Docker pdf download

Docker pdf download

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Learning Docker eBook (PDF) Download this eBook for free Chapters Chapter 1: Getting started with Docker Chapter 2: Building images Chapter 3: Checkpoint and Restore Containers Docker Desktop is an application for MacOS and Windows machines for the building and sharing of containerized applications and microservices. Docker Desktop delivers the speed, choice Learning Path: Docker: Dockerization with Docker 31 Lectures 3 hours Lifetime Access Days Money Back Guarantee Buy Now You can download the PDF of this wonderful tutorial by Docker - Free download as Word Doc .doc /.docx), PDF File .pdf), Text File .txt) or read online for free. Download as DOCX, PDF, TXT or read online from Scribd. Flag for Double-click Docker Desktop blogger.com to run the installer. If you haven’t already downloaded the installer (Docker Desktop blogger.com), you can get it from Docker Hub. It typically ... read more

The --force or -f option skips any confirmation questions. You can also use the --all or -a option to remove all cached images in your local registry. From the very beginning of this book, I've been saying that images are multi-layered files. In this sub-section I'll demonstrate the various layers of an image and how they play an important role in the build process of that image. For this demonstration, I'll be using the custom-nginx:packaged image from the previous sub-section. To visualize the many layers of an image, you can use the image history command. The various layers of the custom-nginx:packaged image can be visualized as follows:. There are eight layers of this image. The upper most layer is the latest one and as you go down the layers get older. The upper most layer is the one that you usually use for running containers.

Now, let's have a closer look at the images beginning from image d70eafea down to 7ff As you can see, the image comprises of many read-only layers, each recording a new set of changes to the state triggered by certain instructions. When you start a container using an image, you get a new writable layer on top of the other layers. This layering phenomenon that happens every time you work with Docker has been made possible by an amazing technical concept called a union file system. Here, union means union in set theory. According to Wikipedia -. By utilizing this concept, Docker can avoid data duplication and can use previously created layers as a cache for later builds.

This results in compact, efficient images that can be used everywhere. In the previous sub-section, you learned about the FROM , EXPOSE , RUN and CMD instructions. In this sub-section you'll be learning a lot more about other instructions. In this sub-section you'll again create a custom NGINX image. But the twist is that you'll be building NGINX from source instead of installing it using some package manager such as apt-get as in the previous example. In order to build NGINX from source, you first need the source of NGINX. If you've cloned my projects repository you'll see a file named nginx gz inside the custom-nginx directory. You'll use this archive as the source for building NGINX. Before diving into writing some code, let's plan out the process first.

The image creation process this time can be done in seven steps. These are as follows:. Now that you have a plan, let's begin by opening up old Dockerfile and updating its contents as follows:. As you can see, the code inside the Dockerfile reflects the seven steps I talked about above. The code is almost identical to the previous code block except for a new instruction called ARG on line 13, 14 and the usage of the ADD instruction on line Explanation for the updated code is as follows:. The rest of the code is almost unchanged. You should be able to understand the usage of the arguments by yourself now. Finally let's try to build an image from this updated code. A container using the custom-nginx:built-v2 image has been successfully run. And here is the trusty default response page from NGINX. You can visit the official reference site to learn more about the available instructions.

The image we built in the last sub-section is functional but very unoptimized. To prove my point let's have a look at the size of the image using the image ls command:. For an image containing only NGINX, that's too much. If you pull the official image and check its size, you'll see how small it is:. As you can see on line 3, the RUN instruction installs a lot of stuff. Although these packages are necessary for building NGINX from source, they are not necessary for running it. Out of the 6 packages that we installed, only two are necessary for running NGINX. These are libpcre3 and zlib1g. So a better idea would be to uninstall the other packages once the build process is done. As you can see, on line 10 a single RUN instruction is doing all the necessary heavy-lifting.

The exact chain of events is as follows:. You may ask why am I doing so much work in a single RUN instruction instead of nicely splitting them into multiple instructions like we did previously. Well, splitting them up would be a mistake. If you install packages and then remove them in separate RUN instructions, they'll live in separate layers of the image. Although the final image will not have the removed packages, their size will still be added to the final image since they exist in one of the layers consisting the image. So make sure you make these kind of changes on a single layer. As you can see, the image size has gone from being MB to The official image is MB. This is a pretty optimized build, but we can go a bit further in the next sub-section. If you've been fiddling around with containers for some time now, you may have heard about something called Alpine Linux. It's a full-featured Linux distribution like Ubuntu , Debian or Fedora.

But the good thing about Alpine is that it's built around musl libc and busybox and is lightweight. Where the latest ubuntu image weighs at around 28MB, alpine is 2. Apart from the lightweight nature, Alpine is also secure and is a much better fit for creating containers than the other distributions. Although not as user friendly as the other commercial distributions, the transition to Alpine is still very simple. In this sub-section you'll learn about recreating the custom-nginx image using the Alpine image as its base. The code is almost identical except for a few changes. I'll be listing the changes and explaining them as I go:. Where the ubuntu version was Apart from the apk package manager, there are some other things that differ in Alpine from Ubuntu but they're not that big a deal. You can just search the internet whenever you get stuck.

In this section you'll learn how to make such an executable image. To begin with, open up the directory where you've cloned the repository that came with this book. The code for the rmbyext application resides inside the sub-directory with the same name. Before you start working on the Dockerfile take a moment to plan out what the final output should be. In my opinion it should be like something like this:. Now create a new Dockerfile inside the rmbyext directory and put the following code in it:. In this entire file, line 9 is the magic that turns this seemingly normal image into an executable one. Now to build the image you can execute following command:. Here I haven't provided any tag after the image name, so the image has been tagged as latest by default. You should be able to run the image as you saw in the previous section. Now that you know how to make images, it's time to share them with the world.

Sharing images online is easy. All you need is an account at any of the online registries. I'll be using Docker Hub here. Navigate to the Sign Up page and create a free account. A free account allows you to host unlimited public repositories and one private repository. Once you've created the account, you'll have to sign in to it using the docker CLI. So open up your terminal and execute the following command to do so:. You'll be prompted for your username and password. If you input them properly, you should be logged in to your account successfully. In order to share an image online, the image has to be tagged. You've already learned about tagging in a previous sub-section. Just to refresh your memory, the generic syntax for the --tag or -t option is as follows:. As an example, let's share the custom-nginx image online. To do so, open up a new terminal window inside the custom-nginx project directory.

My username is fhsinchy so the command will look like this:. The image name can be anything you want and can not be changed once you've uploaded the image. The tag can be changed whenever you want and usually reflects the version of the software or different kind of builds. Take the node image as an example. The node:lts image refers to the long term support version of Node. js whereas the node:lts-alpine version refers to the Node. js version built for Alpine Linux, which is much smaller than the regular one. If you do not give the image any tag, it'll be automatically tagged as latest. But that doesn't mean that the latest tag will always refer to the latest version. If, for some reason, you explicitly tag an older version of the image as latest , then Docker will not make any extra effort to cross check that. Depending on the image size, the upload may take some time. Once it's done you should able to find the image in your hub profile page. Now that you've got some idea of how to create images, it's time to work with something a bit more relevant.

In the process of containerizing this very simple application, you'll be introduced to volumes and multi-staged builds, two of the most important concepts in Docker. Code for the hello-dock application resides inside the sub-directory with the same name. Don't worry though, you don't need to know JavaScript or vite in order to go through this sub-section. Having a basic understanding of Node. js and npm will suffice. Just like any other project you've done in the previous sub-section, you'll begin by making a plan of how you want this application to run. In my opinion, the plan should be as follows:. This plan should always come from the developer of the application that you're containerizing. If you're the developer yourself, then you should already have a proper understanding of how this application needs to be run. Now if you put the above mentioned plan inside Dockerfile.

dev , the file should look like as follows:. Now, to build an image from this Dockerfile. dev you can execute the following command:. Given the filename is not Dockerfile you have to explicitly pass the filename using the --file option. A container can be run using this image by executing the following command:. Congratulations on running your first real-world application inside a container. The code you've just written is okay but there is one big issue with it and a few places where it can be improved. Let's begin with the issue first. If you've worked with any front-end JavaScript framework before, you should know that the development servers in these frameworks usually come with a hot reload feature. That is if you make a change in your code, the server will reload, automatically reflecting any changes you've made immediately. But if you make any changes in your code right now, you'll see nothing happening to your application running in the browser. This is because you're making changes in the code that you have in your local file system but the application you're seeing in the browser resides inside the container file system.

To solve this issue, you can again make use of a bind mount. Using bind mounts, you can easily mount one of your local file system directories inside a container. Instead of making a copy of the local file system, the bind mount can reference the local file system directly from inside the container. This way, any changes you make to your local source code will reflect immediately inside the container, triggering the hot reload feature of the vite development server. Changes made to the file system inside the container will be reflected on your local file system as well.

You've already learned in the Working With Executable Images sub-section, bind mounts can be created using the --volume or -v option for the container run or container start commands. Just to remind you, the generic syntax is as follows:. Stop your previously started hello-dock-dev container, and start a new container by executing the following command:. Keep in mind, I've omitted the --detach option and that's to demonstrate a very important point. As you can see, the application is not running at all now. That's because although the usage of a volume solves the issue of hot reloads, it introduces another problem.

If you have any previous experience with Node. js, you may know that the dependencies of a Node. This means that the vite package has gone missing. This problem can be solved using an anonymous volume. An anonymous volume is identical to a bind mount except that you don't need to specify the source directory here. The generic syntax for creating an anonymous volume is as follows:. So the final command for starting the hello-dock container with both volumes should be as follows:. So far in this section, you've built an image for running a JavaScript application in development mode. Now if you want to build the image in production mode, some new challenges show up. In development mode the npm run serve command starts a development server that serves the application to the user.

That server not only serves the files but also provides the hot reload feature. In production mode, the npm run build command compiles all your JavaScript code into some static HTML, CSS, and JavaScript files. To run these files you don't need node or any other runtime dependencies. All you need is a server like nginx for example. To create an image where the application runs in production mode, you can take the following steps:. This approach is completely valid. But the problem is that the node image is big and most of the stuff it carries is unnecessary to serve your static files. A better approach to this scenario is as follows:. This approach is a multi-staged build. To perform such a build, create a new Dockerfile inside your hello-dock project directory and put the following content in it:.

As you can see the Dockerfile looks a lot like your previous ones with a few oddities. The explanation for this file is as follows:. As you can see, the resulting image is a nginx base image containing only the files necessary for running the application. To build this image execute the following command:. Here you can see my hello-dock application in all its glory. Multi-staged builds can be very useful if you're building large applications with a lot of dependencies. If configured properly, images built in multiple stages can be very optimized and compact. If you've been working with git for some time now, you may know about the. gitignore files in projects. These contain a list of files and directories to be excluded from the repository. Well, Docker has a similar concept. dockerignore file contains a list of files and directories to be excluded from image builds.

You can find a pre-created. dockerignore file in the hello-dock directory. dockerignore file has to be in the build context. Files and directories mentioned here will be ignored by the COPY instruction. But if you do a bind mount, the. dockerignore file will have no effect. I've added. dockerignore files where necessary in the project repository. So far in this book, you've only worked with single container projects. But in real life, the majority of projects that you'll have to work with will have more than one container. And to be honest, working with a bunch of containers can be a little difficult if you don't understand the nuances of container isolation. So in this section of the book, you'll get familiar with basic networking with Docker and you'll work hands on with a small multi-container project. Well you've already learned in the previous section that containers are isolated environments.

Now consider a scenario where you have a notes-api application powered by Express. js and a PostgreSQL database server running in two separate containers. These two containers are completely isolated from each other and are oblivious to each other's existence. So how do you connect the two? Won't that be a challenge? The first one involves exposing a port from the postgres container and the notes-api will connect through that. Assume that the exposed port from the postgres container is Now if you try to connect to The reason is that when you're saying The postgres server simply doesn't exist there.

As a result the notes-api application failed to connect. The second solution you may think of is finding the exact IP address of the postgres container using the container inspect command and using that with the port. Assuming the name of the postgres container is notes-api-db-server you can easily get the IP address by executing the following command:. Now given that the default port for postgres is , you can very easily access the database server by connecting to There are problems in this approach as well. Using IP addresses to refer to a container is not recommended. Also, if the container gets destroyed and recreated, the IP address may change. Keeping track of these changing IP addresses can be pretty hectic. Now that I've dismissed the possible wrong answers to the original question, the correct answer is, you connect them by putting them under a user-defined bridge network.

A network in Docker is another logical object like a container and image. Just like the other two, there is a plethora of commands under the docker network group for manipulating networks. You should see three networks in your system. Now look at the DRIVER column of the table here. These drivers are can be treated as the type of network. There are also third-party plugins that allow you to integrate Docker with specialized network stacks. Out of the five mentioned above, you'll only work with the bridge networking driver in this book. Before you start creating your own bridge, I would like to take some time to discuss the default bridge network that comes with Docker. Let's begin by listing all the networks on your system:. As you can see, Docker comes with a default bridge network named bridge.

Any container you run will be automatically attached to this bridge network:. Containers attached to the default bridge network can communicate with each others using IP addresses which I have already discouraged in the previous sub-section. A user-defined bridge, however, has some extra features over the default one. According to the official docs on this topic, some notable extra features are as follows:. Now that you've learned quite a lot about a user-defined network, it's time to create one for yourself. A network can be created using the network create command. The generic syntax for the command is as follows:. As you can see a new network has been created with the given name. No container is currently attached to this network. In the next sub-section, you'll learn about attaching containers to a network. There are mostly two ways of attaching a container to a network. First, you can use the network connect command to attach a container to a network.

To connect the hello-dock container to the skynet network, you can execute the following command:. As you can see from the outputs of the two network inspect commands, the hello-dock container is now attached to both the skynet and the default bridge network. The second way of attaching a container to a network is by using the --network option for the container run or container create commands. To run another hello-dock container attached to the same network, you can execute the following command:. As you can see, running ping hello-dock from inside the alpine-box container works because both of the containers are under the same user-defined bridge network and automatic DNS resolution is working.

Keep in mind, though, that in order for the automatic DNS resolution to work you must assign custom names to the containers. Using the randomly generated name will not work. In the previous sub-section you learned about attaching containers to a network. In this sub-section, you'll learn about how to detach them. You can use the network disconnect command for this task. To detach the hello-dock container from the skynet network, you can execute the following command:. Just like the network connect command, the network disconnect command doesn't give any output. Just like the other logical objects in Docker, networks can be removed using the network rm command. To remove the skynet network from your system, you can execute the following command:. You can also use the network prune command to remove any unused networks from your system. The command also has the -f or --force and -a or --all options.

Now that you've learned enough about networks in Docker, in this section you'll learn to containerize a full-fledged multi-container project. The project you'll be working with is a simple notes-api powered by Express. js and PostgreSQL. In this project there are two containers in total that you'll have to connect using a network. Apart from this, you'll also learn about concepts like environment variables and named volumes. So without further ado, let's jump right in. The database server in this project is a simple PostgreSQL server and uses the official postgres image. PostgreSQL by default listens on port , so you need to publish that as well. The --env option for the container run and container create commands can be used for providing environment variables to a container.

As you can see, the database container has been created successfully and is running now. Although the container is running, there is a small problem. If your admin account is different to your user account, you must add the user to the docker-users group:. The Docker menu displays the Docker Subscription Service Agreement window. If you do not agree to the terms, the Docker Desktop application will close and you can no longer run Docker Desktop on your machine. You can choose to accept the terms at a later date by opening Docker Desktop. For more information, see Docker Desktop Subscription Service Agreement. We recommend that you also read the FAQs.

Download Docker Desktop for Windows Docker Desktop for Windows For checksums, see Release notes System requirements Your Windows machine must meet the following requirements to successfully install Docker Desktop. WSL 2 backend Hyper-V backend and Windows containers WSL 2 backend Windows 11 bit: Home or Pro version 21H2 or higher, or Enterprise or Education version 21H2 or higher. Windows 10 bit: Home or Pro 21H1 build or higher, or Enterprise or Education 20H2 build or higher. Enable the WSL 2 feature on Windows. For detailed instructions, refer to the Microsoft documentation. The following hardware prerequisites are required to successfully run WSL 2 on Windows 10 or Windows bit processor with Second Level Address Translation SLAT 4GB system RAM BIOS-level hardware virtualization support must be enabled in the BIOS settings.

For more information, see Virtualization. Download and install the Linux kernel update package. Hyper-V backend and Windows containers Windows 11 bit: Pro version 21H2 or higher, or Enterprise or Education version 21H2 or higher. Hyper-V and Containers Windows features must be enabled. We specified the argument -g "daemon off;". This command would then launch the Nginx daemon in the foreground and leave the container running as a web server. For example, we might want to specify the following in our Dockerfile. This allows us to build in a default command to execute when our container is run combined with overridable options and flags on the docker run command line.

We can use it to set the working directory for a series of instructions or for the final container. For example, to set the working directory for a specific instruction we might: Listing 4. You can override the working directory at runtime with the -w flag, for example: Listing 4. ENV The ENV instruction is used to set environment variables during the image build process. For example: Version: v1. NOTE You can also escape environment variables when needed by prefixing them with a backslash. These environment variables will also be persisted into any containers created from your image. You can also pass environment variables on the docker run command line using the -e flag. These variables will only apply at runtime, for example: Version: v1. USER The USER instruction specifies a user that the image should be run as; for example: Listing 4. We can specify a username or a UID and group or GID. Or even a combination thereof, for example: Version: v1. VOLUME The VOLUME instruction adds volumes to any container created from the image.

This allows us to add data like source code , a database, or other content into an image without committing it to the image and allows us to share that data between containers. You can use the VOLUME instruction like so: Listing 4. TIP Also useful and related is the docker cp command. This allows you to copy files to and from your containers. You can read about it in the Docker command line documentation. Or we can specify multiple volumes by specifying an array: Listing 4. The ADD instruction specifies a source and a destination for the files, like so: Listing 4. lic This ADD instruction will copy the file software. lic in the image. The source of the file can be a URL, filename, or directory as long as it is inside the build context or environment. You cannot ADD files from outside the build directory or context. The source of the file can also be a URL; for example: Listing 4.

zip Lastly, the ADD instruction has some special magic for taking care of local tar archives. If a tar archive valid archive types include gzip, bzip2, xz is specified as the source file, then Docker will automatically unpack it for you: Listing 4. The archive is unpacked with the same behavior as running tar with the -x option: the output is the union of whatever exists in the destination plus the contents of the archive. If a file or directory with the same name already exists in the destination, it will not be overwritten. WARNING Currently this will not work with a tar archive specified in a URL.

This is somewhat inconsistent behavior and may change in a future release. New files and directories will be created with a mode of and a UID and GID of 0. If the files or directories added by an ADD instruction change then this will invalidate the cache for all following instructions in the Dockerfile. COPY The COPY instruction is closely related to the ADD instruction. The key difference is that the COPY instruction is purely focused on copying local files from the build context and does not have any extraction or decompression capabilities. You cannot copy anything that is outside of this directory, because the build context is up- loaded to the Docker daemon, and the copy takes place there.

Anything outside of the build context is not available. The destination should be an absolute path inside the container. Any files and directories created by the copy will have a UID and GID of 0. If the source is a directory, the entire directory is copied, including filesystem metadata; if the source is any other kind of file, it is copied individually along with its metadata. LABEL The LABEL instruction adds metadata to a Docker image. You can specify one item of metadata per label or multiple items separated with white space. We recommend combining all your metadata in a single LABEL instruction to save creating multiple layers with each piece of metadata. You can inspect the labels on an image using the docker inspect command.. NOTE The LABEL instruction was introduced in Docker 1. This signal can be a valid number from the kernel syscall table, for instance 9, or a signal name in the format SIGNAME, for instance SIGKILL. This is done using the --build-arg flag.

Your credentials will be exposed during the build process and in the build history of the image. Docker has a set of predefined ARG variables that you can use at build-time without a corresponding ARG instruction in the Dockerfile. NOTE The ARG instruction was introduced in Docker 1. ONBUILD The ONBUILD instruction adds triggers to images. A trigger is executed when the image is used as the basis of another image e. The trigger inserts a new instruction in the build process, as if it were specified right after the FROM instruction. The trigger can be any build instruction. Step 7 : ONBUILD ADD. This could readily be our generic web application template from which I build web applications. Successfully built ad86 We see that straight after the FROM instruction, Docker has inserted the ADD in- struction, specified by the ONBUILD trigger, and then proceeded to execute the remaining steps.

The ONBUILD triggers are executed in the order specified in the parent image and are only inherited once i. This is done to prevent Inception-like recursion in Dockerfile builds. This allows us to make it available for others to use. For example, we could share it with others in our organization or make it publicly available. NOTE The Docker Hub also has the option of private repositories. These are a paid-for feature that allows you to store an image in a private repository that is only available to you or anyone with whom you share it. This allows you to have private images containing proprietary information or code you might not want to share publicly. We push images to the Docker Hub using the docker push command.

Root repositories are managed only by the Docker, Inc. io 1 tags. We would write to your own user ID, which we created earlier, and to an appropriately named image e. We can now see our uploaded image on the Docker Hub. TIP You can find documentation and more information on the features of the Docker Hub here. Automated Builds In addition to being able to build and push our images from the command line, the Docker Hub also allows us to define Automated Builds. We can do so by con- necting a GitHub or BitBucket repository containing a Dockerfile to the Docker Hub.

When we push to this repository, an image build will be triggered and a new image created. This was previously also known as a Trusted Build. The first step in adding an Automated Build to the Docker Hub is to connect your GitHub account or BitBucket to your Docker Hub account. You will see a page that shows your options for linking to either GitHub or Bit- Bucket. Click the Select button under the GitHub logo to initiate the account linkage. You will be taken to GitHub and asked to authorize access for Docker Hub. On Github you have two options: Public and Private recommended and Limited. Select Public and Private recommended , and click Allow Access to complete the authorization. You may be prompted to input your GitHub password to confirm the access. From here, you will be prompted to select the organization and repository from which you want to construct an Automated Build. Select the repository from which you wish to create an Automated Build by click- ing the Select button next to the required repository, and then configure the build.

Specify the default branch you wish to use, and confirm the repository name. Specify a tag you wish to apply to any resulting build, then specify the location of the Dockerfile. The default is assumed to be the root of the repository, but you can override this with any path. Finally, click the Create Repository button to add your Automated Build to the Docker Hub. You will now see your Automated Build submitted. Click on the Build Status link to see the status of the last build, including log output showing the build process and any errors. A build status of Done indicates the Automated Build is up to date. An Error status indicates a problem; you can click through to see the log output. You can only update it by pushing updates to your GitHub or BitBucket repository. NOTE This only deletes the image locally. We can also delete more than one image by specifying a list on the command line. The team at Docker, Inc. The registry does not currently have a user interface and is only made available as an API service.

Running a registry from a container Installing a registry from a Docker container is simple. Just run the Docker- provided container like so: Version: v1. This will launch a container running version 2. Testing the new registry So how can we make use of our new registry? To specify the new registry destination, we prefix the image name with the hostname and port of our new registry. In our case, our new registry has a hostname of docker. The image is then posted in the local registry and available for us to build new containers using the docker run command. To find out details like configuring authentication, how to manage the backend storage for your im- ages and how to manage your registry see the full configuration and deployments details in the Docker Registry deployment documentation. Quay The Quay service provides a private hosted registry that allows you to upload both public and private containers. Unlimited public repositories are currently free.

Private repositories are available in a series of scaled plans. The Quay product has recently been acquired by CoreOS and will be integrated into that product. This gives us the basis for starting to build services with Docker. Using Docker to test a static website One of the simplest use cases for Docker is as a local web development environ- ment. Such an environment allows you to replicate your production environment and ensure what you develop will also likely run in production. Our website is originally named Sample. We start by creating a directory to hold our Dockerfile first. Listing 5. Our two Nginx configuration files configure Nginx for running our Sample website. The global. conf configuration file specifies: Listing 5. conf file server { listen 0. html index. We also need to configure Nginx to run non-daemonized in order to allow it to work inside our Docker container. conf; } In this configuration file, the daemon off; option stops Nginx from going into the background and forces it to run in the foreground.

This is because Docker containers rely on the running process inside them to remain active. By default, Nginx daemonizes itself when started, which would cause the container to run briefly and then stop when the daemon was forked and launched and the original process that forked it stopped. conf by the ADD instruction. Both styles are accepted ways of copying files into a Docker image. NOTE You can find all the code and sample configuration files for this at The Docker Book Code site or the Docker Book site.

You will need to specifically download or copy and paste the nginx. conf and global. conf configuration files into the nginx directory we created to make them available for the docker build. This will build and name our new image, and you should see the build steps execute. We can take a look at the steps and layers that make up our new image using the docker history command. Each step in between shows the new layer and the instruction from the Dockerfile that generated it. This will create a directory called website inside the sample directory. We then download an index. html file for our Sample website into that website directory. This directive causes Nginx to run interactively in the foreground when launched. You will have seen most of the options Version: v1. This new option allows us to create a volume in our container from a directory on the host. Volumes are specially designated directories within one or more contain- ers that bypass the layered Union File System to provide persistent or shared data for Docker.

This means that changes to a volume are made directly and bypass the image. They will not be included when we commit or build an image. TIP Volumes can also be shared between containers and can persist even when containers are stopped. The -v option works by specifying a directory or mount on the local host separated from the directory on the container with a :. You can see the index. html file we downloaded inside that directory. Now, if we look at our running container using the docker ps command, we see that it is active, it is named website, and port 80 on the container is mapped to port on the host.

See further details in Chapter 2 when we discuss installation. Editing our website Neat! Now what happens if we edit our website? html file in the website folder on our local host and edit it. html Version: v1. Figure 5. We see that our Sample website has been updated. This is a simple example of editing a website, but you can see how you could easily do so much more. You can now have containers for each type of production web-serving environment e. Sinatra is a Ruby- based web application framework. It contains a web application library and a simple Domain Specific Language or DSL for creating web applications. Unlike more complex web application frameworks, like Ruby on Rails, Sinatra does not follow the model—view—controller pattern but rather allows you to create quick and simple web applications.

In our case our new application is going to take incoming URL parameters and output them as a JSON hash. You can find the code for this Sinatra application here or at The Docker Book site. The application is made up of the bin and lib directories from the webapp directory. rb file. This command will be executed when a container is launched from this image. We can also use the docker logs command to see what happened when our com- mand was executed. We can also see the running processes of our Sinatra Docker container using the docker top command. It just takes incoming parameters, turns them into JSON, and then outputs them.

We can now use the curl command to test our application. rb now. get "params" params. set "params", [params]. We now create a connection to a Redis database on a host called db on port We also post our parameters to that Redis database and then get them back from it when required. This is usually the redis-tools package on Ubuntu. You can use the quit command to exit the Redis CLI interface. So which method should I choose? The two realistic methods for connecting containers are Docker Networking and Docker links. Which you choose is probably dependent on what version of Docker you are running. On earlier versions you should use links. There are also some differences between networks and links, that explains why it makes sense to use networks instead of links going forward. With links we may need to update some configuration or restart other containers to maintain links. Every Docker container is assigned an IP address, provided through an interface created when we installed Docker.

That interface is called docker0. To enable this run the Docker daemon with the --ipv6 flag. The docker0 interface has an RFC private IP address in the This address, TIP Docker will default to x as a subnet unless that subnet is already in use, in which case it will try to acquire another in the The docker0 interface is a virtual Ethernet bridge that connects our containers and the local host network. Every time Docker creates a container, it creates a pair of peer interfaces that are like opposite ends of a pipe i. It gives one of the peers to the container to become its eth0 interface and keeps the other peer, with a unique name like vethec6a, out on the host machine.

You can think of a veth interface as one end of a virtual network cable. One end is plugged into the docker0 bridge, and the other end is plugged into the container. com traceroute to google. com net Firstly, we can note that there is no default access into our containers. We specifically have to open up ports to communicate to them from the host network. We see one example of this in the DNAT, or destination NAT, rule that routes traffic from our container to port on the Docker host. The docker inspect command shows the details of a Docker container, including its configuration and networking. We could also use the -f flag to only acquire the IP address. IPAddress }}' redis We can instead use the NOTE Docker binds exposed ports on all interfaces by default; therefore, the Redis server will also be available on the localhost or Secondly, if we restart the container, Docker changes the IP address. Docker networking Container connections are created using networks.

This is called Docker Network- ing and was introduced in the Docker 1. Docker Networking allows you to setup your own networks through which containers can communicate. Es- sentially this supplements the existing docker0 network with new, user managed networks. Importantly, containers can now communicate with each across hosts and your networking configuration can be highly customizable. To use Docker networks we first need to create a network and then launch a container inside that network. A network ID is returned for the network. We can then inspect this network using the docker network inspect command. TIP In addition to bridge networks, which exist on a single host, we can also create overlay networks, which allow us to span multiple hosts.

You can read more about overlay networks in the Docker multi-host network documentation. You can list all current networks using the docker network ls command. The --net flag specifies a network to run our container inside. To do this we need to be back in the sinatra directory. It also contains two entries for the db container. The second one adds the app network as a domain suffix for the network, any host in the app network can be resolved by hostname. app, here db. app PING db. app But in our case we just need the db entry to make our application function as our Redis connection code already uses the db hostname.

Our application works! Connecting existing containers to the network You can also add already running containers to existing networks using the docker network connect command. So we can add an existing container to our app Version: v1. We can also disconnect a container from a network using the docker network disconnect command. Containers can belong to multiple networks at once so you can create quite com- plex networking models. TIP Further information on Docker Networking is available in the Docker docu- mentation. This was the preferred method of connecting containers prior to Docker 1. Linking one container to another is a simple process involving container names. For the benefit of folks on versions prior to Docker 1. We start by creating a new Redis container or we could reuse the one we launched earlier.

We need to be back in the sinatra directory to run the container. The --link flag creates a client-service link between two containers. The flag takes two arguments: the container name to link and an alias for the link. The alias allows us to consistently access the exposed information without needing to be concerned about the underlying container name. The link gives the service container the ability to communicate with the client container and shares some connection details with it to help you configure applications to make use of the link. We also get a security-related benefit from this linkage. But even better, only containers explicitly linked to this container using the -- link flag can connect to this port.

Given that the port is not published to the local host, we now have a strong security model for limiting the attack surface and network exposure of a containerized application. TIP If you wish, for security reasons for example , you can force Docker to only allow communication between containers if a link exists. This turns off communications between all containers unless a link exists. For example, if we wanted to use our Redis instance for multiple web applications, we could link each web application container to the same redis container. We can also specify the --link command multiple times to link to multiple con- tainers. TIP Container linking currently only works on a single Docker host. Or Docker Swarm, which we talk about in Chapter 7, which will allow you to do some orchestration between Docker daemons on different hosts. You can use the -h or --hostname flag with the docker run command to set a specific hostname for the container.

For example, we might want to add the hostname and Version: v1. This would add an entry for a host called docker with an IP address of TIP Remember how we mentioned that container IP addresses change when a container is restarted? Well since Docker version 1. We see a bunch of environment variables here, including some prefixed with DB. Docker automatically creates these variables when we link the webapp and redis containers. They start with DB because that is the alias we used when we created our link. The precise variables will vary from container to container depending on what is configured on that container e. More importantly, they include infor- mation we can use inside our applications to consistently link between containers.

rb file might look using our new environment variables. Our application can now use this connection information to find Re- dis in a linked container. This abstracts away the need to hard-code an IP address and port to provide connectivity. Alternatively, there is the more flexible local DNS, which is the solution we chose. TIP You can also configure the DNS of your individual containers using the --dns and --dns-search flags on the docker run command. This allows you to set the local DNS resolution path and search domains. You can read about this here. In the absence of both of these flags, Docker will set DNS resolution to match that of the Docker host. conf file. We can now test our application as we did in the Docker Networking section and confirm that our container connections are functioning correctly. We recom- mend that you use Docker Networking in releases after Docker 1.

This way you can build, replicate, and iterate on production applications, even complex multi-tier applications, in your local environment. Using Docker for continuous integration Up until now, all our testing examples have been local, single developer-centric examples i. Docker excels at quickly generating and disposing of one or multiple containers. Often in a testing scenario you need to install software or deploy multiple hosts frequently, run your tests, and then clean up the hosts to be ready to run again. In a continuous integration environment, you might need these installation steps and hosts multiple times a day. This adds a considerable build and configuration overhead to your testing lifecycle. Package and installation steps can also be time- consuming and annoying, especially if requirements change frequently or steps require complex or time-consuming processes to clean up or revert. Docker makes the deployment and cleanup of these steps and hosts cheap.

Turtles all the way down! TIP You can read more about Docker-in-Docker here. It could be considered simpler but I think the recursive approach is interesting. hpi ; done ADD. Firstly, it sets up the Ubuntu and Docker APT repositories we need and adds the Docker repository GPG key. We then update our package list and install the pack- ages required to run both Docker and Jenkins. We also need some Jenkins plugins. Plugins provide support for additional capabilities for Jenkins e. Remember, the VOLUME instruction adds a volume from the host launching the container.

This location must be a real filesystem rather than a mount point like the layers in a Docker image. There is a bit more information about why the shell script does what it does to allow Docker-in-Docker here. We should be inside the jenkins directory we just created our Dockerfile in to do this. We can now create a container from this image using the docker run command. Privileged mode Version: v1. This enables the special magic that allows us to run Docker inside Docker. WARNING Running Docker in --privileged mode is a security risk. Con- tainers with this enabled have root-level access to the Docker host. Ensure you appropriately secure your Docker host and only use a Docker host that is an ap- propriate trust domain or only runs containers with similar trust profiles. We see that our new container, jenkins, has been started.

war webroot: EnvVars. Logger logInternal INFO: Beginning extraction from war file. You can keep checking the logs, or run docker logs with the -f flag, until you see a message similar to: Version: v1. Our Jenkins server should now be available in your browser on port , as we see here: Figure 5. Then click the Advanced. This is the workspace in which our Jenkins job is going to run. This is a sim- ple repository containing some Ruby-based RSpec tests. This Dockerfile provides the test environment in which we wish to execute. This will build an image that we can test using a typical Ruby-based application that relies on the RSpec test framework.

Back to our script. Next we create a container from our image and run the tests. txt Now we want to attach to that container to get the output from it using the docker attach command. and then use the docker wait command. The docker wait command blocks until the command the container is executing finishes and then returns the exit code of the container. The RC variable captures the exit code from the container when it completes. This should be the exit code of our test run. Next we click the Add post-build action and add Publish JUnit test result report. Finally, we must click the Save button to save our new job. We can click on Console Output to see the commands that have been executed as part of the job.

We see that Jenkins has downloaded our Git repository to the workspace. We can then execute our Shell script and build a Docker image using the docker build command. Running this new container executes the RSpec tests and captures the results of the tests and the exit code. If the job exits with an exit code of 0, then the job will be marked as successful. You can also view the precise test results by clicking the Test Result link. This will have captured the RSpec output of our tests in JUnit form. Next steps with our Jenkins job We can also automate our Jenkins job further by enabling SCM polling, which triggers automatic builds when new commits are made to the repository. Similar automation can be achieved with a post-commit hook or via a GitHub or Bitbucket repository hook.

This Jenkins job uses Docker to create an image that we can manage and keep updated using the Dockerfile contained in our repository. In this scenario, not only does our infrastructure configuration live with our code, but managing that configuration becomes a simple process. Containers are then created from that image in which we then run our tests. It is also easy to adapt this example to test on different platforms or using different test frameworks for numerous languages. TIP You could also use parameterized builds to make this job and the shell script step more generic to suit multiple frameworks and languages. What if we wanted to test our application on multiple platforms? When the Jenkins multi-configuration job is run, it will spawn multiple sub-jobs that will test varying configurations.

Transform and optimize workflows by connecting to an array of pre-built developer tools from our Docker Extensions Marketplace for things like debugging, testing, networking, and security. Explore near endless workflow possibilities by creating your own custom tools and share them with your team or the whole world. Docker Desktop helps you quickly and safely evaluate software so you can start secure and push with confidence. Docker Desktop now includes the ability to generate a Software Bill of Material SBOM pre-build, as well as vulnerability scanning powered by Snyk, which scans your containers and provides actionable insights and recommendations for remediation in your images. Learn more about end-to-end vulnerability scanning and how to shift security left in your app delivery pipeline. Simplify code to cloud application development by closely integrating with Azure Container Instances ACI.

You get the same workflow in Docker Desktop and the Docker CLI with all the container compute you want. No infrastructure to manage. No clusters to provision. Stay more secure by managing which container images on Docker Hub developers can access, and gain more control by configuring organizations to only allow access to Docker Official Images and Docker Verified Publishers. Available with Docker Business. Docker Desktop delivers the speed, choice and security you need for designing and delivering these containerized applications on your desktop. Docker Desktop includes Developer tools , Kubernetes and version synchronization to production Docker Engines. Docker Desktop allows you to leverage certified images and templates and your choice of languages and tools. Development workflows leverage Docker Hub to extend your development environment to a secure repository for rapid auto-building, continuous integration and secure collaboration. Learn more.

Get scoops on new products and community management resources to help your group flourish. Join our special events and get sneak peaks of DockerCon. Develop new skills and build your reputation as a key community leader. Expand your network, learn and connect with like-minded developers. Connect with fellow Community Leaders who can help you learn how to effectively build, manage and grow your community. Benefit from more collaboration, increased security, without limits all enabled with a Docker subscription. Check out our pricing. Docker Desktop Install Docker Desktop — the fastest way to containerize applications. Intel Chip. Apple Chip. The Docker Subscription Service Agreement has been updated. The effective date of these terms is August 31, There is a grace period until January 31, for those that will require a paid subscription to use Docker Desktop. The Docker Pro, Docker Team, and Docker Business subscriptions now include commercial use of Docker Desktop.

Check out our FAQ for more information. Or read our latest blog. Docker Extensions Transform and optimize workflows by connecting to an array of pre-built developer tools from our Docker Extensions Marketplace for things like debugging, testing, networking, and security. Learn More. Volume Management, Dev Environments and more Takes the guesswork out of volume management. Docker Desktop simplifies setting up common and consistent local developer environments across an organization. Secure from the start Docker Desktop helps you quickly and safely evaluate software so you can start secure and push with confidence. Read the Blog. Simplify Code to Cloud Simplify code to cloud application development by closely integrating with Azure Container Instances ACI.

Image Access Management Stay more secure by managing which container images on Docker Hub developers can access, and gain more control by configuring organizations to only allow access to Docker Official Images and Docker Verified Publishers. Build Kubernetes-ready applications on your desktop Docker Desktop is an application for MacOS and Windows machines for the building and sharing of containerized applications and microservices. Considering Alternatives? Containerize and share any application Across any combination of clouds, languages and frameworks.

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The Docker Handbook – Learn Docker for Beginners,Install Docker Desktop on Windows

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Automated Builds In addition to being able to build and push our images from the command line, the Docker Hub also allows us to define Automated Builds. The docker run command will open a random port on the Docker host that will connect to port 80 on the Docker container. Paul has spoken at various conferences, from talking about Agile Infrastructure at Agile during the early days of the DevOps movement to smaller meetups and conferences. Unlimited public repositories are currently free. We take you through the development life cycle, from testing to production, and see where Docker fits in and how it can make your life easier.

The first step in adding an Automated Build to the Docker Hub is to connect your GitHub docker pdf download or BitBucket to your Docker Hub account. Docker excels at quickly generating and disposing of one or multiple containers. Using this information, we check the status of our application by browsing to the mapped port. The destination should be an absolute path inside the container. If you've cloned the project code repository, then go inside the fullstack-notes-application directory, docker pdf download.