hello this is Matthew from simply learn and today we're gonna cover what is docker and why it should be of value to you as somebody who works in DevOps. So let's take a throw scenario a very developer Etna testa before you had the world of docker a developer would actually build their code and then they'd send it to the tester but then the code wouldn't work on their system coders are worldly a system due to the differences in computer environments. So what could be the solution to this well you could go ahead and create a virtual machine to be the same of the solution in both areas what do you think docker is an even better solution so let's kind of break out what the main big differences are between docker and virtual machines as you can see between the left and the right hand side both look to be very similar what you'll see however is that on the docker side what you'll see as a big difference is that the guest OS for each container has been eliminated docker is inherently more

lightweight, but provides the same functionality as a virtual machine. So, let's step through some of the pros and cons of a virtual machine versus Docker. So, first of all, a virtual machine occupies a lot more memory space on the host machine. In contrast, Docker occupies significantly less memory space. The boot-up time between both is very different. Docker just boots up faster. The performance of the Docker environment is actually better and more consistent than the virtual machine. Docker is also very easy to set up and very easy to scale. The efficiencies, therefore, are much higher with a Docker environment versus a virtual machine environment. And you'll find it is easier to port Docker across multiple platforms than a virtual machine. Finally, the space allocation between Docker and a virtual machine is significant. When you don't have to include the guest OS, you're eliminating a significant amount of space. And the Docker environment is just inherently smaller. So, after Docker, as a developer, you can build out your solution and send it to a tester. And as long as we're all running in the Docker environment, everything will work just.

great so let's step through what can I cover in this presentation. We're gonna look at the DevOps tools and where docker fits within that space. We'll examine what docker actually is and how docker works, and then finally we'll step through the different components of the docker environment. So what is DevOps? DevOps is a collaboration between the development team and the operation team, allowing you to continuously deliver solutions, applications, and services that both delight and improve the efficiency of your customers. If you look at the Venn diagram that we have here, on the left-hand side we have development, on the right-hand side we have operation, and then there's a crossover in the middle, and that's where the DevOps team sits. If we look at the areas of integration between both groups, developers are really interested in planning, code building, and testing, and operations want to be able to efficiently deploy, operate, and monitor. When you can have both groups interacting with each other on these seven key elements, then you can have the efficiencies of an excellent DevOps.

team. So, planning in codebase, we use tools like JIT and Guerra for building. We use Gradle and Maven. Testing, we use Selenium. The integration between dev and ops is through tools such as Jenkins. And then the deployment operation is done with tools such as Docker and Share. Finally, Nagios is used to monitor the entire environment. So, let's step deeper into what Docker actually is. So, Docker is a tool which is used to automate the deployment of applications in a lightweight container so the application can work efficiently in different environments. Now, it's important to note that the container is actually a software package that consists of all the dependencies required to run the application. So, multiple containers can run on the same hardware. The containers are maintained in isolated environments. They're highly productive and they're quick and easy to configure. So, let's take an example of what Docker is by using a house that may be rented for someone using Airbnb. So, in the house, there are three rooms and only one cupboard and kitchen. And the problem we have is that none of the guests are

really ready to share the cupboard and kitchen because every individual has a different preference when it comes to how the cupboard should be stocked and how the kitchen should be used. This is very similar to how we run software applications today. Each of the applications could end up using different frameworks. So you may have a framework such as Rails, Flask, and you may want to have them running for different applications, for different situations. This is where Docker will help you run the applications with the suitable frameworks. So let's go back to our Airbnb example. So we have three rooms and a kitchen and cupboard. How do we resolve this issue? Well, we put a kitchen in covered in each room. We can do the same thing for computers. Docker provides the suitable frameworks for each different application, and since every application has a framework with a suitable version, this space can also then be utilized for putting in Suffern applications that are long. And since every application has its framework and suitable version, the area that we had previously stored for a framework can be used for something else now.

can create a new application. In this instance, a fourth application that uses its own resources. You know, with these kinds of abilities to be able to free up space on the computer, it's no wonder Docker is the right choice. So let's take a closer look at how Docker actually works. So when we look at Docker and we call something Docker, we're actually referring to the base engine, which is installed on the host machine that has all the different components that run your Docker environment. And if we look at the image on the left-hand side of the screen, you'll see that Docker has a client-server relationship. There is a client installed on the hardware. There is a client that contains the Docker product. And then there is a server which controls how that Docker client is created. The communication that goes back and forth to be able to share the knowledge on that Docker client relationship is done through a REST API. This is fantastic news because that means that you can actually interface and program that API. So we look here in the animation, we see that the Docker

client is constantly communicating back to the server information about the infrastructure, and it's using this REST API as that communication channel. The docker server then will check out the requests and the interaction necessary for it to be the docker daemon, which runs on the server itself, will then check out the interaction and the necessary operating system pieces needed to be able to run the container. Okay, so that's just an overview of the docker engine, which is probably where you're going to spend most of your time, but there are some other components that form the infrastructure for docker. Let's dig into those a little bit deeper as well. So what we're going to do now is break out the four main components that comprise the docker environment. The four components are as follows: the docker clientís server, which we've already done a deeper dive on, docker images, docker containers, and the dagger registry. So if we look at the structure that we have here on the left-hand side, you see the relationship between the docker client and the darkest server, and then we have the REST API in between now.

if we start digging into that REST API, particularly the relationship with the Docker daemon on the server, we actually have other elements that form the different components of the Docker ecosystem. So, the Docker client is accessed from your terminal window. So, if you are using Windows, this can be PowerShell. On Mac, it's going to be your terminal window. And it allows you to run the Docker daemon and the registry service when you have your terminal window open. So, you can actually use your terminal window to create instructions on how to build and run your images and containers. If we look at the images part of our registry here, we actually see that the image is really just a template with the instructions used for creating the containers which you use within Docker. The Docker image is built using a file called the Dockerfile. And then once you've created that Dockerfile, you store that image in the Docker Hub or registry. And that allows other people to be able to access the same structure of a Docker environment that you've created. The syntax of creating the image is fairly simple. It's

something that you'll be able to get your arms around very quickly, and essentially what you're doing is you're creating the option of a new container. You're identifying what the image will look like, what are the commands that are needed, and the arguments for and then those commands. And once you've done that, you have a definition for what your image will look like. So if we look here at what the container itself looks like, is that the container is a standalone executable package, which includes applications and their dependencies. It's the instructions for what your environment will look like, so you can be consistent in how that environment is shared between multiple developers, testing units, and other people within your DevOps team. Now the thing that's great about working with docker is that it's so lightweight that you can actually run multiple docker containers in the same infrastructure and share the same operating system. This is its strength. It allows you to be able to create those multiple environments that you need for multiple projects. So you're working on. Interestingly though, within each container that contain it creates

an isolated area for the applications to run. So while you can run multiple containers in an infrastructure, each of those containers are completely isolated. They're protected so that you can actually control how your solutions work there. Now as a team, you may start off with one or two developers on your team, but when a project starts becoming more important and you start adding in more people to your team, you may have 15 people that are offshore, you may have 10 people that are local, you may have 15 consultants that are working on your project. You have a need for each of those two verbs or each person on your team to have access to that docket image. And to get access to that image, we use a Docker registry, which is an open source server site servers for hosting and distributing the images that you have defined. You can also use Docker itself as its own default Rattray and Docker Hub. Now something it has to be very mindful is that for publicly shared images, you may want to have your own private images in which

case you would do that through your own registry. So once again, public repositories can be used to host the docket images, which can be accessed by anyone. And I really encourage you to go out to Docker and see the other docket images that have been created, because there may be tools there that you can use to speed up your own development environments. Now, you will also get to a point where you start creating environments that are very specific to the solutions that you are building. And when you get to that point, you'll likely want to create a private repository, so you're not sharing that knowledge with the world in general. Now, the way in which you connect with the Docker registry is through simple pull and push commands that you run through terminal window to be able to get the latest information. So, if you want to be able to build your own container, what you'll start doing is using the pull commands to actually pull the image from the Docker repository. And the command line that is fairly simple in terminal window, you would write docker pull and then you put in the image name.

and any tags associated with that image, and use the command pools. So, in your terminal window, you would actually use a simple line of command once you've actually connected to your docker environment. And that command will be docker pull with the image name and any associated tags around that image. What that will then do is pull the image from the docker repository, whether that's a public repository or a private one. Now, in reverse, if you want to be able to update the docker image with new information, you do a push command where you would take the script that you've written about the docker container that you defined and push it to the repository. And as you can imagine, the commands for that are also fairly simple. In the terminal window, you would write docker push the image name, any associated tags, and then that would then push that image to the docker repository again, either a public or a private repository. So, if we recap, the docker file creates a docker image that's using the build commands. Docker image then contains all the information necessary for you to be able

to execute the project using the Docker image. Any user can run the code in order to create a Docker container. Once the Docker image is built, it is uploaded to a registry or to a Docker Hub where it can be shared across your entire team. From the Docker Hub, users can get access to the Docker image and build their own new containers. So, the five key takeaways here: with a virtual machine, you're able to create a virtualized environment to run an application on an operating system. With Docker, it allows you to focus on just running the application and doing it consistently. It improves the ability for teams to be able to share environments that are consistent from team to team. It's highly productive and it's really quick and easy to configure. The architecture of Docker is primarily built out of four components, of which the one that you'll use the most is the client-server environment. As a developer, you have a client application running on your local machine, and then you connect with a server environment where you're getting the latest information about

that container that you're building a solution for. And then finally, what we see with the workflow improvements with Docker is that the goal is to be able to be more efficient, to be able to be more consistent with your development environments, and be able to push out those environments, whether it goes to a test person, to a business analyst, or anybody else on your DevOps team, so they have a consistent environment that looks and acts exactly like your production environment and can be eventually pushed out to a production environment using tools such as Puppet or Chef. So you're creating a consistent operations environment. Really hope you've enjoyed this presentation. As always, click like and subscribe below to get more of these presentations. And if you have any questions, please put those in the comments below. Hi there. If you like this video, subscribe to the Simplilearn YouTube channel and click here to watch similar videos. De-nerd up and get certified. Click here.

What Is Docker? | What Is Docker And How It Works? | Docker Tutorial For Beginners | Simplilearn

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What Is Docker? | What Is Docker And How It Works? | Docker Tutorial For Beginners | Simplilearn

What Is Docker? | What Is Docker And How It Works? | Docker Tutorial For Beginners | Simplilearn

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