve. So these container instances enable us to focus on applications and not worrying about managing VMs or not worrying about the learning the new tools required to manage the VMs or even the deployment and our applications that we create they run in a container and running in a container is what helps us to achieve all these not being able to manage or not needing to manage the virtual machines. So these containers uh they can be deployed into the cloud using a single command if you're using a command line interface and a couple of button clicks if we are using the Azure portal and these containers are kept uh lightweight but they are equally secure as virtual machines. Let's talk about container services as next thing. uh the container service or u sometimes called as Azure Kubernetes service it helps us to manage the containers container is one thing and a service that's used to manage the container is another thing now this Kubernetes service or ACS it helps us to manage the containers so let's expand on this a bit so this Azure container service or ACS it it actually provides a way uh to simplify the creation configuration and management of a cluster of virtual machines that are preconfigured to run containerized applications on top of them. Now deploying them deploying these containers might take like 15 to 20 minutes or deploying the virtual machines that run containers in it might take 15 to 20 minutes and once they are provisioned we can actually manage them by using simple SSH tunnel into them. And this ACS when it runs application it runs applications from docker images. What does that mean? Docker images makes sure that the applications the container runs are fully portable. Images are portable and ACS also helps us to orchestrate the container environment. Not only that, it also helps us to ensure that these applications that we run in containers can be scaled to thousands or even tens of thousands of containers. So in a nutshell, managing an existing application into a container and running it using AKS or ACS is really easy or that's what it is all about to make the application management or migration easy. Now managing the containerbased architecture and we discussed that containers could be tens or even tens of thousands of containers. So managing them is made simple using this container services and even training of model using a large data set in a complex and resource intensive uh environment. This AKS helps us to simplify that uh environment. All right. As next thing in container domain, let's talk about container registry. We spoke about registry a little bit when we spoke about Docker images. So container registry is a single place where we can store our images which are docker images when we use when we use uh containers it's it's docker images that we use for our image purposes. So these container images are a central registry that can be used to ease container development by easing the storage and management of container images. So there we can store all kind of images like u docker swarm or the images used in docker swarm are in kubernetes. Everything can be stored in container registry in Azure. Now anytime we store a container image it provides us an option for geo replication. What that means is that we can efficiently manage a single registry replicated across multiple regions. Now this georrelication it actually enables us to manage global deployments assuming we are having an environment that requires a global deployment. So it helps us to manage global deployments as one entity because we are georrelicating. We would be updating we would be editing one image and that image gets replicated throughout the global uh replication centers we would have set up and so just one editing would have actually edited the global images and those global images would have provisioned the global application. So one edit replication and then provisioning of the applications globalwide. And this replication also helps us to helps us network latency because you know anytime an application needs to deploy it does not have to rely on a single source which which can be reached only through high latency network. Because we have global replications around the world. Anytime the application wants to check back, it would check back uh the application which is in a very nearby location for the application itself. Global replication means that we are managing it as a single entity that's being replicated across the multiple regions in the globe. As next thing in a learning, let's talk about um Azure databases. Now this Azure databases are uh rational. In fact, they have uh many flavors in them. Uh we're going to look at uh different u flavors. No, SQL NoSQL cache type of database that Azure offers. So, we're going to learn one at a time or we're going to learn one by one. So, this Azure SQL database is a relational database. In fact, it's a relational database as a service. It's managed by Azure. We don't get to do a lot of management in it. So it's a relational database as a service uh based on Microsoft uh SQL server database engine and this database is a high performance database it is very reliable and uh it's very secure as well and this high reliability high performance and for this high security really don't have to do anything it comes along with it and uh it's managed by Azure and there are two things that I definitely need to mention about Azure SQL database that is it's an intelligent service. Number one, it's fully managed by Azure and it also has this one good thing which is it has built-in intelligence that learns app patterns and adapts to maximize performance and reliability and data protection of the application. That's something that's not found in uh many of the other cloud providers that I'm aware of. So, I thought I'll mention it. So it uses built-in intelligence to learn about um the user's database patterns and helps improve performance and protection and migration or importing data is very easy when it comes to Azure SQL database. So it can be readily or immediately used for analytic reporting and uh intelligent applications in Azure. As next thing let's talk about Azure Cosmod. Now, Azure Cosmodb is a database service that is for NoSQL type and uh it's it's created to provide low latency and uh an application that scales dynamically or that scales rapidly. Now, this Azure Cosmodb is an a globally distributed service and it's a multimodel database. This can be provisioned in a click of a button. That's all we got to do if we need to provision an Azure Cosmod in the Azure. It helps with scaling the database. Now we can elastically and independently scale throughput and storage across this database and in any of the Azure geographic regions. It provides a good throughput. It provides good latency. It provides good availability and um it provides or uh Azure promises a a comprehensive SLA that uh no other database can offer. That's the best part about Cosmo DB. So this Cosmod was built with a global distribution in mind and it's built uh with a horizontal scale in mind and all this we can use by only paying for what we have used and remember the difference between Azure Cosmodb and SQL database is that Azure Cosmod supports NoSQL whereas SQL doesn't all right few other things about Azure Cosmod is it allows users to use key value graph column family and document data. It also gives users a number of API options like SQL, JavaScript, MongoDB and and few others that you might want to check in the document at at the time of reading. And the best part here is that all that we mentioned we get to use only by paying for the amount of storage and throughput that are required and the storage and the throughput can be elastically scaled based on the requirement of that R. All right, let's talk about um Reddis cache. Discussion about Azure database won't be complete without we talking about Reddis cache. Now Reddis cache is a a secure data cache. It's also called it's also sometimes called as messaging broker that provides high throughput and low latency access to data for the applications. Now Reddis cache is based on an a popular open-source caching product which is Reddis sometimes called as Reddis cache. Now what's the use case? It's typically used to cache to improve the performance and scalability of a system that rely heavily on back-end data stores. Now performance when we use ZIS cache is improved by temporarily copying the frequently accessed data to a fast storage located very close to the application. Now with Reddis cache this fast storage is located in memory with Reddis cache instead of being loaded from the actual disk in the database itself. Now this radius cache can also be used as an in-memory data structure store. Not only that, it can be used as an distributed non- relational database and a message broker. So there are variety of uh use cases for this radius cache. And by using radius cache, the application performance is improved by taking advantage of the low latency and the high throughput performance that this radius cache engine provides. So to summarize this radius cache when we use radis cache data is stored in the memory instead of the disk to ensure that there is high throughput and low latency when the application needs to read the data. It provides various levels of scaling without any downtime or interference. Now this radius cache is actually backed by radius server and it supports u a string hashes linked list and various other data structures. Now let's talk about security and identity services. Now identity management in specific is a process of authenticating first and then authorizing using security principles and not only that identity management involves controlling information about those principal identities. You might ask now what's an principal identity? Now identity or principal identity are services, applications, users, groups and a lot more. The specialtity about uh this identity management is that it not only helps authenticate and authorize principles in cloud, it also helps authenticate and authorize principles or resources on premises especially when you run an hybrid cloud environment. So all these services and features that this identity management helps us to get additional level of validation like identity management can provide multiffactor authentication. It can provide access policies based on condition permit or deny based on condition. It can also monitor suspicious activity and not only that it can also report it. It can also help generate alerts for potential security issues and in a way to mitigate it can send us an alert so we can get involved and prevent and a security accident from happening. So let's talk more about identity management. So some of the services under security and identity management are Azure security center. Now this Azure security center provides security management and threat protection across the workloads in both cloud and in the hybrid environment. It helps control user access and application control to stop any malicious activity if present. It helps us to find and fix vulnerabilities before they can be even exploited. It integrates very well with analytic methods that helps us to identify or it gives us the intelligent to identify or detect attacks and prevent them before it can actually happen. And it also works seamlessly with hybrid environment. So you don't have to have one policy for on premises and one policy for the cloud. It's now a unified service both for on premises and the cloud. The next service in security and identity would be key. Now a key wault is a service or a feature that help safeguard the cryptographic keys and any other secrets used by the cloud applications and the services. In other words, this Azure key wault is a tool for securely storing and accessing the secrets of the environment. I mean the secret keys. Now a secret is anything that you really want to have a very tight control access like the certificates like the passwords stuff like that. Now if I tell you what keywalt actually solves that would actually explain what keywalt is. Now keywalt is used in secrets management. It helped in securely storing the tokens, the passwords, the certificates. It helps in key management. You know it really helps in creating and controlling the encryption keys that we would use to encrypt data. It helps in certificate management. Talking about certification management, it helps us to easily provision, manage and deploy public and private SSL TLS certificates in Azure and lot more. So in a nutshell, this key wall, it provides users the ability to provision new walls and keys in just a matter of minutes. All that in a single command or all that in a couple of button clicks. It also helps users to centrally manage their keys, secrets and policies. Next in the list, let's talk about Azure Active Directory. Now, Azure Active Directory, it helps us to create intelligent driven access policies to limit resource usage and manage user identities. What what does that mean? Now, this Azure Active Directory is a cloudbased active directory and identity management service. Now, Azure Active Directory combines, you know, it's actually a combination of the core directory services plus application access management plus identity protection. And one good thing about this Azure, in fact, there are a lot of good things, but especially when you're running hybrid environments, you might wonder well how this Azure Active Directory is going to behave. Now, this Azure Active Directory is built to work on on premises and cloud environment as well. Not only that, it also works seamlessly with mobile applications as well. So in a nutshell, this Azure Active Directory, it acts as an central point of identity and access management for our cloud environment. It also provides good security solutions that protect against unauthorized access of our app and the data. Now that we've discussed about security and identity, let's talk about the management tools that Azure has to offer. Azure provides built-in management and account governance tools that helps administrators and developers that helps them to keep their resources secure and very compliant and again it helps both in on premises and in the cloud environment. And these management tools help us to monitor the infrastructure, monitor the applications. It also helps in provisioning and configuring resources. It also helps in updating apps. It helps in analyzing threats, taking backup of the resources, build uh disaster recoveries. It also helps in applying policies and conditions to automate our environment. we use u Azure management tools and it's also used in cost control methods. So this Azure management plays a wide role across the Azure services and in the management tools first comes the Azure advisor. Now this Azure advisor it acts as a guide to educate us about Azure best practices. It throws recommendations that we can select on the basis of the category of service and it also provides the impact it can have or the impact that would happen in our environment if we follow the recommendations given and recommendations are uh first one is the recommendations are kind of templatized and it throws um the templatized recommendations. Not only that, it also provides customized uh recommendations on the basis of the configuration, on the basis of our usage patterns. And these recommendations are not hard. It's not like something that it recommends and then just leaves us hanging there. These recommendations provided are very easy to follow, very easy to implement and see results. You can think of Azure advisor as an a very personalized cloud consultant that helps you to follow best practices to optimize our deployments. It kind of analyzes our resources, our configurations, our usage and then it recommends a solution for us that really helps in improving the cost effectiveness, improving the performance, improving high availability and improving security in our Azure environment. So with this Azure advisor, we can get a proactive, actionable and personalized best practice recommendations. Now you don't have to be an expert. Just follow the Azure advisor and your environment is going to be good. It also helps in improve the performance, security, high availability of our environment. And also it helps in bringing down the overall Azure spend. And the best part is it's a free service that analyzes our Azure usage and provides recommendations how we can optimize our Azure resource to reduce cost and reduce cost at the same time boost the performance helps in strengthening the security and improve the overall reliability of our environment. Next in the list would be network watcher. Now this network watcher helps users identify and gain insights in the overall network performance and the health of the overall environment. Now these Azure watchers provides enough tools to monitor to diagnose to view the metrics and to enable or disable logs which means you know generate and collect the logs for resources in the Azure virtual network. So with network watcher can monitor and diagnose issues in networking without even logging into the virtual machines with just the logs which are real time we can actually come to a conclusion what could be wrong in a certain resource in a VM or in a database you know by just looking at the logs and not only that it's used for analytic or to gain some intelligence of what's happening in our network we can gain a lot of insight to the current network traffic pattern using the security group flow logs that this network watcher offers. It also helps in investigating VPN connectivity issues using detailed logs. Now you might or might not know that you know VPN troubleshooting requires both parties or it involves two parties. you know the person the network administrator on this side and the network administrator on the other side and they will have to check logs in their end and we'll have to check logs and our end stuff like that but with the network watcher it kind of takes it to the next level the logs itself we could easily identify which side is having the issue and suggest an appropriate fix and the next in the list would be Microsoft Azure portal now this Microsoft Azure portal it provides ides a single unified console to perform various number of activities like building not only building managing and monitoring the web applications that we build. Now this portal can be used to organize our environment or the appearance of the environment or the visual of the environment based on our work style. And using Azure portal, users can control who gets to manage or access the resources all from the Azure portal. And this Azure portal gives a very good visibility on the spends that happen on each resource, right? And if we can customize it, we can also identify spends based on team, spends based on days, spends based on department, stuff like that. So it kind of gives us a good visual of where the money is spending or where is the bill consumed within the Azure environment. Next in the list would be Azure resource manager. Now Azure resource manager enables us to manage the usage of the application resources. Now we use resource manager to deploy, monitor and manage solution resources as a group as if it's one single entity. Now the infrastructure of our application is typically made of various components which includes virtual machine storage virtual network web app database servers some other third party services that we might use in our environment and they are by nature separate services but with Azure resource manager we don't see them as different components or different entities instead we see them as related services in a group that supports an application. Now we kind of get the relation between them instead of you know letting them spread. Azure resource manager identifies the relation between them and helps us to visually see them all as one or single entity. Not only that, Azure resource manager helps or it ensures that the resources that we provision or deploy at a constant rate along with the other application. It also helps users to visually see their resources and how they are connected and that helps in managing the resources a lot better. Resource group also is used to control who can access the resources within the users's organization. Kind of gives you the fine grained control over who gets to access and who does not get access. And the last one in the management tools would be automation. And this automation gives us the ability to automate, configure and install upgrades across hybrid environments. It provides a cloud-based automation and configuration service. Not only that, this can be applied for non-asure environments as well which is on premises. So some of the automation we could do is process automation, update management automation, configuration features automation, stuff like that. And this Azure automation provides complete control during the deployment operation and also during the decommissioning of the workloads and resources. With automation we can actually automate uh time consuming or mundane or any task that's errorprone because of uh human errors those things can be automated. So irrespective of how many times you run it, it's going to run the same way and that really helps in reducing the overall time and also the overhead cost because a lot of the things are automated which means it's human error-free which means the application is not going to break and keep running for a longer time. With automation we can actually build a good inventory of operating system resources and configuration items all in one place with ease. And this really helps in tracking the changes and investigating the issue. Let's say something happened because we have automation because it's logging the configuration changes. It's easy to track, easy to identify, easy to identify what has changed lately that has broken the environment, go back and fix it or kind of roll it back. That solves the problem. And that actually summarizes the Azure management tools or management services. Now let's talk about the networking tools or the networking services available in Azure. There are variety of services especially networking services that Azure offers and I'm sure it's going to be an interesting one. Let's begin our discussion with content delivery network. Now the content delivery network in short CDN it allows us to perform secure and a very reliable content delivery. Not only that, it also helps in accelerating the delivery time or in other words reducing the delivery time also called as load times. It also helps in saving bandwidth and increases in responsiveness to the application. Let's expand on this. The content delivery network is actually a distributed network of servers that can efficiently deliver web content to users. Now, CDN's, we're going to use the word CDN here. CDN's store cached content on global edge servers, also called as uh pops, point of presence locations that are very close to the end users. So, the latency is minimized. It's like taking a copy of the data or taking a multiple copy of the data and storing it in different parts of the world. and whoever is requesting it, the data gets delivered to them from a server which is very locally to them. So this CDN offers developers a global solution for rapidly delivering high bandwidth content to users by caching the content in a strategically placed location which is very near to them. So these content delivery networks it really helps in handling that's one advantage you get for content delivery network that's we can handle spikes and heavy loads very efficiently and we can also run analytic against the logs that gets generated in content delivery network which helps in gaining good insight on the workflow and what would be the future business need for that application and this just like a lot of other services. This is on a pay as you go type. So you use the resource first and then you only pay for what you have used. The next one in networking would be express route. Now express route is actually a circuit or a link that provides an a direct private connection to Azure and because it's direct it gives low latency link to Azure. It gives good speed and reliability for the Azure data transfer. It could be on premises to Azure. So it gives very good speed. It gives increased reliability and low latency for that connection. Let's expand on this a bit. Now this express route is an service that actually provides an private connection between Microsoft data center and infrastructure in our premises or in a different collocation facility that we might have. Now these express routes uh do not go over the public internet and because they don't go over the public internet they offer a high security reliability and speed and low latency compared to the connections um which are in the internet because it's fast because it's reliable because it it has low latency it can be used as an extension of our existing data center. You know users are not going to feel the difference whether they are accessing services from an on- premises or in the cloud environment because latency is minimized as much as possible. Users are really not going to see the difference. And because it's a private line and not an public internet line, it can be used to build hybrid applications without compromising a privacy or the performance. Now these virtual private cloud these express routes can be used for taking backups. If assume a backup going through the internet that would be a nightmare. If you use express route for backups that's going to be fast and imagine recovering a data through the internet from the cloud through the internet to the on premises in a time of disaster. That would be the worst nightmare. So these express routes can be used not only to backup but also to recover the data because it provides good speed low latency. Recovering the data is going to be lot sooner. The next product or service we're going to discuss in networking is Azure DNS. Now Azure DNS allows us to host domain name in Azure and these domain names come with an exceptional performance and availability. Now, Azure DNS is used to set up and manage DNS zones and records for our domain name in the cloud. Now, this Azure DNS is a service for DNS just like the name says and it provides name resolution by using Azure's infrastructure and uh by using this domain we can actually manage the DNS ourselves through the Azure portal with the same credential. Imagine having a DNS provider which does not even belong in our IT. Imagine that environment. You know, we would have a separate portal to manage the DNS environment. Now those are gone and now we can actually manage the DNS in the very same Azure portal where we use the rest of the other services. And this Azure DNS very much integrates with other DNS service providers. It uses a global network of name servers to provide fast response to DNS queries. And these domains are having additional availability compared to the other uh domain service providers availability promises. These are going to have more availability than the rest because most of the servers are maintained by Microsoft and it helps resolve sooner. It helps reyncing let's say a server fails. It kind of helps reyncing with the rest of the servers. So all the Microsoft's environment, all the Microsoft's global network of name servers kind of ensures that our domain names are resolved properly. Not only properly but also are available most of the time. Right. Next in the list in networking services is virtual network. I'm sure this is going to be very interesting and I'm sure you're going to like it. So this networking or virtual networking in Azure, it actually allows us to set up our own private cloud in the public cloud. It gives us an isolated and highly secure environment for our application. Let's expand on this. Now this Azure virtual network helps us to provision Azure virtual machines and uh it helps us to securely communicate with other onremises and internet networks. It also helps in controlling the traffic that flows through or flows in and out of this virtual network to other virtual networks and to the internet. Now this Azure virtual network sometimes called as VNET is actually a representation of our own network in the cloud. It's actually a logical isolation of the Azure cloud dedicated to our subscription. All our environments are provisioned in a VNET that is separate from another customer's VNET. That way we have that logical separation there. So this virtual network can also be used to provision VPNs in the cloud. So we can connect the uh cloud and the on premises uh infrastructure and lot more especially in a environment where we have hybrid environment surely we will be using virtual network because that's going to require a VPN for secure data transfer in and out of the cloud and in and out of the on premises environment. All right so it kind of gives us an boundary for all the resources. So all the traffic between the Azure resources they kind of logically stay in between or logically stay within the Azure virtual network. And here we can design the network. It's given over to us. You know you can pick the IP, you can pick the routing, you can pick the subnet. You know, lot of freedom is given or I would say a lot of control on how the network is designed. It's not like something that's already cooked and we only get to use it. No, we can actually build the network from the scratch. We can pick the IP address that we like. We can pick, you know, which subnet needs to communicate with the other subnet, stuff like that. And like I said, if you are using hybrid environment, you definitely would be requiring a virtual network because it helps connect the on premises and the cloud in a secure fashion using VPN. The last product we're going to discuss in networking is a load balancer. This load balancer actually provides application a good availability and a good network performance. So how does it work? It actually works by load balancing the traffic to and from uh the virtual machine and the cloud resources. Not only that, it also load balances between uh cloud and cross premises virtual networks. With Azure load balancer, we can actually scale our application and create high availability for our services, which means our application will be available most of the time. If any of the server goes dead, the server does not get traffic. What happens if the server gets traffic? User is going to experience downtime. What happens if the server does not get traffic? User won't experience any downtime. The connection is shifted to an healthy service. So the user experiences uptime all the time. So this load balancer supports inbound and outbound scenarios and it provides low latency. It gives high throughput of the data transfer and we can actually scale up the flow of the TCP and UDP connections from hundreds to thousands to even millions because we have a load balancer now in between the user and the application. So how does it operate? This load balancer actually receives the traffic and it uh load balances the traffic to the backend pool of instances connected to it according to the rule and the help probe that we set. That's how it maintains high availability. So what does load balancer help? It helps in creation of high available scalable application in the cloud in minutes. It can be used to automatically scale the environment with the increasing application traffic. And one feature of load balancer is to check the health of the user's application instance and it removes or it stops sending the request to the unhealthy instance and kind of shifts that connection to the healthy instance. That way a user or a connection does not get stuck with an instance that's not healthy. That's all that you need to know about the networking services. Now let's talk about the storage services or the storage domain in Azure. Now Azure storage in general is a a Microsoft manage service providing cloud storage which basically is highly available, secure, durable, scalable and redundant because it's all managed by Azure. We don't get to manage a lot of it. And these Azure stoages are a group of storage services. They cater different needs. And the storage products include Azure blobs which is actually an object storage. It includes um Azure data lake. It includes Azure files as you see it. It includes Azure cures. It includes Azure tables and lot more. But let's start our discussion with Azure store simple. Azure store simple is an hybrid cloud storage solution that actually lowers the cost of storage to nearly 60% of how much you would be actually spending without using it. So, Azure Simple Storage or Store simple is an integrated storage solution that manages the storage task between on premises and the cloud storage. What I really like about Azure is that it's built around a hybrid environment in mind. There are a lot of other cloud providers that are there where running and hybrid environment is a big challenge. You know, it has some compatibility. you won't be able to find an hybrid or a on premises and cloud solution for your need stuff like that. But with the Azure especially when it comes to storage a lot of the things that we're going to see it clearly is designed with hybrid environment in mind. All right. So let's come back and talk about store simple. So store simple is an very efficient cost effective and a very easily manageable sand storage area networking solution in the cloud. I thought I'll throw in this information. The reason why it got store simple is really because it uses store simple 8000 series devices which are used in Azure data center and this uh store simple or simple storage. It comes along with storage tearing to manage uh the stored data across the various storage media. So the current the very current data is actually stored in on premises on solid state drives and data that is used less frequently is stored in uh HDDs or hard disk drives and the data that requires archived or that needs to be archived very old data let's say less frequently used data candidate for archived they are actually pushed uh to the cloud. So you see how this storage sharing automatically happens in store simple. And one another cool feature of store simple is that it enables us to create an ondemand and scheduled backups of data and and then store the data locally or in the cloud. And these backups are actually taken in the form of incremental snapshot which means that they can be created and restored quickly. It's not a complete backup. It's an incremental backup. And these cloud snapshots they can be critically important when there is a disaster and when there is a disaster recovery scenario because these snapshots can be called in and they can be put on storage systems and then they become the actual data. So recovering is faster if you have proper scheduled backups or if you have frequent backups. And this storage simple it really helps in easing our backup mechanism which means it kind of eases our disaster recovery steps or procedures as well. So the store simple it can be used to automate data management, data migration, data movement, data taring across the enterprise both in cloud and on premises. It actually improves the compliance and accelerates the disaster recovery for our environment. And if there is one thing that's increasing every new day in our environment, that would be storage. And this store simple addresses that need. And we really don't have to pre-plan or or think in deep or having a proper storage because now we have a simple storage available in the cloud. And moreover, it's on a pay as you go type. So not much pre-planning on storage is needed. Yes, there would be a need but not as much as I would without the cloud or without the simple storage. And the next service under storage that we would like to discuss is the data lake store. This data lake store or storage it's a cost effective solution for big data analytics in specific. So let's expand this. So this data lake storage is an enterprisewide repository for big data analytic workload. Now that's the major service that's dependent on this data lake store. And this data lake enables us to capture data of any size of any type and of any injection speed and it kind of collects them in one single space or in one single place for operational efficiency. I mean operational efficiency and for analytic purpose. Hadoop in Azure is very dependent on this data lake storage and this uh data lake store is designed with performance for analytics in mind. So anytime you think of or anytime you're using analytic in the cloud or anytime you're using Hadoop in the cloud in Azure we are definitely using or we will be to the most part or or the normal procedure or the right storage to pick would be data lake store in Azure. It's designed with security in mind. So anytime we use Azure storage we can be rest assured that we are using storage from within a data center which has or which was built with security in mind. So this data store also uses Azure blob storage behind the scenes for global scale durability and for performance. Let's talk about blob storage. Now blob storage provides large amount of storage and scalability. Now this blob storage is the object storage solution for Azure cloud. Let's expand a bit on blob storage. Azure blob storage is Microsoft offering for object storage. Now this blob storage is optimized for storing massive amount of unstructured data which could be text or binary data. It's designed and it's optimized for rapid reads. If I explain to you on what scenarios we would be using blob storage that might help you get a good understanding of what blob storage is. So it's help or its design as of now it's being used in many IT environments to serve images or documents directly to the browser. It helps in storing files for distributed access. A lot of fetchers can fetch data from Azure blob storage and it currently helping users stream video and audio. It's currently being used for writing log files. It's currently being used to store data as backup and restore at a later point in times of disaster recovery. It also is used as an archiving storage in lot of cloud IT environments. It's widely used in storing analytic data. Not only storing but also running analytic query against the data stored in it. So that's a wide use case for blob storage. Not only that, in addition to all that we mentioned, uh it also supports versioning. So anytime somebody updates an data, a new version gets created, which means at any point I can roll back as and when needed. And it provides a lot of flexibility on optimizing the users's storage need. It also supports uh taring of the data. So based on need when I actually explore I would find a lot of options I can pick from that uh you know suits to my unique storage environment or unique storage need and like I said it stores unstructured data and this unstructured data is available for customers through restbased object storage environment. The next product in storage service would be a Q storage. Now Q storage provides durable cues for large volume cloud services. It's a very simple and a cost-effective durable messaging queue for large workloads. Let's expand this Q storage for a moment. Now this Q storage is a service for storing large amount of messages that can be accessed from anywhere in the world through HTTP and HTTPS calls. A single queue or a single cube message can be up to like 24 KB in size. And a single que can contain millions of such 24 KB in size messages. And how much can it hold? It can hold up to the total capacity of the storage account itself. So that's kind of easy to translate how much will it hold. And this Azure Q storage, it provides an messaging solution between applications and components in the cloud. What does it help? It helps in designing an application for scale. It helps in decoupling the application. So you know it's not very dependent or sometimes it's not at all dependent on the other application because now we have a queue in between which kind of translates or which kind of connects or which kind of decouples both the environment. Now we have a queue in between both the environment can scale up or scale down independently. The next in the storage service would be file storage. Let's talk about file storage. Now these Azure files provide secure, simple and managed cloud file shares. Now with fileshare in the cloud, it actually extends the user servers on premises performance and capacity and lot of familiar tools for the cloud fileshare management can be used along with the file storage that we're talking about. So let's expand a bit on file storage. Now this Azure files or Azure file storage offers a fully managed file shares in the cloud that can be accessed via the uh SMB protocol server message block protocol. Now this Azure file shares can be mounted concurrently by cloud or in on premises deployments. Lot of operating systems are compatible with it. Windows are compatible, Linux is compatible, Mac OS is compatible. In in addition to all this being able to run on on premises and on the cloud or being able to access from on premises and on the cloud, it can also offer cache for caching uh the data and keeping it locally. So it's immediately available when needed. So that's some additional feature I would say that's some advanced feature that it offers compared to the other file shares available in the market. Let's talk about table storage. Let's talk about table storage. Now table storage is a NoSQL key value pair storage for quick deployments with large semistructured data sets. The difference between one important thing to note with table storage is that it has a flexible data schema and also it's highly available. Let's expand a bit on table storage. So anytime you want to pick a schemaless a NoSQL type table storage is the one we'll end up picking. It provides an key pair attribute storage with a schemalless design. This table storage is very fast and very cost effective for many of the applications and for the same amount of uh data. It's a lot cheaper when you compare it with the traditional SQL data or data storage. So some of the things that we can store in the table storage are of course they're going to be flexible data sheets uh such as uh user data for web application address books device information and other types of metadata for our service requirements and it can have any number of tables up to the capacity limit of the storage account. Now this is not possible with SQL. This is only possible with NoSQL especially with table storage in Azure. explanation of storage really concluded the length and breadth of the explanation this CEO was giving his uh IT personal but this IT personal is not done with it yet. He still has a question even after this lengthy discussion and his question was well there are a lot of other cloud providers available. What made you specifically choose Azure? I mean from the kind of question that he asked we can say that he is very curious and uh he definitely had asked an very thoughtful question. So his CEO went on and started to explain about the uh other capabilities of Azure or how it kind of outruns the rest of the cloud providers. So he started or uh he again started his discussion but from a different angle now. So he started to explain what are the capabilities or how Azure is better than the competitors. So he started with explaining the platform as a service capabilities and I'm going to tell you what the CEO told his ID person. So this platform as a service or in platform as a service the infrastructure management is completely taken care by uh Microsoft allowing users to focus completely on the innovation. No more infrastructure management responsibilities. Go and focus on innovation. That's that's a fancy way of saying it. When we buy platform as a service, that's what we get. We can contribute our time on innovation and not just maintaining the infrastructure. And u Azure especially is u net friendly. Azure supports the .NET programming language and um it has or it is built or designed or it is optimized to work with old and new applications deployed using net programming framework. So if your application isnet most of the time you would end up picking Azure I mean if you try to compare most of the time you would end up picking Azure as your cloud service provider and the security offerings that Azure offers is it's designed based on the security development uh life cycle which is an industry-leading assurance process. When we buy services from Azure, it assures that uh the environment is designed based on security development life cycle. And like I mentioned many times in the past and I would like to mention it again, Azure has well thought about the hybrid environments which a lot of other cloud providers have failed. So it's very easy to set up an hybrid environment to migrate the data or not to migrate the data and still run a hybrid environment. They work seamlessly with the Azure because Azure provides seamless connection across on premises data centers and the public cloud. It also has a very gentle learning curve. If you look at the uh documentation, it's picture and the documentations are neat and clear. Would really it would encourage you to learn more. It would encourage you to think and imagine and try easily get a grasp of how services work. So it has a very gentle learning curve. Azure allows the utilization of technologies that several business have used for years. So there is a big history behind it. It has a very gentle learning curve. the the certifications, the documentations, the stage bystage certification levels. It's all very gentle learning curve which is generally missing in other cloud service providers. Now, this would really impress the CTOs or or people working in finance and budgeting. If an organization is already using Microsoft software, they can definitely go and avail or be bold and ask for a discount that can reduce the overall Azure spending. In other words, overall pricing of the Azure. So that's what helped or they are the information that helped the CEO pick Azure as his cloud service provider. And then this year goes on and talks about the different companies that are currently using Azure and they are definitely using Azure for a reason like Pixar, Boeing, Samsung, EasyJet, Xerox, BMW, 3M. They are major multinational, multi-billion companies. They rely, run, operate their IT in Azure. And this CEO has a thought that his IT person is still not very convinced unless and until he shows him a visual of how easy things are in Azure. So he goes on and explains about a practical application of Azure which is what exactly I'm going to show you as well. All right, a quick project on building an Azure app using or building a net application in Azure web app and making it connect to an SQL database will solidify all the knowledge that we have gained so far. So this is what we're going to do. I have an Azure account open as you see logged in and everything is fresh here. Let me go to resource group. There's nothing in there. It's it's kind of fresh. Right, I'm logged in and this is what we're going to do. So, we're going to create an application like this, which is nothing but an todo application, a to-do list application, which is going to run from the web app, get information from us, and save it in the database that's connected to it. So, you can already see it's a two-tier application, web and DB. All right, so let me go back to my Azure account. The first thing is to create an resource group. Let's give it an a meaningful name. Let's call it Azure Simply Learn. All right. And it's going to be a free trial. And the location, pick one that's nearest to you or, you know, wherever you want to launch your application. Now, for this use case, I'm going to pick Central US and create. It's going to take a while to get created. There you go. It's created. It's called Azure Simply Learn. Now, what do we need? We need an web app and an a separate SQL database. Let's first get our web app running. So, go to app services and then click on add. It's not the web app plus SQL that we want. We want web app alone for this example. So, let's create an web app. Uh give it a quick name. Let's call it u Azure Simply Learn. The subscription is free trial and I'm going to use my existing resource group, a resource group that we created some time back. It's going to run out of Windows and we're going to publish uh the code. All set we can create it. All right. While this is running, uh let me create my uh database. Right? SQL database. Create a database. Give it a name. Let's call it Azure SimplyLearn DB. Put it in our existing resource group that we created. It's going to be a blank database. All right. And it's going to require some uh settings like the name of the server and the admin login, the password that goes along and in which location this is going to be created. The server name is going to be Azure SimplyLearn DB. That's the server name. And the admin login can be what can be the admin login name. Let's see. So let's call it simply learn. That's my admin login name. And let me pick a password. Click on create. So what have we done so far? We have created an web app and we have created an uh a database in the resource group that we have created. So if I go to resource group, it's going to take some time before things show up. So if I go to my resource group, I only have one resource group as of now, Azure Simply Learn. And there I have a bunch of resources being created. You know, it's still being created, right? In the meantime, I have my application right here that's running out of uh or that's in Visual Studio as of now. Right. So once the infrastructure is set and ready in the Azure console, uh we're going to go back to Visual Studio feed these inputs in the Visual Studio. So the code knows what the database is, the the credentials to log into the database, stuff like that. So we're going to feed those information in Visual Studio. By that we're actually feeding it into the application and then we're going to run it from there. Deploying this application takes uh quite a while. We really got to be patient. All right. Now we have all the resources that we need for the application to run. Here is my uh database and here is my app service. There's one more thing we need to do that is um create an firewall exception rule. So one more thing needed is to create an firewall exception uh rule. Right? So the application is going to run from my local desktop and it's going to connect to the uh uh database, right? So let's add an exception rule by simply adding the client IP. It's going to pick my IP, the IP of laptop I'm using as of now and it's going to create an exception to access the database. So that's done. Now we can go back to our Visual Studio. I already have a couple of um apps running or a couple of uh configurations pushed from uh Visual Studio. I'm going to clean that up. If you're doing it for the first time, you you may not uh need to do this. All right. So, let's start from the scratch. This is very similar to uh how you would be doing in your environment. All right. So we're going to uh select an existing Azure app service. Now before that I have logged in as you can see I have logged in with my credential. So it's going to pull few things automatically from my Azure account. So in this case I'm going to use an existing Azure app. So select existing and then click on publish. All right. If you recall, these are the very same resources that we created a while back. All right, we have clicked on save and it's uh running kind of validating the code and it's going to come up with an URL. Now, initially the URL is uh not going to work because we haven't mapped the application to the database. That would be the next thing. All right. So, the app has been published and it's running from my uh web app. As of now, it's going to throw an error. Like you see, it's throwing an error. That's because we haven't mapped the app and the DB together. So let's do that. All right, let's do that. So let's go to server explorer. Uh this is where uh we're going to see our uh uh databases that we have created. Now let's quickly verify that. Go back to uh the resource group, right? Appropriate resource group which is right here. And uh here I have my uh database Azure SimplyLearn database. All right. It has some issues connecting uh to my uh database. Give me a quick moment. Let's fix it. Okay. All right. So, we'll have to map the database into this application. All right. So, let's go to the solution explorer. Click on publish. And a page like this gets shown. And from here, uh we can go to configure. Here is our web app. All right, with all its uh credentials, let's validate the connection number one. All right, and then click on next. This is my DB connection string, right, which the app is going to use to connect to my DB. Now, if you recall, RDB was uh Azure uh simply learn DB and that's not being shown here. So, let's fix that, right? So, let's fix that. Click on configure and here uh let's put our uh DB servers uh URL. Now before that let's change this to SQL server. All right. And then in here uh put the DB's URL. So go back to Azure. Here is my DB or server's name. Put that here. Right. the username to connect to the server. That's right here. Put that in. And the password to connect to the server. Let's put that in. All right. It's trying to connect to our Azure portal or the Azure infrastructure. And here is my database. If you recall, it's Azure SLDB. That's the name of the database. Let's test the connection. Connection is good. Click on okay. So now it's showing up correctly. Azure simply learn DB. That's the name of uh the database that we created. Now it's configured. All right, let's modify the data connections. Right, let's map it to the appropriate database again. All right, so our name of the database is Azure SimplyLearn DB and then uh it's going to be SQL server. That's the data source. The uh username is simply learn and the password is what we have given in the beginning. All right, let's validate the connection. It's good. Click okay. Now we're all set and ready to publish our application again. Now the application knows how to connect uh to the database. We have educated it with the u the correct connection strings the DNS name the username and the password for the application to connect to the database. So, Visual Studio is building this project and once it is up and running, we'll be prompted with an URL uh to connect and anytime we put or we give inputs to the URL that's going to receive the input and save it in the database. All right. So, here is my uh to-do list app and uh I can start uh creating to-do list for myself. All right. So, I have the items already listed. I can create an entry and these entries get stored in the u in the database. I can create another entry and I'll take the dog for a walk. That's going to get stored. I can create another entry uh book tickets for scientific uh exhibition and that's going to receive and put that in the database. And that concludes our session. So through this session we saw how I can use Azure services to create web app and connect that to the DB instance and how those two services which are decoupled by default which are separate by default. How I can you know use the connection strings to make connection between the app server and the database and be able to create an working app. Imagine a large hospital where doctors and nurses need to access patient records every day. They look up medical histories, test results, and treatment plans to make sure they give the best care. One day, the hospital's old database system crashes and suddenly nobody can get the information they need. Doctors can't see patient records during emergencies and everything comes to a standstill. What can the hospital do to make sure this never happens again? This is where AWS databases come to the rescue. By using AWS powerful and reliable database services, the hospital can make sure the patient data is always available, safely stored, and easy to access. AWS offers a range of database solutions that keep the data secure and backed up. So doctors and nurses can always get the information they need even in emergencies. So in today's video, we'll explore about the storage services of AWS and the different types of databases available in AWS. We'll explain how each service works, their key features, and the best ways to use them. Whether you are a developer, a database administrator, or just curious about cloud technology, this video has something for you. So what is AWS? Amazon Web Services or AWS is a comprehensive cloud computing platform provided by Amazon offering a wide array of ondemand services such as compute power, storage and databases along with advanced functionalities like machine learning, analytics and IoT. It helps businesses to scale their applications efficiently. It reduces the IT cost as it has pay as you go model. Its global network of data centers ensures high availability and security. Now what is a database and why is it important? So databases are systems that store, organize and manage lots of data efficiently. They have tables to hold the data, queries to find specific information and indexes to speed up searches. Databases also ensure that all operations are completed correctly and keep data secure. Now there are different types of databases. Relational databases use structured tables and SQL for queries while NoSQL databases handle unstructured data and are easier to scale. Now using databases in cloud has many benefits. Cloud databases can easily grow or shrink based on your needs. So you can handle busy times without paying for extra resources you don't need. They're also reliable because cloud providers manage backups and replicate data in different locations which minimizes downtime and data loss. Additionally, cloud databases reduce costs because you don't have to buy and maintain your own hardware and software. They allow global access so teams and applications around the world can quickly get the data they need. Now, let's discuss the various storage services provided by AWS and identify which AWS databases use each type of storage. So, AWS offers a variety of storage services tailored for different use cases. First we have Amazon S3 or simple storage service which is an object storage service that is highly scalable, durable and secure. Ideal for backups, big data analytics and content storage. It's used by databases like Amazon RDS, Amazon Dynamob and Amazon Red Shift for backups and data storage. Next we have Amazon EBS or elastic block store which provides block storage for EC2 instances offering different volume types for balancing cost and performance. Now Amazon EBS is used by Amazon RDS and Amazon Aurora for database storage. Now next we have Amazon EFS which is elastic file system. Now it offers scalable file storage that can be concurrently accessed by multiple EC2 instances suitable for applications needing shared access like web serving and content management. Next on the list is Amazon FSX which provides fully managed file systems optimized for specific workloads such as FSX for Windows file server and FSX for Luster. The latter being ideal for high performance tasks like machine learning and big data processing. Now for archival storage, Amazon S3 Glacierio offers low cost storage for infrequently accessed data. Perfect for complent and archival needs. Now finally we have the AWS snow family including snow cone, snowball and snow mobile which facilitates secure and efficient data transfer into and out of AWS supporting the initial data loading for various databases. So having known the services offered by AWS, now let's move on to the different databases in AWS and discuss each of them with their use cases. So first we have Amazon Dynamo DB. Now Amazon Dynamob is a fully managed NoSQL database service offered by AWS. It is designed to handle large amounts of data with high speed and low latency, making it perfect for applications that need to store and retrieve data quickly. Some of its features are scalability. Dynamo DB can automatically scale up or down based on the application's demand ensuring consistent performance. It provides singledigit millisecond response times which is ideal for real-time applications. AWS handles all the maintenance tasks like backups, patches, and hardware provisioning so you don't have to worry about them. So let's see a use case. Imagine you're running a mobile game with thousands of players online simultaneously. Each player's game progress scores and in-game purchases need to be stored and retrieved quickly to ensure a smooth gaming experience. Now, Dynamob can efficiently handle this type of workload by providing quick access to player data even when there are sudden spikes in game activity. This ensures players have a seamless and enjoyable experience without delays or lag. Now, next we have Amazon Aurora. Amazon Aurora is a high performance fully managed relational database service offered by AWS. It's designed to be compatible with MySQL and Postgres SQL which are popular database systems, but it's much faster and more reliable. Aurora automatically takes care of tasks like backups, software patching, and scaling. So, you don't have to worry about them. Let's see its use case. Imagine you have an online store that handles thousands of transactions every day. You need a database that can quickly process orders, manage inventory, and store customer information without any slowdowns. Amazon Aurora is perfect for this because it can handle lots of read and write operations very efficiently, ensuring a smooth shopping experience for your customers. Plus, Aurora can automatically scale up to meet high demand during sales or holidays and scale down when traffic is lower, helping you save costs. Its high availability and automatic backup features mean your data is always safe and accessible, even in case of hardware failures. This makes Aurora an excellent choice for running a reliable and responsive e-commerce website. Next on the list, we have Amazon RDS. Now, Amazon RDS or Amazon relational database service is a cloud-based service that makes it easy to set up, operate, and scale a relational database. This means you can store and manage your data in a structured way using popular database engines like MySQL, PostB SQL, Oracle, SQL Server, and Maria DB without worrying about the underlying infrastructure. Now, imagine you run an online store. You need a database to keep track of your products, customers, orders, and inventory. Using Amazon RDS, you can quickly create a database that handles all these tasks. RDS automatically takes care of backups, software updates, and scaling. So you don't have to worry about your database crashing during a big sale or needing more space as your business grows. Now, next we have Amazon Time Stream. Now, Amazon Time Stream is a cloud-based time series database service offered by AWS designed to efficiently store and analyze time stamp data. Now, timestamp data is information collected at regular intervals like temperature readings every minute or stock prices every second. So the key features encrypt performance. It handles trillions of events per day with fast query capabilities. Now it automatically scales up or down based on the volume of data. Now you only pay for storage and queries you use with automated data life cycle management to reduce costs. Now imagine you have a network of thousands of IoT sensors deployed across a city to monitor air quality. Each sensor collects data like temperature, humidity, and pollution levels every few seconds. Now, Amazon time stream can efficiently store this vast amount of timestamp data and provide quick access for real-time monitoring and historical analysis. This helps in analyzing trends, predict pollution levels, and make datadriven decisions to improve air quality. Next on the list, we have Amazon Neptune. Now, Amazon Neptune is a fully managed graph database service provided by AWS. is designed to work with highly connected data making it ideal for applications where relationships between data points are as important as the data itself. Its key features include graph models. It supports popular graph models like property graph and RDF which is resource description framework optimized for quering large amounts of interconnected data quickly. It handles database management tasks like backups, patching and scaling automatically. Now one common use case for Amazon Neptune is building social networking applications. So in a social network users are connected to each other in various ways friends, followers, likes, comments and groups. Now Neptune can efficiently manage these connections and quickly answer complex queries like who are the mutual friends of two users or what groups are my friends part of. So by using Neptune, social media platforms can provide a fast responsive user experience even as a number of users and connections grow. So next we have Amazon QLDB. Now it stands for Amazon Quantum Ledger Database which is a fully managed ledger database provided by AWS. It is designed to maintain a complete and unchangeable history of all changes made to your data over time. uh think of it like a highly secure and transparent digital log book where every entry is recorded and can't be altered. So the key features are immutable ledger. Once data is entered, it cannot be changed or deleted. It ensures the integrity of your data by allowing you to verify that it hasn't been tampered with. Now AWS handles all the maintenance including scalability, backups, and availability. So one common use case for QLDB is in tracking financial transactions. So imagine a bank needs to maintain an accurate and tamperproof record of all the transactions to ensure transparency and compliance with regulations. So QLDB can provide a trustworthy and unchangeable log of every transaction making it easy to audit and verify the history of financial activities. Now the last on the list is Amazon RDS on VMware. So it is a service that allows you to run Amazon's managed relational database service or RDS in your own data centers using VMware. Now, VMware is a virtualization and cloud computing software provider. So, this means you can enjoy the benefits of RDS like automated backups, patching and scaling without moving your data to the AWS cloud. So, it's perfect for businesses that want to keep their data on premises due to regulatory requirements, low latency needs or existing investments in VMware infrastructure. For example, imagine a hospital that needs to store and manage large amounts of sensitive patient data. So due to strict privacy regulations, this data must remain on-site itself. With Amazon RDS or VMware, the hospital can set up and manage databases easily within their own data centers. They get the reliability and automation of AWS RDS while keeping patient information secure and compliant with local laws. So this setup ensures a hospital's data is always backed up, secure, and accessible without the complexity of managing database servers manually. Let's dive straight into the top AWS services. So guys, our first service is Amazon EC2 which stands for elastic compute cloud. So basically what it is, Amazon EC2 basically lets you rent virtual computers which is servers in the cloud. You can use them to run your applications without having to buy your own physical servers. And you'd be questioning that why this service is so important. So guys, the reason is that businesses no longer need to invest in expensive physical servers which can be difficult to maintain and scale. So EC2 allows companies to adjust their computing power based on the current needs ensuring they only pay for what they use. This flexibility helps companies to save cost during low traffic periods and manage high demand during peak times all without worrying about maintaining physical infrastructure. Now let me propose a case study where a company named Airbnb used EC2. So guys this was the challenge. Airbnb experienced issues with scaling during high traffic periods such as holidays and during major events which leading them to system slowdowns and potential outages. Managing their own server was very very costly and time consuming as they had to predict demand and manually add capacity which often led to over and under poisoning. Now I'll explain what over and under poisoning is but let us first look at what are the issues they faced. The first one they had the scaling issue which means that high traffic periods during holidays caused slowdowns and outages. Then there was a problem of server management. Managing physical servers was very expensive and complex. Then they had unpredictable demand. It was very hard to predict traffic spikes which led them to capacity problems. Then there was manual capacity addition. It also required manual intervention to scale up during their resources. And finally they had over or under poisoning which mean often they had many servers or few servers which led to wasting resources or causing slowdowns. Now what was the solution guys? So after moving to Amazon EC2 Airbnb could automatically scale its infrastructure up and down based on the demand. EC2's pace as you go model allowed them to avoid the cost of overprovisioning and handle peak traffic seamlessly. So guys, there is some statistics which I want to share that Airbnb infrastructure scaled up by 3x during the peak period using EC2's autoscaling feature which led them to zero downtime during high demand seasons. They also reduce infrastructure cost by 20% by paying only for the capacity they needed. Now let us move to our second service. So guys our second service is Amazon S3 or simple storage service. What it is guys? Basically Amazon S3 is a cloud storage where businesses can store and retrieve any amount of data like documents, videos and backups. Why it was important guys? Basically S3 provides virtually unlimited secure storage that automatically scales with your needs. It eliminates the need for businesses to purchase and manage physical storage hardware. S3 also integrates easily with other AWS services making it a key component for storing large amount of data like backup application files or even media streaming content. Its high durability is around 99.99% which ensures that your data is safe and always accessible. Now let us look at a case study of Netflix. So guys during 2012 Netflix faced a massive outage due to a failure in their data storage system resulting in downtime that cost them millions in loss in revenue. Their existing infrastructure could not handle the massive amount of content that required constant maintenance. Now there are some of the problems with Netflix faced. The first one is massive outage which means that Netflix experienced a major data storage failure in 2012. Then they had to go through a significant downtime. This outage resulted in millions of dollars in lost revenue. They had inadequate infrastructure. Their existing storage system couldn't handle the large content volume. Then there was scalability issues and also constant maintenance. The infrastructure struggled to scale up with the growing user demand and also caused them lot of problems. Now after migrating to Amazon S3, Netflix was able to store massive amount of data. S3's scalability allowed Netflix to handle global content distribution without interruptions or data loss. Now let me show you some statistics, guys. So Netflix now streams to over 230 million users globally with S3 handling 1,000 pabytes of video content approximately. The switch to S3 reduce Netflix data loss risk to near zero and downtime dropped by 90%. So guys this was one of the case study where Netflix used S3 and this was the amazing result that they got. Now let us see of the one of the next Amazon web services which is Amazon RDS or Amazon relational database service. So what it is guys? RDS is a managed database service that takes care of setting up, maintaining and backing up databases for you. Why it is important guys? Because managing databases can be time consuming. It involves task like software updates, backups and scaling. RDS automates these tasks freeing up valuable time for businesses to focus on the other core activities with features like automated backups, multiszone availability and easy scaling. RDS helps businesses to ensure their databases are always running smoothly and securely without the headache of manual intervention. Now we'll take again the example of Netflix. So guys during this phase also Netflix suffered from a critical database outage leading to a data corruption and millions in losses. Managing onremises database was very very difficult as backups, scaling and disaster recovery required significant resources and manual effort. Now these are some of the problems which Netflix faced. The first one was critical database outage where Netflix experienced a major database failure. Then they had to go through data corruption where this outage caused significant data corruption. There was massive losses because there was incident resulted in millions of dollars in losses. Then there were some on-premise challenges like managing their on-premise database was very complex and inefficient and there was also lack of automation because manual database management increase the risk of failure. So guys by using Amazon's RDS Netflix automated database backups patching and scaling RDS multi-aser deployment provided high availability and fall tolerance which ensured that data losses during the failure outages are very very minimal. Now there is some statistics that Netflix reduced its database recovery time from hours to minutes in using RDS. Their database operational cost also dropped by 50%. And due to the automated management features see how this service was very useful for Netflix. Now let us move ahead and try to understand our next service which is AWS Lambda. But before we discuss this service just a quick info guys. Simply learn has got cloud architects master program. You can master AWS, Azure, Google Cloud with the cloud architect course. You will build expertise in AWS, Microsoft Azure, GCP with the cloud architect certification course. You'll also receive exam vouchers which is included on any Azure course. You'll access official AWS authored self-arning content. Plus, you'll also master cloud architectural principles, design, and also deploy a scalable service on cloud platforms. So guys, hurry up now and join the course. The course link is mentioned in the description box. Now let us move ahead in the discussion of what is AWS Lambda. So guys, Lambda lets you run your code in the cloud without having to manage servers. Basically, it automatically scales up when needed and only charges for the time your code runs. Why it is important, guys? Because Lambda allows businesses to run code without worrying about servers or infrastructure, paying only for the compute time used. This means companies can handle fluctuating traffic without having to overprovision servers, which means that it will help in saving cost and reducing complexity. Lambda is ideal for event-driven applications where task are triggered based on the specific events such as a file upload or a user action. Now there's a company called iroot guys. So iRoot needed to process large volumes of data from millions of Roomba devices worldwide. Managing servers to handle this real-time data was very very complex and expensive especially when usage fluctuated. Now there was some problem guys with this that they had high data volume. They had realtime processing problems. They had a problem of server management. Then the cost challenges also came up and the scalability issues. Then iroot adopted AWS Lambda's serverless architecture to automatically scale based on the number of incoming requests. They no longer had to manage servers or pay for idle time as Lambda only charges for the exact compute time used. So guys, what was the result? That iRoot saw a 90% reduction in infrastructure cost by using Lambda's pay-per-use model. Lambda processed over 20 million events per day, scaling effortlessly without manual intervention. So guys, these were the success story of iRoot by using the AWS Lambda service. Now let us move ahead and discuss about our next service which is Amazon CloudFront. So guys, what is CloudFront? Basically CloudFront is a content delivery network that speeds up the delivery of websites, videos and other data to the users around the world. Why it is important guys? Because CloudFront reduces the time it takes to deliver the content to users, particularly those located far from the origin server. This is crucial for businesses that need to provide a fast and seamless experience to global audiences. Whether it's delivering videos, web applications or large files, CloudFront ensures low latency access improving the user satisfaction and engagement. So guys, you have heard about a company called Slack. Slack once experienced high latency and slow message delivery for users located far from their data centers. This created delays and inconsistent user experience especially for global teams collaborating in real time. Now let us see what were the problems faced by Slack. They had a problem of high latency where I have told you that users far from Slack's data center experienced significant delay in message transmission. The slow message delivery was there. Geographical impact was one of the problem where the latency issues were more pronounced for global teams collaborating across distant locations. Then if we talk about real-time collaboration were also hindered. This delayed caused challenges for teams that rely on real-time communication. which finally affected and disrupting the workflow and finally they had inconsistent user experience. So guys by implementing Amazon's CloudFront Slack was able to cach and deliver content from edge location closer to the users reducing latency and improving overall performance. CloudFront's integration with AWS Shield also improved security against potential DDoS attacks. Now after using the service, Slack reduced the latency by 50% globally, providing realtime messaging to 10 plus million daily active users. They also experienced 40% faster file uploads and improved performance for international teams. So guys, this was a success story of Slack. Now let us move ahead and discuss about our next service which is Amazon EBS or elastic book store. So guys, what it is? Basically, Amazon EBS provides high performance storage for application running on EC2 instance. It is like a virtual hard drive that you can attach to your EC2 server. Why it is important guys? Because EBS offers fast, reliable and persistent storage for applications that require consistent high performance storage like databases or big data applications. Businesses can scale storage up or down as needed. EBS automatically backs up the data with snapshots which ensures minimal downtime and data loss. So guys, there's a company called Expedia which faced performance issues with their existing storage system. It struggled to handle high volume of transactions during peak booking times leading to slow response times and frustrated customers. They had performance issues. They had high transaction volume problem like as I've told you during the booking busy periods. Then they had slow response time where customer experienced slow response affecting their ability to complete bookings efficiently. Then they had the problem during the peak booking. They faced challenges where the problem was basically the performance issues. Now the customers were also frustrated. So what Xedia did was Xedia migrated their databases from Amazon EBS which offered consistent low latency performance and automatic scaling to meet high demand periods. EBS also provided robberous snapshots backups for disaster recovery. As a result, Expedia improved booking transaction speeds by 35% ensuring fast response time during their pre-travel seasons. They also increased their data through output by 2x supporting millions of daily searches queries without the delays. So this was a success story of Expedia guys. Now you'd be excited to know the next success story. So our next AWS service is Amazon VPC or Amazon virtual private cloud. What is Amazon VPC? Basically, VPC allows businesses to create a secure private network in the AWS cloud, giving them control over how their data and applications interact with the internet. Why this is important, guys? Basically, VPC provides businesses with full control over their cloud network, including IP addresses, subnets, and security. It allows businesses to securely connect their onremises infrastructure to the cloud and ensures that sensitive data is kept separate from the public internet. For industries like finance and healthcare, this level of security is critical for meeting regulatory compliance. What was the challenge guys? So there's a company name called Capital One. Capital One needed a secure and scalable cloud solution to manage its sensitive financial data while meeting strict regulatory requirements. Their on-promises infrastructure was expensive to maintain and difficult to scale securely. So guys, they had problems like need for security, scalability challenge, they had a problem of regulatory compliance, they had high maintenance cost and they it was very difficult to scale securely. So guys, by creating an isolated virtual private cloud, Capital One securely migrated its application and data to AWS. VPC gave them full control over their networking environment, ensuring compliance with data privacy regulations while reducing infrastructure costs. Capital One basically reduced their infrastructure management cost by 30% by using the VPC. They achieved 99.99% of uptime for critical applications thanks to secure scalable cloud infrastructure of VPC. So guys this was one success story of capital one. Now let us look at another Amazon web service which is Amazon AM or Amazon identity and access management. What it is guys? Basically, IM lets businesses control who can access their AWS resources by setting permissions and user roles. It is important because IM ensures that only authorized individuals can access sensitive resources, reducing the risk of security breaches. It's a critical tool for controlling access in large organizations where multiple teams need different level of access to cloud resources. IM also supports multiffactor authentication which adds an extra layer of security. Now what is the challenge guys which a company named Autodex faced? So Autodex had a global workflows and managing users to access various AWS resources was becoming very complex. They needed a way to ensure that only authorized users could access sensitive data and resources while maintaining security across the board. So they faced a problem of complex user access management. Then there was a need for authorized access. Then there was a global workforce challenge with Autodesk faced. Then they had to also maintain their security standards. And they had a problem of access control. They needed a solution on access control where a more efficient and a scalable system was required by Autodesk to simplify and secure user access management across the AWS resources. So guys, Autodesk implemented AWS to manage permissions and access control across their global team. With IM they created detailed user roles and policies ensuring secure access based on need and reducing the risk of data breaches. So guys Autodesk reduced unauthorized access incidents by 60% after implementing IM. They decreased the time spent on access management by 40% thanks to the IM's centralized control system and that was possible. So this is how Autodisk solved this problem. Now let us move ahead and discuss about our next service. This is a very amazing service guys. Its name is Amazon SQS or Amazon simple Q service. Basically Amazon SQS is a messaging service that allows components of systems to communicate with each other by sending and receiving messages between distributed applications. Why it is important guys? Because SQS allows systems to scale independently by decoupling tasks, meaning different part of an application can work on their own schedule without being dependent on one another. It's useful for batch processing, eventdriven applications and microservices. I know it sounds bit of a technical jargon but these are some of the scenarios where SQS is used. So guys, you have heard about this famous company called Disney Plus. Disney Plus face challenges in managing their large volume of user request especially during their release of popular shows and movies. Handling real-time requests without overloading the system was a constant issue. They faced problem like high user request volume, realtime request handling. Then system overload risk was there because the platform constantly struggled with the risk of system overload during peak viewing times. Scalability challenges were also there because handling large number of concurrent users required scalable solution and also consistent user experience means they ensure to have a smooth and uninterrupted experience for all the users during high demand periods which was not happening. Now Disney Plus adopted Amazon SQS to queue and process task efficiently decoupling their application components. This ensured that tasks such as streaming requests were processed smoothly even during high traffic periods. And finally, Disney Plus handled over 1 million requests per second during peak streaming periods with SQS ensuring no message was lost. The use of SQS improved systems performance by 25% enabling Disney Plus to deliver uninterrupted streaming experiences. So guys, this is a success story of Disney Plus. Now let us move ahead and discuss about our final service. Can you guess it guys? Yes, it is Amazon Dynamo DB. Dynamob is a fully managed NoSQL database service that is fast and scalable. It is ideal for applications that need to handle large amount of data with low latency. So this is the thing. Now you would be wondering why Dynamo DB is important. So guys, DynamoB is very essential for applications that experience rapid growth or fluctuating demand. Unlike the traditional databases, they might struggle to keep up the volumes of traffic. But Dynamo DB can automatically scale up to handle millions of requests per second. This is just something which I told you. Let me elaborate this by the story of a company called Lyft. So guys, Lyft needed a database that could handle millions of write requests in real time. But their traditional database systems could not scale efficiently to meet the demand leading to slow response time during busy hours. They had problem like real-time data handling, scaling limitations. They had they had high request volume, they had slow response times and also they needed a scalable solution for this problem. Now here comes the Dynamo DB. Lyft switched to Amazon's Dynamo DB which provided fast, scalable and serverless architecture with NoSQL database services. Dynamob ability to handle millions of requests per second ensured that Lyft could match drivers with riders in real time without latency. Now this is the thing which Lyft has seen. Lyft processed over two million ride request per day with Dynamob scaling automatically to meet the peak demand. They improved the response time by 70% ensuring a smooth experience for both drivers and writers. This is how Lyft solved this problem. What amazing service is Dyn. Hello everyone, welcome back to the channel. Today I want to take you on a journey that could transform your career much like how cloud computing has transformed some of the world's most innovative companies. Imagine Netflix once a DVD rental service transforming into a streaming giant capable of delivering highdefinition content to millions of users simultaneously. Or consider Airbnb which has used cloud computing to manage listings and bookings for millions of properties around the globe providing a seamless experience for host and travelers alike. Both Netflix and Airbnb utilized cloud technologies to efficiently scale their businesses, manage large volumes of data and ensure high availability and performance. So by transitioning from traditional costly and inflexible on-remises infrastructure to scalable cloud environments, they significantly reduce cost, accelerated innovation and improved user experience in real time. Now you might think that working on such impactful projects requires years of experience and advanced degrees. But there's the good news guys. With the right approach, you can start a career in cloud engineering in just 3 months, even if you are starting from scratch. In this video, I will outline a clear actionable plan that uses entirely free online resources to get you there. We will cover the essential skills you need to learn, the certifications that can help validate your knowledge, and practical projects that will make your resumes stand out. So if you're ready to dive into the world of cloud computing and perhaps one day contribute to the next big thing in tech. So stay tuned guys. So let's get started. And the number one point you should start with is starting your cloud journey. So transitioning into cloud engineering may seem daunting especially if you are new to this field. The first step is understanding why this is a valuable career move. The cloud industry is booming with a projected market value of $800 billion by 2025 and the potential to grow even further. This growth means a constant demand for skilled professionals making it an excellent time to enter the field. Now that we understand the industry's potential, the next question is where should you start? So you should choose a cloud provider. So choosing a cloud provider is a critical decision as it shapes your learning path and future jobs opportunities. So the three major players are AWS, Azure and Google Cloud Platform GCP. So starting with AWS. So AWS that is Amazon Web Services is often recommended for beginners because it has the largest market share and a wide range of services which translates into more job opportunities. Now coming to Azure that is another strong option especially if you're targeting jobs in enterprises that use Microsoft technologies. Now coming to GCP that is Google cloud platform and it is gaining popularity and offers excellent features especially in data analytics and machine learning. For beginners, AWS is popular choice due to its widespread use and extensive documentation. However, it's important to research the demand in your local job market and consider your own interest when making a decision. And with the cloud provider chosen, the next step is to build a strong foundation in the fundamental technologies that underpin cloud computing. So now before diving into cloud specific services, it's essential to understand the foundational technologies that cloud computing relies on. These include number one comes networking. So understanding how data moves across networks is crucial for setting up and managing cloud infrastructure. Then comes operating systems. Familiarity with operating systems particularly Linux is essential as most cloud environments run on Linux servers. Then comes virtualization. So this is the process of creating virtual instances of physical hardware. That's a core concept in cloud computing. And then comes databases. So knowledge of databases both relational and non-reational is critical for managing data in the cloud. So with these foundational skills in place you are now ready to explore cloudspecific learning paths. So let's start with certifications. So certifications can validate your knowledge and make you stand out in the job market. For AWS starting with the AWS cloud practitioner certification is advisable. This certification provides a broad overview of cloud concepts and AWS services. It covers key areas such as compute services, storage options, security measures, networking capabilities and billing and pricing structures. Now coming back while certifications are valuable they need to be complemented with practical hands-on experience to truly demonstrate your skills. Here comes building projects or hands-on practice. So building projects is the most effective way to apply what you have learned and to demonstrate your abilities to potential employers. So here are a few beginner friendly projects to consider. Number one is setting up virtual machines. So start by launching an EC2 instance on AWS. Learn about the different instance types, configurations and the basics of server management. Then comes the next project that is cloud storage systems. So experiment with services like S3 for object storage and RDS for relational databases. Document the use cases and differences between these services. Then deploy a web application. Host a static website using S3 and CloudFront which will teach you about web hosting, content delivery and the basics of DNS management with route 53. Initially you can use the AWS console for these task but as you progress try implementing these projects using infrastructure as code tools like Teraphform. This approach not only deepens your understanding but also aligns with industry best practices. In addition to practical projects, having some coding knowledge can greatly enhance your capabilities as a cloud engineer. So now we'll see how you can learn to code. While not always mandatory, coding skills can significantly enhance your effectiveness as a cloud engineer. Languages like Python and Bash are particularly useful for scripting and automation. Even a basic understanding can help with tasks such as writing scripts or server automation, managing cloud services or resources programmatically, then implementing infrastructure as code. For those new to coding, check out simply learn videos on YouTube, which offers excellent starting points. Coding skills not only make you more versatile, but also open up opportunities to specialize in areas like DevOps or cloudnative development. And once you have built your skills and some projects, it's time to start with the job hunting process. That is building your profile. Creating a strong online presence is crucial when job hunting. Your LinkedIn profile should clearly reflect your new skills, certifications, and projects. So here are some tips. Number one is optimize your LinkedIn profile. That is include a professional photo and engaging summary and detailed description of your projects. Then comes network actively. Connect with professionals in the field. Join cloud computing groups and participate in discussions. And then comes apply strategically. Tailor your resume for each job application, highlighting the skills and projects that align with the job description. Applying for jobs can be a number game. So be persistent. It's also helpful to reach out to recruiters or hiring managers directly to express your interest in the role. As you start to gain experience in your first cloud role, consider specializing in a niche area to advance your career. And then comes specializing and continuous learning. So specializing in a particular area of cloud computing can make you more valuable and increase your earning potential. Possible specializations include DevOps that is it focus on automation, continuous integration and continuous deployment practices. Then comes serverless computing work with functions as a service that is FAS and other serverless architectures. And then comes security. specialize in cloud security to protect data and infrastructure. The cloud industry is dynamic with new tools and technologies emerging regularly. So continuous learning is key. So stay updated through online courses, webinars and industry news. Finally, remember that the journey into cloud engineering is continuous and ever evolving. So if we talk about resources, so embarking on a career in cloud engineering is challenging but highly rewarding. Utilize free resources like YouTube tutorials, community forums, and documentation to guide your learning. Let's now take a look at some individual features of S3. Starting off with life cycle management. So life cycle management is very interesting because it allows us to come up with a predefined rule that will help us automate the transitioning of objects from one storage class to another without us having to manually copy things over. Of course you could imagine how timeconuming that would be if we had to do this manually. So we're going to see this very soon in a lab. However, let me discuss how uh how this works. So once we uh it's basically a graphical user interface. It's very very simple to use once you come up with these uh life cycle management rules. But you're going to define two things. You're going to define the transition action and the expiration action. So the transition action is going to be something like well I want to transition an object from maybe it's all objects or maybe it's just a specific type of object in a folder example that has a specific prefix from one storage class. let's say standard to standard inactive or infrequent access maybe only after 45 days after at least a minimum of 30 days like we spoke of before and then maybe after uh 90 days you want to transition the objects in IIA to right away glacier deep archive or 180 days you come up with whatever combination you see fit okay it doesn't have to be sequential from S3 to IIA to one zone etc etc Because like we discussed before, it depends what kind of objects that you're interested in putting in one zone. Objects that you don't really mind losing if that one availability zone goes down. So you're going to be deciding those rules. It ends up that this even is not a simple task because you have to monitor your usage patterns to see which data is hot, which data is cold and what's the best kind of life cycle management to implement to reap the benefits of the lowest cost. So you have to put somebody on this job and make the best informed uh decisions based on your access patterns and that is something that you need to consistently monitor. So what we can do is we can instead opt for something called S3 intelligent tiering which basically analyzes your workload using machine learning algorithms. And after about a good 30 days of analyzing your access patterns will automatically be able to transition your objects from S3 standard to S3 standard infrequent access. Okay? It doesn't go past the IIA1. doesn't go after the glacier and whatnot. Okay. So, it can then offer you um that at a reduced um price overhead. So, there is a monitoring fee that is introduced in order to uh implement this feature. It's a very nominal, very very low monitoring fee. And the nice thing is is if ever you take out an object out of the infrequent access before the 30-day limit as we spoke of before, you will not be charged um an overhead charge because of that. Why? Because you're using the intelligent taring. You're already paying an overhead for the monitoring fee. So at least in that sense the intelligent tearing will take the object out of IIA and put it back into the S3 standard class if you need access to it before the 30 days and in that case you won't be charged that overhead. So that is something that is very um that is very um good to to to do in order not to have to put somebody on that job. So yes, you're paying a little bit of overhead for that monitoring fee, but at the other side of the spectrum, you're not investing in somebody uh working many hours to monitor and put into place a system to monitor your uh data access patterns. So let's take a look at how to do this right now. Let's implement our own life cycle management rules. So let's now create a life cycle rule inside our bucket. First off, we're going to need to go to the management tab in the bucket that we just created. And right on the top, you see right away life cycle rule. We're going to create life cycle rule. And we're going to name it. So, I'm just going to say something very uh simple like simply learn uh life cycle rule. And we have the option of creating this rule for every single object in the bucket or we can limit the scope to a certain type of file perhaps with a prefix like I could see one right now something like log. So anything that we categorize as a log file will transition from one storage tier to the next as per our instructions. We're doing this because we really want to save on costs, right? It's not so much of organizing what's your older data versus your newer data. It's more about reducing that storage cost as your objects get less and less used. So in this case, logs are a good fit because perhaps you're using your logs for the first 30 days. You're sifting through them. Um you're trying to get insights on them, but then you kind of move them out of the way because they become old data and you don't need them anymore. So, we're going to see how we can uh transition them to another pricing tier, another storage tier. Uh we could also do this with object tags, which is a very powerful feature. And in the life cycle rules action, you have to at least pick one of these options. Now, since we haven't enabled versioning yet, what I'm going to do is just select transition the current version of the object between these storage classes. So as a reminder of what we already covered in the slides, our storage classes are right over here. So the one that's missing is obviously the default standard storage class, which all objects are placed in by default. So what we're going to say is this. We want our objects that are in the default standard storage class to go to the standard inactive access storage class after 30 days. And that'll give us a nice discount on those objects being stored. Then we want to add another transition. And let's say we want to transition them to Glacier after 90 days. And then as a big finale, we want to go to Glacier deep archive. You can see the rest are grayed out. Wouldn't make sense to go back. And maybe after 180 days, we want to go there. Okay. Now, there's a little bit of um a warning or call to attention here. They're saying if you're going to store very small files um into Glacier, not a great idea. There's an overhead in terms of metadata that's added and also there's an additional cost associated with storing small files in Glacier. So, we're just going to acknowledge that. Of course, for the demonstration, that's fine. In real life, you'd want to store very big tar files or zip files that had, you know, one or more lock files in there. Okay, that would bypass that that search charge that you would get. And over here you have the timeline summary of everything we selected up above. So we have here after 30 days the standard inactive access, after 90 days glacier, and after 180 days glacier deep archive. So let's go and create that rule. All right. So we see that the rule is already enabled and at any time you could go back and disable this if ever you had um a reason to do so. We can easily delete it as well or view the details and and edit it as well. So if we go back to our bucket now what I've done is created that prefix with the slash logs. Since we're not doing this from the command line, we're going to create a logs folder over here that will fit that prefix. So, I'm going to create logs, create folder, and now we're going to upload our, let's say, Apache log files in here. So, we're going to upload one demonstration Apache log file that I've created with just one line in there, of course, just for demonstration purposes. We're going to upload that. And now we have we're going just close that. And now we have our our Apache log file in there. So what's going to happen because we have that life cycle rule in place after 30 days anything any file that has the logs prefix or basically is placed inside this folder will be transitioned as per that life cycle role policy that we just created. So congratulations you just created your first S3 life cycle rule policy. Let's now move over to bucket policies. So bucket policies are going to allow or deny access to not only the bucket itself but the objects within those buckets to either specific users or other services that are inside the AWS network. Now these policies fall under the category of IM policy. So IM stands for identity and access management and this is a whole other topic that deals with security at large. So there are no services in AWS which are allowed to access other services or data for example within S3 without you explicitly allowing it through these IM policies. So one of the ways we do that is by attaching one of these policies which are written in a JSON format. So it's a text file that we write at the end of the day. That's the artifact and that's a good thing because we can use that artifact and we can configuration control it in our source control and version it and put it alongside our source code. So when we deploy everything, it is part of our deployment package. So in this case here we have several ways of doing this. We can use what's called the policy generator, which is a graphical user interface that allows us to simply click and point and populate certain text boxes, which will then generate that JSON document that will allow us to attach that to our S3 bucket. And that will determine like I said which users or services have access to uh whatever API actions are available for that resource. So we might say we want certain users to be able just to list the contents of this bucket, not necessarily be able to delete or upload new objects into that bucket. So you can get very fine grained permissions based on the kind of actions you want to allow on this resource. So in order to really bring this home, let's go and perform our very own lab on this. Let's now see how to create an S3 bucket policy. Going back to our bucket, we're now going to go into permissions. So the whole point of coming up with a bucket policy is that we want to control who or what the what being other services have access to our bucket and our objects within our bucket. So there are several ways we can go about doing this. Let's edit a bucket policy. One, we can go and look at a whole bunch of pre-anned examples, which is a good thing to do. two, we could actually go in here and code the JSON document ourselves, which is much more difficult, of course. So, what we're going to do is we're going to look at a policy generator, which is really a formbbased graphical user interface that allows us to generate through the answers that we're going to give here the JSON document for us. First question is we got to select the policy type. Of course, we're dealing with S3, so it would make sense for us to create an S3 bucket policy. The two options available to us are allowing or denying access to our S3 bucket. Now, in this case here, we could get really um fine grained and specify certain kinds of services or certain kinds of users, but for the demonstration, we're just going to select star, which means anything or anybody can access this S3 bucket. All right. Now, depending on uh also the actions that we're going to allow. So in this case here we can get very fine grained and we have all these check boxes that we can check off to give access to certain kind of API action. So we can say we want to give access to you know just deleting the bucket which obviously is something very powerful. Uh but you can get more fine grain as you can see you have more of the getters over here. Um and you have more of the the the listing and the putting new objects in there as well. So you can get very fine grain. Now for demonstration purposes we're going to say all action. So this is a very broad and wide ranging permission something that you really should think twice about before doing. We're basically saying we want to allow everybody and anything any service all API actions on this S3 bucket. So that's no uh small thing. We need to specify the Amazon resource name the ARN of that bucket specifically. So what we're going to do is go back to our bucket and you can see here uh the bucket ARN. Okay. So we're just going to copy this, paste it in this policy generator and just say add statement. You can see here kind of a resume of what we just did. And we're going to say generate policy. And this is where it creates for us. And make this a little bit bigger for us. It creates that JSON document. So, we're going to take this, we're going to copy it, and we're going to paste it into the generator. Okay. Now, of course, we could flip this and change this to a deny, right? Which would basically say we don't want anybody to have access or any thing, any other service to have access to this S3 bucket. We could even say slashstar to also encapsulate all the objects within that bucket. So if I save this right now, you have a very ironclad S3 bucket policy which basically denies all access to uh this bucket and the objects within. Of course, this is on the other side of the spectrum very very secure. So we might want to for example host a static website through our S3 bucket. So in this case here allowing access would make more sense, right? So if I save changes, you see that we get an error here saying that we don't have permissions to do this. And the reason for that is because it realizes that this is extremely permissive. So in order to give access to every single object within this bucket, as in the case that I was stating of a static website being hosted on your S3 bucket, it would be much better to also at first enable that option. So I'm just going to duplicate the tab here. And once you go back to the permissions tab, one of the first things that shows up is this block block public access setting. Right? Right now it's completely blocked. And that's what's stopping us from saving our policy. We would have to go in here, unblock it, and save it. Right? And it's also kind of like a double clutch feature. You have to confirm that just so you don't do that by accident. Right? So now what you've effectively done is you've really opened up the floodgates to have public access to this bucket. It's something that can't be accidentally done. It's kind of like having to perform these two actions before the public access can be granted. Now, historically, this was something that AWS was um was guilty of was making it too easy to have public access. So, now we have this double clutch. Now that this is enabled or turned off, we can now save our changes here successfully. And you could see here that now it's publicly accessible, which is a big red flag that perhaps this is not something that you're interested in doing. Now, if you're hosting a public website and you want everybody just to have read access to every single object in your bucket, yes, this is fine. However, please make sure that you um pay very close attention to this uh type of access flagged over here on the console. So, congratulations. You just got introduced to your first bucket policy, a permissive one, but at least now you know how to go through that graphical user interface through the policy generator and create them and paste them inside your S3 bucket policy uh pane. So let's continue on with data encryption. So any data that you place in S3 bucket can be encrypted at rest very easily using an AES 256 encryption key. So we can have server side encryption. We could have AWS handle all the encryption for us and the decryption will also be handled by AWS when we request our objects later on. But we could also have client side encryption where we the client that are uploading the object have to be responsible for also passing over our own generated key that will eventually be used by AWS to then encrypt that object on the bucket side. Of course, once that happens, then the key is discarded. the client key is discarded and you have to be very mindful that since you've decided to handle your own encryption client side encryption that if ever you lose those keys well that data is not going to be recoverable in that bucket on the AWS network. So be very careful on that point. We can also have a very useful feature called versioning which will allow you to have a history of all the changes of an object over time. So versioning sounds exactly how it's named. Every time you make a modification to a file and upload that new version to S3, it will have a brand new version ID associated with that. So over time you get a sort of stack of a history of all the file changes over time. So you can see here at the bottom you have an ID with all these ones and then an ID with one 121212. So eventually if ever you wanted to revert back to a previous version, you could do so by uh accessing one of those previous versions. Of course versioning is not an option that's enabled by default. you have to go ahead and enable that yourself. It is an extremely simple thing to do. And so there may be a situation where you already have objects within your buckets and you only then enable versioning. Well, versioning would only apply to the new objects that would get uploaded from the point that you enabled versioning. the objects that were there before that point will not get a specific version number attached. In fact, they will have a sort of null marker um version number that will get attached to them. It's only after that you modify those objects later on and upload a new version that they will get their own version numbers. So, right now, what we're going to be doing is a lab on actual uh versioning. So let's go ahead and do that right now. In this lab, we're going to see how to enable versioning in our buckets. Enable versioning is very easy. We're simply going to click on our bucket, go into properties, and there is going to be a bucket versioning section. Going to click on edit and enable it. Once that's done, any new objects that are uploaded to that S3 bucket will now benefit from being tracked by a version number. So if you upload objects with the same file name after that, they'll each have a different version number. So you'll have version tracking, a history of the changes for that object. Let's actually go there and upload a new file. I'll upload one called index.html. So, we're going to simulate a situation where we've decided we're going to use an S3 bucket as the source of our static website to deploy one. And in this index.html file, if you take a look uh right now, let's take a look at what's in there. You can see that we have welcome to my website and we're at version two. Okay. So if I click on this file right now and I go to versions, I can clearly see that there's some version activity that's happening here. Okay, we have here um at 1456 which is the latest one. The latest one is on the top, the current version, we have a specific version ID and then we have a sort of history of what's going on here. Now, I purposely enabled versioning before and then try to delete versioning or disable versioning. But here's the thing with versioning. You cannot disable it fully once it's enabled. You can only suspend it. Right now, suspending means that whatever version numbers those objects had before you decided to suspend it will remain. So you can see I have an older version here that has an older version number. And at this point here, I decided to suspend versioning. And so what it does instead of disabling the entire history, it puts what's called a delete marker. Okay, you could always roll back to that version if you want. Now in the demonstration when we started it together, I enabled it again. So you can see this is actually the brand new version number as we did it together but you don't lose the history of previous versioning if ever you had suspended it before. So that's something to keep in mind right and it'll come up in the exam where they'll ask you can you actually disable versioning once it's enabled and the answer is no you can only suspend it and your history is still maintained. Now we have that version there and let's say I come to this file and I want to upgrade this I don't know I say version three right and now what's going to happen is if I click on this version just as the current one with version two and I open this we should see version two which is fine that's that's that's expected if we go back to our bucket and upload that new version file that has version three in there, the one I just modified. We should now see in that index.html file a brand new version that was created under the versions tab. And there you go. 1458 just 2 minutes after. You can see here we have a brand new version ID, right? And if I open this one, you can see version three. So now you have a way to enable versioning very easily in your buckets and you also have seen what happens when you want to suspend versioning. What happens to the history of those versions files before just to actually go back here to the properties uh where we enabled versioning in the first place. If I want to go back in here and disable it, like I said, you can't disable. You could only suspend. And that's where that delete marker gets placed, but all your previous versions retain their version ID. So don't forget that because that will definitely be a question on your exam if you're interested in taking the certification exam. So congratulations, you just learned how to enable versioning. Let's move on to cross region replication or CRR as it is known. There will be many times when you find yourself with objects in a bucket and you want to share those objects with another bucket. Now that other bucket could be within the same account, could be within another account within the same region, or could be within a separate account in a different region. So there's varying levels of degree there. The good thing is is all of those um combinations are available. So CRR if we're talking about cross region replication is really about replicating objects across regions something that is not enabled by default because that will incur a replication charge because it's syncing objects across regions. Of course you are spanning a very wide area network in that case. So there is a search charge for that. Now doing so is quite simple to do. But one of the things that we have to be mindful of is to give permissions for the source bucket which has the originals to allow for this copying of objects to the destination bucket. So if we're doing this across regions of course we would have to come up with IM policies and we would also have to exchange credentials in terms of uh IM user credentials in terms of account ids and and the such. Um, we're going to be doing a demonstration in the same account in the same region, but largely this would be the same steps if we were going to go cross region. So, this is something you might find yourself doing if you want to share data with other um entities in your company. Maybe you're a multinational and you want to uh have all your lock files copied over to another bucket in another region for another team to analyze to extract business insights from. Or it might just be that you want to aggregate data in a separate data lake in an S3 bucket in another region or in like I said it could be even in the same region or in the same account. So it's all about organizing moving data around across objects across these boundaries and let's actually go through a demonstration and see how we can do CRR. Let's now see how we can perform cross region replication. We're going to take all the new objects that are going to be uploaded in the SimplyLearn S3 demo bucket and we're going to replicate them into a destination bucket. So, what we're first going to do is create a new bucket. Okay? And we'll just tack on the number two here. And this will be our destination bucket where all those objects will be replicated to. We're going to demonstrate this within the same account, but it's the exact same steps when doing this across regions. One of the requirements when performing cross region replication is to enable versioning. So if you don't do this, you can do it at a later time, but it is necessary to enable it at some point in time before coming up with a cross region replication rule. All right, so let me create that bucket. And now after the bucket is created, I want to go to the source bucket and I want to configure under the management tab here a replication rule. So I'm going to create a replication rule call it simply learn rule and I'm going to enable this right off the bat. The source bucket of course is the SimplyLearn S3 demo. We could apply this to all objects in the bucket or perform a filter. Once again, let's keep it simple this time and apply to all objects in the bucket. Of course, caveat here. This will only now apply to any new objects that are uploaded into this source bucket and not the ones that are already pre-existing there. Okay. Now in terms of the a destination bucket, we want to select the one we just created. So we can choose a bucket in this account or if we really want to go cross region or another account in another region, we could specify this and put in the account ID and the bucket name in that other account. So we're going to stay in the same account. We're going to browse and select the newly created bucket. And we're also going to need permissions for the source bucket to dump those objects into the destination bucket. So we can either create the role ahead of time or we can ask this user interface to create a new role for us. So we'll opt for that and we'll skip these additional uh features over here that we're not going to talk about in this demonstration. We're just going to save this. So that will create our replication rule that is automatically enabled for us right now. So let's take a look at the overview here. You can see it's been enabled. Just to double check, the destination bucket is the demo 2. We're talking about the same region. And again here we could opt for additional um parameters like different storage classes in the destination bucket that that object is going to be deposited in etc etc. For now we just created a simple rule. Now if we go back to the original source bucket which we're in right now and we upload a new file which will be transactions file in a CSV format. Once this is uploaded that cross region replication rule will kick in and will eventually right it's not immediate but we'll eventually copy the file inside the demo 2 bucket. Now I know it's not there already. So what I'm going to do is pause the video and come back in 2 minut