Cloud Computing and DevOps Course | Cloud DevOps Tutorial | Cloud and DevOps Training | Simplilearn

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[Music] Looking for a tech career that's fast growing, highpaying, and super exciting? Then this cloud and DevOps full course is just for you. The world is moving to the cloud and businesses everywhere are adopting DevOps to build, launch, and scale software faster than ever before. That's why cloud and DevOp professionals are among the top most in demand experts today with salaries ranging from $80,000 to $150,000 plus depending on skills and experience. In this course, we will start with the basics of cloud computing, what it is, why it matters, and how companies use platforms like AWS, Azure, and Google Cloud to run their operations. Then we will dive into DevOps fundamentals, understanding how development and operations come together to speed up software delivery. You'll also learn powerful tools like Docker, Kubernetes, Genkins, and Terraform. And also explore cloud security, automation, CI/CD pipelines, and monitoring. And the best part is you won't just learn theory. You'll get to work on hands-on projects, real world use cases, and stepbystep guidance to build practical skills. And by the end of this course, you'll have the confidence to pursue cloud and DevOp roles, crack top certifications, and land highpaying jobs in this booming industry. So, let's get started. Your future in cloud and DevOps begin right here. Before we move on, just a quick information. If you're looking to futureproof your tech career, this professional certificate program in cloud computing and DevOps by ENIC Academy, IT Goard is the perfect choice for you. Within 8 months, you'll gain hands-on expertise across AWS, Azure, and Google Cloud. You can master DevOp tools like Genkins, Docker, Kubernetes, and work on 30 plus real world projects. What makes this program stand out is you'll get official Azure certifications, IIT GE issued credentials, access to live master classes, and even a campus immersion opportunity. Plus, with AI powered job assistance, resume building and interview preparation, you are set up for real career growth. Whether you're upskilling or making a career switch, this program offers everything you need to thrive in the world of cloud and DevOps space. You can find the link below. >> 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 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 containerrest service. 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 code start 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 are EMR and which is elastic map produce and cloud search. 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. There 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, it's 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. It 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 addressed 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 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 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 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 Dynamob is the service that this application uses to store data. There's my Dynamob. And if I go to tables, all 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. All 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. And 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 their 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 nojs 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, 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 our 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 a 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 compute 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 in 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 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 uh 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 skill 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 good 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 in 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 and 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 a 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 uh 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 uh flavors 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 Cosmod. So this Cosmod was built with global distribution in mind and it's built uh with the 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 at 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 opensource caching product which is reddis sometimes called as radius 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 Reddis 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. Now 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 uh 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 helps 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 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. And 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 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 an 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 stored Simple is really because it uses store simple 8000 series devices which are used in Azure data center and this 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 Q or a single cube message can be up to like 24 KB in size. And a single Q 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 would 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 uh 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? and 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 to 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 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 database. Give me a quick moment. Let's fix it. 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 get 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. 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 core tools like Terapform. 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. than implementing infrastructure as code. For those new to coding, check out simple 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 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. Hello, this is Matthew from SimplyLearn and today we're going to go through a complete end to end journey on what it takes to set up a DevOps team. Uh we're going to go through what um we need to be able to do to go to DevOps, what the arguments are and why you need to do DevOps. And then we'll actually go through all the individual tools you need to be able to successfully implement DevOps within your organization. In addition to that, we're also going to take time and go through each of those tools so you get a good understanding of a step-by-step instructions on how to do basic setup of each of those tools. So, let's get started. So, what was DevOps before? So, what was the process that we took for doing delivery before DevOps? Well, it was a model called waterfall. And waterfall was a very traditional approach to actually building out solutions. And the reason why it's called waterfall is that you break out all the individual requirements and individual sections of a project and they cascade off each other. So if we look at the breakdown, we have requirements design uh we have implementation, we have verification, we have maintenance, you'll have user acceptance testing and this is all based on the software development life cycle model or SDLC and it's been around for quite some time and is still used by a lot of companies today. The challenge you had with the waterfall model is that it really is a very long drawn out model for actually building and delivering solutions. So it took a very long time to actually um write code and then deploy the code. It was very difficult to actually identify problems within the code and provide feedback to the development team on what to fix. Um and this really was a very time consuming. We're talking about months, sometimes years for projects to be actually go through a warfall model process. So along came a new method of being able to do delivery and it's called agile. And the agile approach is a way of being able to take the actual work that's done in a waterfall model and compress it down into small iterations. And what we would do is a fundamental change is that you would actually take uh teams that were disparate and as part of the individual cascades within a waterfall project and you actually bring them together. So you have your requirements team person, design developer and release management team all together in one group working on an iteration. The great thing about agile is that you took a process that was weeks or months or even years in length as it was with waterfall and you reduce it down to two or 4 week sprint uh depending on the cadence for your team. Uh typically you have a twoe sprint and then the goal is is that at the end of uh each sprint or sometimes every other sprint you would do a software release and so that customers were getting the software much faster. The problem that we still ran into though with um agile is fundamentally similar to what we were having with waterfall. uh you have your DevOps person working on code on their system and it' be working great on their computer and then you have the operations person who's migrating the code from the developers environment, the test environment to the production environment and you would run into issues where the code simply wasn't work and there's a lot of reasons why that would happen. Uh the actual developer environment would often be very different or would have different dependencies in it. So the uh the hardware, the the software, there may be additional uh applications that were installed on the operating system that simply hadn't been transferred over to the operations environment. And so what you would have is a disconnect between the developer environment and the operations environment, making it difficult um to actually roll out code. So you'd run into a program where that when you rolled out code, you'd have to have a roll back plan in case the code wouldn't work in production. And so each release became an event where everybody got very stressed about the actual event of releasing code because you didn't know whether it was going to work. So Dev Ops really looks to address and solve a lot of these problems. So the key word that you'll often hear with uh DevOps is continuous integration. And what that means is essentially that as a developer is working on their code, their code is constantly being tested against not just the actual code itself with unit testing, but the environment with which it's going to be released in. And the goal from a dev ops model is that the breakdown of communication that happens with waterfall and agile where dev developers and operations teams aren't working in the same environment is being removed and you're able to provide a continuous and contiguous um environment uh between the developer and the actual operating model. So the reality is when the developer is working on their code, they're actually working in an environment that is identical to the production environment. And so when the actual operations person comes to actually do releases for the code and you can see some teams are doing as many as 20 to even up to 50 releases to production environments every single day. you're able to guarantee that the actual code itself will work and releases go from being a stressful event to a byproduct of good testing and good setup and structure for how you actually build out your solutions. So what we're seeing here so the goal is that as a developer and as an operations person that the code is working continuously in both environments. You have continuous integration and continuous delivery. So simply put, what we're able to do is we're able to eliminate the problem of the operation environment not being in sync with the development environment. And this is a an improvement on agile. This is not to say that waterfall or agile are wrong as delivery models. What it is is just a maturity of the ability to deliver solutions and DevOps is just another rung in that maturity curve using tools that are available to us now that 5 10 years ago simply weren't available. So the goal is for you as a team to move to a dev ops model where you can implement continuous releases on your software as long as you're using the tools that are available. And the good news is those tools are open-source tools. So let's go through some of the benefits of why you'd want to go um and use DevOps. So you know essentially what's in it for you. So let's over the next few slides we're going to go through what is DevOps. We're going to go through the benefits of DevOps. So in the last few slides you've actually seen you know what is DevOps and the benefits of DevOps along with the life cycle. But we're also going to start digging into the tools that you have that are useful for DevOps. And we're going to focus in on seven tools that can provide an end-to-end infrastructure for delivering DevOps solutions with there are significantly more tools available on the market. Uh but these are seven of the most popular uh for each of their categories. So DevOps really is an essential collaboration between the development team and the operations team. These are teams that have in past been somewhat at conflict with each other. And what you have now is an opportunity where those teams can can now work continuously with each other. The expectation with DevOps is that it will continue to mature. Indeed, you're actually even seeing some groups which are now called dev sec ops where they're integrating security as part of the delivery between the development team and the operations team. The bottom line is a DevOps engineer is highly in demand. The demand for a DevOps engineer is literally going through the roof with salaries going up exponentially around that. So let's dig into some of the benefits of DevOps. It's not just a new catchphrase. It's actually got significant value and how you can speed up delivery of your software. So the benefits of DevOps can really broken up into a number of key areas. First of all, we have continuous delivery of software which allows you to continuously release new features with the security and understanding that the software going out is of high quality. It allows the teams that are working on the software delivery within your organization to more effectively collaborate with each other so that you're all talking from the same page and understanding of what needs to be delivered. The deployment process itself moves from being an event where there's a lot of stress and there's a lot of contingency plans to being a much easier deployment. The efficiency within the actual code that you're writing and the ability to scale up using the different tools are available allows you to be able to bring in and scale up and reduce the teams you have running the software as needed. errors can be fixed much earlier and more quickly and can be caught before anything gets pushed out to the production environment. And fundamentally what we're looking for is improving the security of the actual releases. So the actual concept of security is center to all the work you're doing. And then finally what really allows you to uh reduce the number of errors is that there is much less manual intervention. there is a greater reliance on scripted environments that you can actually test and validate for their security reliability and uptime efficiency. So let's talk a little bit about the life cycle of a devops. So the very first step that you'll take is to actually build out a build and test environment and this is a continuous build and test environment and this is managed with the first step of your source code. Once you move through that and you're looking at continuous integration, which means that every time somebody checks in their code, they're validating that the code actually can run in the production environment. Once you've actually then passed the continuous integration and the testing that you have with your code, you're looking at continuous deployment. If the code works and is available to be released into the production environment, let's go ahead and release it. And once you actually have release code, then you want to be able to validate that your environment is working efficiently. You may release code that is a new feature within your application and customers may then gravitate immediately to that new feature. If they do, you want to be able to ensure that the code is working and more importantly that the infrastructure is there to support. And then finally, you're looking at software released um as a continuous event. And then you go back to the beginning. You start working on more code. You run it through your build environment and continuous integration, deployment, continuous monitoring, and keep that cycle moving. So let's dig into the tools that you as a DevOps engineer would need to learn. If we break down the environment that we have all the way from source code management to software release, there are a number of key tools that you want to be able to use. So for instance, source code management git is an open-source tool that you would want to use for managing your code. The continuous build and test environment would be managed with Maven and Selenium. Integration with the environments that you're working on is managed through Jenkins. The actual deployment to your production environment would be managed with products such as Anible and Docker. And then the monitoring of your network would be used with tools like Negios. The thing that you have to remember with all these tools is that they're open-source tools. There is no licensing that you have to uh purchase. Uh some of the tools will have prolevel licensing that you can choose um to select. But to get started, all of these are open- source tools you can actually start using for free right now. So let's dig into Git. So let's look at the the challenge that Git is able to address. So before git and you if you had a team of developers that were working on different pieces of code, one of the key problems you have is that there was no collaboration between the team. And the the challenge you have is that with version control it was difficult and often required um having to check in to a large environment or you had very you know quasi version control environments. It was time consuming. Often there were problems that what would happen if this the uh version control server would crash and there wasn't a backup. Then you'd have to kind of essentially go back to square zero uh to see whether or not you actually had to do the work again. So let's look at what git does to actually solve this. So first of all, one of the things that um git does is it makes team collaboration much easier. The software itself is more effectively documented and more and more effectively maintained. the actual code that actually gets worked on by each developer in a git environment is the complete code. So it makes it much easier for backups and for sharing uh content amongst each um developer. So the way in which git is able to accomplish this is that it is essentially a distributed version control um solution. Um, and what that means is that when you have multiple developers, yes, you do have a git remote hub that you connect and uh are able to upload and download uh different branches of the code that you're working on. But essentially as a developer when you um actually have the code, you actually have all of the code and uh you're able to uh manage it directly from your local PC or your local development machine um without having to uh worry too much about the network or the server actually going down. So some of the key things in which um git is really good at it is you know a software management tool. It's designed from the ground up to manage code development. It does track the changes on that code easily and effectively. It makes it easy for you as a developer to track your code. The ability for multiple developers to work together is much easier in comparison to um other solutions. And and this is really the the key success point with Git is that it allows for nonlinear code development. So you can actually have people working on different areas of the code that may be released at different times because of what they're working on. So if we actually break down the architecture of git, it really falls into four key areas of a working directory, a local staging area, a local repository and a remote repository. So the process you would go through is you would add files to this um staging area from your working directory. And this would be use the get add command. And then from your staging area when you're ready to actually then commit those files to a local repository, you would use the git commit command. And then from there you would actually then push your local repository out to the remote repository uh for a final commit uh to the remote repository. Um and this allows then the rest of the team to pull down your latest final changes. So you can be working on your code locally and you can be using your local local staging area, local repository and and when you're ready to commit your work, you can commit it and then as soon as it's committed, the rest of the team can then pull down the latest changes that you have worked on. And this allows for a complete and holistic checkout and checkin process. And then sometimes you want to be able to go through and then take the checked out code that you um that you're pulling out and merge it with your local code. And the merge process always ensures that uh you are working on the latest and best version of the code and everybody on the team is being consistent with the uh communication of the actual code that's being delivered. Okay. So what we're going to do is we're going to validate that we have git running on our computer. We're going to then create a directory, add a file to that directory, make some changes to that file, and then use the commit commands to be able to check in the files and validate changes that have been made. So, first thing we do is we're going to see if we have git um installed. And to do that, you just use the command git version and what you'll sorry, git- version. And they'll actually then give you the version number. And now we're going to create a new folder. So, mk dur green. And that'll create a new folder. and we'll move our cursor into the green folder by changing the directory. And we can go back into Windows and we can validate that that directory is actually there. So here we go. Let's have a look. We should see it. There's the green folder. If I double click into that, you'll see there's nothing in the folder right now. So what we have to do is we actually have to add the folder as part of a git project. And so we're going to use our git initiate in it. And that will actually initialize the folder and make it a git repository. And so let's go ahead and create a file that'll actually go inside of um that uh new initialized folder. And you'll see that there's a git folder that's been added. So the new text file we're going to create is going to be called class. And it'll actually be class.txt. The extension is hidden by default. In the uh text file, we're just going to type in the text uh welcome to SimplyLearn and save that. Now let's go ahead and check the status um of that file in Git. So let's do get status and you'll see that it says yes, there's a file there, but it hasn't been committed to the repository. That's why it's in red. So what we have to do now is commit the file to the repository and it won't be able to track any changes that we do to that file. So let's go ahead and commit the file. So we do commit add class.txt and they'll add that to the repository. And there we are. It's added. And the final step is we want to do is commit it. And let's do get. So let's do get commit-m put in this will be our first commit and this is the description and so it actually shows us committing the file. It's the only item in the folder. So now we can go over to the file that we just created and we can make some changes to it. So let's open up the file. So it says welcome to simply learn. Uh let's put in some text afterwards that says this is my demo. And we'll save that. Close that. And now if we go back to git, we can do a compare and contrast between the original file that we committed and the new um updates that we've just done. And we can check the difference by using git diff. And what you'll see is the uh red text was the original text and the green text is now the new text that's been added. And so that shows you how you can actually go and create a um a new git repository, go through adding files, committing the files into the repository, and being able to see the different version controls. Let's move on to Maven. So why use Maven? So, so why use Maven? Well, let's look at some of the things that you would have done in the past if you actually building out the tasks. So let's break down what you would have done before using Maven. If you were to create a game of football using Java, you would actually have to go out and for your actual um game, you'd have to collect all the different components needed within the Java environment uh to make sure that everything would work correctly and if you make the slightest mistake, uh you wouldn't get the right output that you needed. The actual process of building and deploying a project really would take quite a lot of time. After Maven, Maven allows you to be able to take templates that are stored locally and be able to use those to be able to improve the efficiency of being able to build out your environment by removing dependencies within the application. It makes it a lot easier for you to be able to focus on just writing the code for your game or your solution rather than having to manage the environment within which that solution would be deployed. Now the focus within Maven is that it is an automation tool and it's used for projects that have a short period of time. So as you're starting on your environment for building out um solutions, Maven is great to get started with and then if you need to have longerterm projects then you can look at other alternative tools on the market. So, four key areas that you want to focus on and why Maven can help you is that it does allow for efficient um parallel builds to be run concurrently. It's really easy to use. You can get up and started with Maven very quickly. Uh you do have fast access to new features and new configurations quickly within your environment and the build process that allow you to be able to visualize your code happens very quickly. The actual architecture of Maven is that the execution and commands are managed through what's known as a pom file. The pom file itself is a project object model and it's an XML file that actually has the details for the project and the configuration for the build environment. Pom file itself will then fetch dependencies from the local repository and will apply any plugins that you may have also included within your Maven environment. The goal is that your software is built much more controlled manner. So what we're going to do now is we're going to show you how to go through and run your very first project using Maven. The first steps you're going to have to do is make sure that you have the latest JDK installed on your computer. So we're going to go ahead and open up our web browser and get this installed on your computer. So, we're going to type in JDK download into our Chrome web browser and go to the Oracle website, which allows us to download the JDK. And because we're running this on Windows, we're going to download the Windows version of the JDK. And once you have that installed, so the next step is to actually then go ahead and download the Maven files. So, it's going to take us to the mavenapache.org org website where you can actually go ahead and download the version of Maven that you need for your operating system. We're going to go ahead and download the zip file instead of just an executable file. This will give you more control over how you install it onto your Windows PC. After the file has been downloaded, we want to go ahead and extract the entire um file so you have uh the unzipped folder running on your computer. So, one of the things that we're going to have to do is go through and set a number of system variables for the JDK and for the path to your Maven files. And to do that, you want to go into your control panel and select the system security and then system settings and then go into advanced system settings. This will give you access to the uh edit system variable setting that you're looking for. So, we're going to go down to the path variable, and you'll see already that we have pasted in the link to the JDK uh right there underneath the variable value. If you've installed the JDK, it's likely that it's already installed this path for you correctly. The good news is it's actually fairly easy to uh install the path to Maven and to the JDK because all you have to do is copy the path for where the folder is located on your system and just paste it into a variable value under the edit systems variable fold um file system. And that should now get us all the files. And you can see that we have our extracted folder already on our desktop there. And the system path is now um set to where the Maven folder is located. So we also have to go into system protection and set the system path to your Maven folder. Now we have to go ahead and do a user variable that also part links to the path of the Maven files. So what we're doing right now is we're just validating that all the files have been extracted correctly. They have which is good. We can now go ahead and link to this M folder. All right. So now what we're going to do is we're going to move over to command prompt. This is where we're going to do most of our work from here on out. First command we're going to do is uh mv. So we're going to go ahead and create a new user variable and uh we're going to type in we're going to call this one m2 dash and then we'll put in the path uh to the Apache Maven folder. You should be able to use m2-home uh for your project, but if it's not, you can always use the variable name maven-home and that will do exactly the same as uh m2. We're going to do both here uh just so we have a backup. So, we're going to open up command prompt and we're going to see if Maven is installed. We do that by writing mvn- version. And here we are. Yes. So now we're going to go ahead and create our first Maven project. And the first part of creating the Maven project is actually the directory in which we will store the files that will be used to create for our project. So we're just going to go ahead into the folder and we're going to create a new directory and we're going to call this one and we're going to call it simply learn. And we can just copy the path for that. So I'm going to write this the uh correct path for us. So we're going to change directory CD and copy the file location over. All right, we are now moved ourselves over to the simply learn folder and we'll be able to install the pom file which is what all the instructions for Maven are stored in uh into this area. So to do that, we're actually going to use a template that's already been created by Maven. And this is going to be the MVN archetype template. And so you just do mm archetype colon generate and this will go ahead and create all the files for us. So there can be quite a few files and they're all being downloaded from the Maven website. Uh so it can take some time but as you see we've gone ahead and all the files have downloaded and we have everything up and running correctly inside of our environment on command line and command prompt. So we'll have some values that we do have to set. The first one is group ID and we're going to call this one com.mav. And then the next one is going to be artifact ID and this is going to be mav mav- project. Hit return and then version is going to be 1.0- snapshot. We'll just put in the same value for this version be 1.0- snapshot. And the package we're going to type call this one com.mmav.demo. And then we'll select yes or w toh create the environment and it will build the environment for us. And what we have now is we have this screen which shows everything is up and running for us. And we have a successful build. And so let's go into the maven folder and just see there we have our simply folder. Let's open up and see what's in there. So we double click into that directory. Yep. And there we are starting to see some of our files. So, it's um the same project names there as mav- project. And then we have our pom file that's in there, which is fantastic. Under the source folder, we'll actually see the uh the demo and we have our app under the demo app. We have our test file as well. So, in the main folder, we have a file that's called the pom file. And that really is the most important file that you need for your project. You'll now go in, you'll be able to set all your settings inside of that pong file. But that's it. That's what we have done here is we've gone through and we've gone through all the setup that allows you to uh make sure you have the right files running on your computer, the right files to download from the Maven website, how to install all the files, the settings you need to make on your Windows computer, and then all the settings that need to be done in the command line to be able to run the application. And then from here you can actually start running Maven. Now let's look at selenium as we get start looking at testing. So before selenium if you wanted to run testing and particularly if you wanted to do sequential testing it would take up a lot of time. You'd have to run one test then the second test and then all the other tests and the actual time elapse would be quite significant. With selenium you're actually able to do parallel testing. So instead of looking at the amount of time it would take to actually run a test and run the test sequentially, the length of time to actually run your test is based on the length of the longest running test of which in this example uh the longest running test is 2 minutes. Now one of the things that you'll notice with Selenium is that its focus is on web applications. Um, and it is an open-source tool and it's really good at regression and functional testing of web applications. If you're doing a mobile application or if you're doing an IoT application, there are other uh tools you can use on the market as well. But if you are new to DevOps and you're setting up your first DevOps environment, Selenium is a great place to start. And web applications are mature and allow you to be able to test out and validate the concept of continuous testing in your environment. So, four key takeaways uh for Selenium. Um, it really is fast. I mean, for fast execution, it's highly accurate. Um, so you can always validate that what you're doing uh will work correctly and feedback can be sent straight back to the developer if their uh code doesn't pass the test. Um, allows you to script in multiple languages. Um, again, this is a great way for you to test. The focus is on web applications, but you can um test in multiple languages used for web applications and most importantly allows for parallel test execution which speeds up the whole test process significantly. Actually to break down the architecture of Selenium and what you'll find is the actual libraries that you can use for Selenium run in uh C, Java, Python, JavaScript, PHP. Uh these are the common languages used to build out web applications. The actual web driver itself is an API driver um which is fantastic because it makes it easier for you to integrate Selenium with applications through API and you can run the solution through different web browsers. The most popular being Firefox, Chrome and Edge. So to focus, the Selenium web driver codes are being used to build out the client libraries that make it um to allow you to be able to build solutions across multiple web um application environments. The web driver application interface is used to integrate with the application to make it easy for testing. The web driver service provides an immutable stateless environment that makes it very easy for you to be able to use protocols such as JSON to wire up your test environment. The driver manages communication between the browsers and the wire protocol that's used for JSON within the web browser itself. And then the actual commands are then run through the web browser for you to be able to get your results. Okay. So before we actually get into the setup of Selenium, the first things we want to do is we want to make sure that we have the right version of Java installed. And so I'm just using command window here and I'm going to type in Java. And actually what I can see now is I do have Java installed, which is fantastic. Otherwise, you'd have to go and download Java from Oracle's website. The next step is to validate that I have Eclipse installed. And I'm just typing Eclipse. And there we are. I have the Eclipse app installed. Uh you can actually download um Eclipse from the Eclipse website. The third step I want to check is to validate that I have a browser driver installed. So I'm using uh Google's Chrome um for my main browser, but you can actually go out and download the Chromium driver um and that's the actual core engine that powers Chrome. Uh interesting enough being used in the new Microsoft Edge web browser. So you can actually go and download the latest uh Chromium driver and install that. And then the final stage is to go to the Selenium website and download the JAR files themselves. So just uh do a Google search on Selenium download. And here we have the Seleniumhq.org website and it takes us straight to the download page. And we want to download the latest version. And we've gone ahead and done that already. So we have everything running. And now the next step is for us to install all of this great content. Okay, so before we actually get into the setup of Selenium, the first things we want to do is we want to make sure that we have the right version of Java installed. And so I'm just using command window here and I'm going to type in Java. And actually what I can see now is I do have Java installed, which is fantastic. Otherwise, you'd have to go and download Java from Oracle's website. The next step is to validate that I have Eclipse installed. And I'm just typing Eclipse. And there we are. I have the Eclipse app installed. You can actually download um Eclipse um from the Eclipse website. The third step I want to check is to validate that I have a browser driver installed. So I'm using uh Google's Chrome for my main browser, but you can actually go out and download the Chromium driver. Um and that's the actual core engine that powers Chrome. interesting enough being used in the new Microsoft Edge web browser. So you can actually go and download the latest uh Chromium driver and install that. And then the final stage is to go to the Selenium website and download the JAR files themselves. So just uh do a Google search on Selenium download and here we have the seleniumhq.org or website and it takes us straight to the download page and we want to download the latest version and we've gone ahead and done that already. So, we have everything running and now the next step is for us to install all of this great content. So, we're just going to go ahead and open up the Eclipse environment. And it always takes a moment to launch Eclipse. And we're going to go ahead and create a new project. And we're going to call our project XYZ. I think that should be fine. And this is just a test after all. And we're going to go ahead and create a new class file by right-clicking and select new class. And we're going to go in here and we're going to give the class file a name of simply learn. And don't see the finish button being selected. So maybe we need to select some other options here. Oh, you know, I think it could be the package name. Yeah, let me go ahead and change the package name. And I'm going to change that to QWE. QWF app. Yep. And the finish button has now been highlighted. I can select that. I can go select that and click finish. And uh we now have a test page that's up and running. But what we have to do is to validate that Selenium is actually part of the project. So to do that, we're going to go to the source to the actual source XYZ file and right click on it. And we want to validate that all the files are there correctly. And so we're going to see that we have the libraries are there. Yep, there's Selenium. If it's not there, you can select add external files and find the Selenium Java file. Select open and that would load that in there. And then you hit apply and close and that would apply it to your project. And now we can actually start writing the code part. So we're going to put this uh code in the public static void section. And the first uh command is going to be a system set property. And we want to make sure that we're configuring the web driver for Chromium correctly. So we're going to do web driver um chrome driver. And then the argument is actually going to be the full path, full network path to the Chromium driver that you have on your PC. So let's see. We have Chromium here. We want to copy that path. And so that paste that in. And then after we've pasted in the path, we have to make sure that we also put a link to the actual file that we want to execute, which is in this case is chromedriver.exe. And then we want to make sure that the web driver is pointing to the new chromedriver. And you'll notice that there's a couple of red colors on here, which means that we don't have all of the public classes imported correctly. So you can right click on that and say import the web driver and just select that real quick. And that adds the import correctly at the top of the page. And same for Chrome driver. And that's just a very quick way um when you're working in Eclipse to import additional uh files. So before we actually start our test, we want to make sure that we've actually cleared out any potential browser cookies that would be within the Chromium driver. So for that, we're actually going to go ahead and we're going to write a script that allows us to remove the cookies. So we want to do driver.mage and then delete all cookies. And the next line we're going to do is to actually have the web page that we're going to connect to open up in full screen mode. And for that to happen, we're going to go and actually use the window property, which is what I was writing before by mistake. And so this will allow us to go full screen. And now we need to pull in a web page. So we're going to get the get command. And what we're going to do is we're actually just going to pull in a web page from Amazon. Uh which I just happen to have here. So I'm just going to go to Amazon web page. And so I'm just going to copy the URL. Uh you know, just need to copy https uh www.mazon.in or.com wherever you're located. And so you can see that I've pulled in the Amazon web page. And then line 18 actually allows me to go and connect. So here we are. we have uh the Amazon web page that I'm pulling in. And then what I also want to do is I want to look for a specific ID in one of the elements and so I have the uh driver which is called find an element and that allows me to look for any element that would be on the actual page. So here we have the HTML in the console screen and I can actually then paste out an ID from the element that I want to use. So the find element is just the ID for each element and most of them have them because they need it for the JavaScript and CSS. So let's see there's quite a few IDs. So and we can select any of those. So what we have here is we have two tab search text box and then what that actually does is that finds the ID for the text box used for searching and then we're going to use the send key command which allows us to actually prefill in the search box and we're going to use the test of Puma shoes. This is a fixed string but you could actually put a variable in here if you wanted to pull strings from a database or an XML file. And then the next uh line on line 19 which shows how long we're actually going to run the actual script for the uh search which is only 10 seconds. And then once the uh 10 seconds has elapsed, we'll actually quit the script which actually closes the web browser and takes us back into our screen here. And let's test that. Make sure it's working and everything's looking good. The web browser opens, which is what we expect. It goes to Amazon. Fantastic. Um, it now actually goes to the search screen and should fill in the Puma shoes. There we go. Puma shoes. And waits 10 seconds. And it closes. And that's exactly what we were expecting. Now, you can actually change the unit of time that you would have for the actual test. So, if you wanted to see what was happening, so longer than 10 seconds, you can actually change the actual time or the actual metric. So in in this instance we got it says seconds and unit of time but you could do minutes or hours or microsconds and you can change the keyword as well. So it could be jigsaws or anything you wanted to check. But if you're actually building your own application, you want to be able to test your own data against your own application, that's where you put in that specific data. So let's look at the center the heart of um your DevOps environment and that center is with Jenkins. So before Jenkins people would uh developers would work on their code and the code would then be checked into a source repository. You would then check for any issues and then you would then send that uh code over to the operations team and there would be a delay for actually delivering software. So the actual um uh challenges developers had is that if they wanted to run any tests, they had to wait until their software was built and there was a lot of problems in providing feedback particular if you had large teams working on software who actually had the error. The actual delivery of software was often uh delayed uh because of these key problems. So after Jenkins, what we actually have is the ability to be able to streamline this whole process. The build, test, and deploy happens continuously and are able to then notify developers and the actual specific developer of any errors that are detected. Being able to speed up the delivery process much more efficiently. The focus of Jenkins is that it automates a continuous development, testing, and deployment environment. And it's opensource. Jenkins is easy to install and configure. It's been around for many years now and it is very mature. There are many plugins that you can use within Jenkins to be able to have the Jenkins product work with your environment. If there isn't a plug-in, you can actually extend via you can actually write your own plugins if a plug-in doesn't exist. So, you can actually continue and extend and invest in the Jenkins ecosystem and it can be easily distributed across multiple machines. So let's break out the architecture of Jenkins. So Jenkins starts as a remote source code repository and it then pulls out the code every time there is a commit from into the server master. The server master will then have a slave that will run on either Windows, Linux or Mac OS to be able to distribute its load across those environments. And after it's actually gone through and run its test, it'll then send out a report. The goal of the report is to communicate back to the team what has passed and what has failed the actual check-in process. Okay, so we're going to go ahead and show you how to install Jenkins on your local PC. Uh so the first thing you want to do is check that you have Java installed. So we're just going to go into our system and see whether or not we have the Java JDK installed. You can do that by going into the system properties, clicking advanced, and then environment settings. And there we are. We have Java JDK installed. And you want to just double check on the system variables to make sure that you have the Java_Home installed correctly as well. And we have that installed. And under path also make sure you have a link to the uh Java JDK as well. So we have everything installed and what we're going to do is we're going to open up command window and just do a double check right there. So open up command window and we're just going to check that we have Java installed. So we do java dash version and we have a version number that comes back. If we didn't have Java installed, we wouldn't get a Java version number come back. We'd actually have an error. All right. So everything looks good. So the next thing we want to do is to go to the Jenkins website and download the files. So we're going to go to jenkins.io. And that's the official Jenkins website. And if you want to download, you just go to jenkins.io/d download. or you can just type into your search bar download Jenkins and that will give you a link straight to the download page. And one of the things that you'll see is that there's lots of different versions uh for Jenkins because Jenkins runs on pretty much uh most operating systems uh including Windows uh Linux and Mac OS. But we want to select the Windows version. So we've already gone ahead and downloaded a zip file which contains all of the files that we need for Jenkins. And so that's the zip file and we've expanded it. And what we want to do now is h double click the installer file and we'll go ahead and install that. So we've already installed this. So um one of the things that we'll get is a message asking if you want to repair. You would actually get a install message because it' be a fresh install for you. Um but once you've done that, it has all the files and all the settings correctly installed onto your Windows computer. And we do all of our commands for Jenkins through um a web page that's run locally on your PC. And so you're going to type in localhost colon 8080. And when you do that, they'll actually take you to Jenkins running locally on your PC. And here we have our Jenkins dashboard. And we've already gone in and created some sample jobs. And you can see those listed on the uh sorry on the right hand side of the screen. So let's go through some of the things you would want to set up here. So first of all, let's go into the manage Jenkins screen and that will actually so we'll go to the manage Jenkins tab on the left hand side uh to do some standard configuration settings. So we'll go into the configuration systems and if you want to if you're like remotely connecting to a remote genkins environment you can actually install a JDK remotely for on that machine if you want to. We already have the JDK environment already set up so you know that's good here. So we don't need to do that. But you'll also see as you go through the the list of applications that you have gradal, ant, Maven, Docker, Git and other tools that you would use in a DevOps environment. There are many other tools you can install through plugins as well. Let's have a look at one more setting here with the security. The default security is Jenkins own user database. Uh that probably is not allowed within your company due to security um restrictions. Um so you can choose LDAP which allows you to connect with your active directory configuration again because there are so many plugins uh for Jenkins uh there are plugins for SAML authentication as well as OOTH. So, let's go ahead and start a new build, new build job. And so, we'll select a new item. And we're going to select demo one from that. Create a new item. And we're going to use just a freestyle project because I just want to demo how you can actually create a build. Okay. Description. Um gosh, what could we write here? Um, we can put in snippy demo. And we're not going to use source code for this one. We're going to do that in the next demo. put uh this what we want to go down to is the job type and we're going to so build and we can just do um add for wind execute Windows batch command and so let's just put in a very simple command and so we're going to type in echo open quotes hello world and then we'll put in the time stamp. So we'll put in date first and then time as part of our output close quotes and we're going to save that alo sit save and that's our simple project. So what we want to do now is we want to actually go and select the build now command to actually run this project. Yep. Build now. And it take a couple of minutes for it to run. And here we are. This is our project and we can actually now see the different builds that have happened. And if you look on the build history, you'll see the latest history shows when the build was executed. And if you click on that uh you can actually start getting information such as the console output will actually provide information that we were asking for. So for instance uh we have it's first of all we can see that the build was successful and we see the output includes uh the hello all and date and time. So we're going to go ahead and create one more project where we can actually connect to a GitHub and use the git command tool to be able to build a real project. So we're going to go ahead and create a new item and we're going to call this one Jenkins. It's freestyle project and our description is demo using git. Um, so we're actually going to connect to GitHub. Um, so to do that, we're going to go into source code management tab and we're going to select Git. And so we select that we can actually now connect to uh GitHub. Um, so to do that, you go to your GitHub account and you want to go in and select the clone or download and you get the URL link from there. So, copy that. Uh, go back to Jenkins and add that in the repository URL. So, you paste that in. And then for credentials, we want to add in our Jenkins credentials. And so, just make sure you have those selected correctly. And we've seen we just pull those from the drop down. And let's not change any of the other settings. And then for the build, we're actually going to be building a Java application. So, it's a slightly different set of build commands. So we want to type in Java C for compile and then space and the file name is simply Java and you want to put Java and space simply on a new line. Save that. It's again this is a really simple application but it gives you the understanding of what you need to do here. And so we saved it and let's now go ahead and see if everything's working. We'll do the build now and see what happens. And here is our first build. We select that. Uh we can go to the console output for details and what we can actually see if we scroll down is that the finished at the finished output at the very end says success which means everything was built correctly. And so that's how you're able to connect Jenkins with a git repository. And the thing that's great with working with Jenkins is that it connects to so many different systems and really does become the central point of your dev ops tool set. So let's start looking at the operations side of the DevOps uh environment and let's focus in on Docker. So before Docker, the problem you had as a developer, if you're working on a virtual machine, the actual virtual machine uh was a your VM was a very complex piece of software. First of all, VMs have not been around for very long. We're talking about less than 10 years. And the typical way of having a VM is that it's very heavy on usage on your um computer. You essentially are running everything of the VM plus the the tools to run the VM on your computer. With Docker, what you're able to control is the actual development environment you're working in. You don't have to be encumbered by all of the additional extraneous processing that a VM environment has. you're really stripped down to just the bare minimum that you need to have to run the environment using a containerized solution known as docker. So docker is essentially an OS level virtualization software. It is a maturity of the solutions that was started with virtual environments and there are other solutions out there. Doc has become the de facto container solution that you can use for building out and guaranteeing that what you the developer is building is going to be the same as what the operations team will use. So Docker itself is highly scalable and efficient. You can have many Docker environments running on a single piece of hardware. The boot up time is incredibly short. You can reuse the data volumes very very easily. is not complicated and the actual applications are completely isolated. This is a like a perfect sandbox environment. So let's dig through the architecture of Docker. So there are really two parts to Docker. There's the Docker engine and there's the Docker client. Uh the Docker engine is comprised of the Docker CLI which connects with the server demon. The Docker client will then issue the commands to the Docker demon and then the Docker demon will then interact with your system to be able to provide the tasks and tools needed for you to be able to build out your solution. The actual images that Docker uses are instructions for creating Docker containers. And the actual Docker container itself is a lightweight package that contains all the dependencies needed to run an application. Now once you have created a container that is of value to your team, you want to be able to store that container so that other team members can use it. And this is where you would use a Docker registry to be able to host and distribute multiple Docker images. So in this video, we're going to go ahead and see how we can get Docker installed and running. So we're going to go ahead and open up our terminal window, and we want to validate whether or not Docker is installed. Uh if you haven't installed Docker, you can actually go ahead and use the following command and that is to enter in pseudo apt install docker and that will go ahead and run the command to install Docker. Um I already have Docker installed on my system. So I'm not going to do that right now. So I'm just going to delete that out. But um what I am going to do is check to see what Docker images I have installed on my system. And to do that, I'm going to type in pseudo docker images. And when I run this, this will actually show how many images I have. And right now, I don't have any images at all. So, why don't we go ahead and install an image. There are two ways you could create an image for your Docker environment. One is to get one from Docker Hub and the other is to create your own image. And let's go ahead and get one from Docker Hub. And so the command line that we'd want to write is pseudo docker pull radius colon. And after the colon, we're going to actually write the name of the actual file that we're going to be connecting to from docker. So I'm going to go ahead and go to docker hub. And I have already logged in with my user ID and account. So I'm going to go to docker hub and hub.docker.com is the website address. And I'm already logged in with my Simply Learn account. And what you can actually see is different repositories that I have already created below. I'm going to click the explore button. And I can see the the Reddius image. And these are all the different commands that I can actually use, all the different variations that I can create. So I can I can do 5.0, I can do a 32bit version, I can do um a 4.0 version or a 3.8 eight version or if I select latest that will allow me to just pull the latest version even if it's updated. So I'm going to go back to my command line and do latest and what's going to happen now is that we're actually going to pull the files live over the internet and create the docker image. So this is going to take just a few minutes. Of course if your internet speed is faster then this will happen a lot faster. And here we are. We have everything downloaded which is great. And so let's just go and check and see if the image has been added to uh Docker. So we do uh pseudo docker images and now you can actually see that we have the latest reddest reddest um image and it's given the default image ID and there's the size of the docker image and the tag is latest. So it's the latest version of radius and I'm just checking to see if there's any other images running and no there isn't. So let's go ahead and now create a container. And so the command for that is pseudo docker run-d.0.0 I think it's 80 colon 80 space reddis colon latest. And let's run that. Got an error message. Okay. Now you know that it's a real demo. This is really live. So I'm just going to clear the screen and um let's write that in again. And so pseudo docker run-d and it's 0.0.0.0 col80 radius colus. And there we are. Everything's up and running. Awesome. So let's just go ahead and check that we actually have the image running in Docker. So pseudo docker ps. And there you can see that we actually have the latest Reddit version and it was created 16 seconds ago. We have a new container ID for it. And there's our port that we've created. And let's see if we can view all the running containers. And pseudo docker ps- a. There we are. And we created that container 42 seconds ago. One of the things you'll notice is um the name uh for the docker is created automatically by docker. And here we have stupified anglebars is the name. Let's change that name to something that's more meaningful for the work that we're doing. So that's actually fairly easy to do and it's going to be our final task here. So, we're going to type pseudo docker and the command is rename. And we want to copy over the old name and then we put in the old name and then you do a space and then you put in what you want the new name to be in which case we're going to make it simply learn. We run that command. That's good. Now, let's validate that everything has been changed. So, we're going to do pseudo docker ps- a just ps. And there we are. Everything has been renamed. And that gets you started working with Docker. Now let's move on to Anible. So before Antible, the ability to be able to deploy software across a network was pretty hard. Um, you know, you couldn't guarantee that your web servers were all consistent and that the database environments were consistent. This was okay if you had a small environment, but once you actually start getting into more complex environments, it became very difficult to manage. Antible is code that allows you to be able to consistently and reliably create and stand up the environments that you need to be able to store your code for production. So whether or not you require one server environment or you need a thousand server environments, using tools like Ansible will allow you to be able to consistently deploy out environments that all look the same. So essentially Antible is a configuration management tool and it allows you to be able to deploy automatically to a large variety of environments. The actual tool itself is a pushbased configuration tool. Uh it is an agentless tool. So there is no communication coming back about the health of the environment. We actually have tools that we'll cover later on in the video that cover that. Anible does have a consistency of its product performance. So you know that if you're using Ansible that it's going to work. It's just a very consistent product. And it uses SSH for very secure connections. So it doesn't matter whether or not you have one or a thousand pieces of hardware you're looking to configure. You can actually be rest assured that there will be no security infringement because of the use of SSH. Now we look into the architecture of Ansible. It's a very simple architecture. There is the aspole management node that has playbooks which contain the instructions