As businesses move more and more infrastructure online due to the effects of competition (not to mention COVID-19), finding the best way to manage that infrastructure becomes more and more important. Docker gives development teams more reliable, repeatable, and testable systems that can be deployed at massive scale with the click of a button. In this series (Parts 1 and 2 are linked below), we are looking under the hood at Docker, an infrastructure management tool that has grown rapidly in popularity over the last decade.
- Linux Docker For Mac Localhost Equivalenttoylasopa Setup
- Docker Docker.for.mac.localhost
- Docker.for.mac.localhost Linux
- Linux Docker For Mac Localhost Equivalenttoylasopa Download
- Linux Docker For Mac Localhost Equivalenttoylasopa Tutorial
In this installment, I will walk you through the process of using the Docker command line tools to download, install, and run containers, as well as build your own container. If you’re not a technologist, you should skip this article. If you are, then jump right in!
Learn how to build and share a containerized app In this self-paced, hands-on tutorial, you will learn how to build images, run containers, use volumes to persist data and mount in source code, and define your application using Docker Compose. Docker exec-it vue-storefront-apiapp1 yarn restore docker exec-it vue-storefront-apiapp1 yarn migrate Clone the image files for default product database (we're using Magento2 example products dataset (opens new window).
Installing Docker
The installation process varies by operating system, but installing Docker is fairly straightforward. However, you must be running a 64-bit operating system (which is common today) in order to run Docker.
All of the commands given will be for a root user. On Linux-based servers, you must be the root user to install and run Docker and Docker images, so all of the commands given will be for the root user. You can run Docker images as a non-root user but doing so is outside the scope of this tutorial.
To install Docker on a CentOS 7-based Linux system, just run “yum install docker” and everything installs (CentOS 8 is more involved – see here). For a Debian-based system, run “apt-get install docker.io”. Then, for both of them, you can run “systemctl start docker” to get the service up and running and “systemctl enable docker” to make sure that it starts when the machine reboots.
On Windows and Mac, you can download Docker from DockerHub. Docker Desktop for Mac is available here and Docker Desktop for Windows is available here.
On Windows, Mac, or Linux, Docker is primarily a command-line tool. So, this tutorial will assume at least a basic working knowledge of how the command line works.
Running Your First Container
In order to demonstrate different aspects of Docker containers, I built a few custom containers just for this article. The first one will be a “hello world” container, which just turns on, says “hello world,” and turns back off. To run this, just do:
The first time you run this, it will connect to the standard Docker registry and look for a repository named “johnnyb61820/hello-world” (johnnyb61820 is my username). It will then find the image tagged with “latest” (meaning the most recent version of this image). It will pull down the image, save it locally, and then run it. It will display information about downloading the image and then the last line will say “Hello World!”.
If you run the command again, since the image is now saved to your computer, it will just print “Hello World!” and exit. Run the command a total of three times.
Now we will investigate what those commands actually did on your computer. The first thing it did was to install a Docker image onto your computer. You can see this by running the following command:
If you aren’t familiar with Unix terminology, “ls” (that’s an L and an S if you are having trouble reading it) is a shortened form of “list,” so this command lists the docker images on your computer. If this is your first time using Docker, it should print out something like this:
The repository is where the image is located. The “tag” is the version number (“latest” is the standard version for the most recent version of this image). The “Image ID” is the computer’s name for the image. The “size” is how much space it takes up on your computer.
However, the image is just the unchanging part of a container. A container itself is a full virtual machine that has both changing and unchanging components. In fact, if you ran the “Hello World” program three times, your computer now has three containers on it. You can see them by running the following command:
docker container ls -a Without the “-a”, this command will only list running containers. But we want to see all of the containers on the computer, whether running or not. This produces what may be some surprising output:
Every time we ran the command, the system started up a new container (i.e., a new “virtual machine”), created a read-write space for the command to run in, ran the code in the container, and exited. The containers still exist, and here they are. So what do these columns mean?
The Container ID is the computer’s internal name for your container, and is generated at random. The “names” on the right-hand side are also generated, but are meant to be more human-readable. You can refer to containers by either name. The “image” is the name of the image on which the container is running. The “command” is the command that was run when the container executed.
Most containers contain entire operating systems that have several commands available. However, this container only has one file—the program to execute. Additionally, containers specify an “entrypoint” or “default command” and this is the command that they run when they are started. In our case, the the “johnnyb61820/hello-world” container had one file in it, “/hello”, which is run when the container starts.
To restart the container (i.e., to re-run the command in the container without creating a new one), we will issue a “start” command to the container with the following command:
In this command, replace CONTAINER_ID with one of the Container IDs that returned when you listed the available containers (or you can use the friendlier name as well). This will re-run the command within the existing container, rather than creating a new one.
Now, first you might be wondering why these containers are staying around. The reason is simple—in most cases, these are full applications, so, even when they aren’t running, we don’t want the container to be deleted! However, in this case, the program doesn’t save any information, so we can just delete the container. We can tell Docker to auto-delete a container when it is done running by adding “–rm” to the “docker run” command, like this:
This will create the container, run the command, and then remove the container when the command is done, so it is not listed in the list of containers.
Note, however, that containers are not expensive! The containers all share the image that they start with. In our case, the application does not modify any files, which means that the amount of disk space that they use is extremely small (about 200kB each).
To delete your non-running containers, run the command:
you can add a “-a” to the end of that command to also delete all the images that are not presently used.
If you want to try out another simple docker command, run:
This will simply simulate the roll of a dice.
Running a Docker Service
Docker is usually used to run services rather than individual commands. In this next example, we will run a Docker app that runs as a very simple HTTP service on port 8070 inside the container. As you will see, we can map that port to a port on the main server (the example will use port 8080).
Run:
While it is running, you can use your web browser to access the service running on your machine at http://localhost:8080/ . It should give you back a plain-looking web page that says, “Hello from Docker!” You can push control-c at any time to stop the service.
So what does this command do? It is almost identical to our previous commands, with the exception that there is a “-p 8080:8070” added to the command. Remember, each container acts almost exactly like a full virtual machine. That means that each container has its own networking, too. The “-p” flag says to take the port 8080 on the real machine, and proxy it to port 8070 on the Docker virtual machine. Note that these can actually be the same value because they act like completely separate machines. However, I put different values so that you can see that you can map the ports in any way you wish.
Now, most services are actually run in the background. To run a Docker image as a background service, add a “-d” flag like this:
It will print out the Container ID (which is a longer form of the same name you get from “docker container ls”) and return to you. Now, if you do “docker container ls” you can see it running:
Note that without the “-ai”, “docker container ls” only shows actively running containers. It shows the ports that have been proxied from the main host to the container. We can then stop the container with “docker container stop CONTAINER_ID”. We can restart it again with “docker container start CONTAINER_ID”. We used the “-a” flag earlier because otherwise, “docker container start” runs the container in the background (which we now want to do). After a container is stopped, it can be removed altogether by “docker container rm CONTAINER_ID”. Remember, the CONTAINER_ID can be either the raw ID that the computer generates, or the more user-friendly name.
Running a Whole Operating System
So far, the containers we have been looking at are extremely lightweight, as they only contain one single file with the command in them. However, most Docker instances actually contain a minimal operating system, often based on the Ubuntu Linux distribution.
If you want to run a container as essentially a full machine, run the following command:
The “-it” will allocate an interactive terminal. The default program that is run with ubuntu in the command line is the shell. That means that running this command will (a) download a fairly minimal Ubuntu distribution (about 75MB), (b) create a container, and (c) start up a shell in which you are now typing. Again, this is a real Linux distribution, so you can use “apt-get” to install whatever additional packages you like. However, don’t forget to “apt-get update” to retrieve the list of packages available for installation.
Note that, in the container, you can do anything you want: create files, run programs, anything! When you leave, the container will stop. However, you can get back to it by finding the container’s name with “docker container ls -a” and then starting it again with “docker start -ai CONTAINER_ID”.
Because your containers act essentially as full virtual machines, anything you do inside the Docker container won’t affect other containers or the main operating system. If I install a package, it is only installed within the container. If I add a user, that user is only added within the container.
Copying Files to and from the Container
With Docker, you can easily copy files in and out of the container from the host computer using the “docker cp” command. If there is a file on your computer, say, “myfile.txt”, you can copy it to your container using the command:
If there is a file in your container, say, “/path/to/file.txt”, you can copy it out of your container using the same command:
David garrard. No extra options are needed for copying directories. Just specify the name of the source and destination directories, and the entire directory tree is copied, maintaining permissions if possible.
You can copy from a container whether it is running or stopped.
Creating a New Docker Image
Let’s say that you have taken the Ubuntu package, done modifications to it, and now you have a container that you want to replicate to other containers. This can be done easily by converting your container to an image.
As a simple example, we will create a container from the Ubuntu image, install a single package, and then create a new image out of our container. Run the following commands:
The “–name” parameter tells Docker that we will decide the name of the container rather than having Docker autogenerate one for us. Then, inside the container, we run those commands to install a single additional package, the “uuid” package (this was chosen just because it is a small package that supplies an easy-to-run command, “uuid”). Finally, we exit from the container.
Now, to create an image out of our new container, we run:
This will take the Container ID “mycontainer” and create an image out of it called “ubuntu-with-uuid”. Additional changes can be made with the “–change” flag (such as which program gets run when the container starts), but that is outside the scope of this article.
Now, we can run new containers using this image as a base with the command:
Note that the image for this container, as given in “docker ls”, is 98MB. However, it actually uses much less than that. Because our new image is based on the Ubuntu image, it shares the underlying files with that image, so only the differences take up additional disk space.
If you want to see the changes you have made to a container before converting it to an image, you can run “docker diff CONTAINER_ID”, and it will give you a list of all the files that have been added, changed, or removed from the container.
Creating Docker Images Using a Recipe
While you can create images by just messing around with an existing image, that can lead to problems with configuration management. Let’s say that there is a new release of the Ubuntu image, and you want to rebuild your environment using the new image as a base. Do you remember all the steps you followed to configure your environment? Chances are, you won’t. I’ve been building operating system images practically my whole life and I can tell you that I never remember.
Therefore, a better and more systematic approach is to use a recipe, known as a Dockerfile to create your image from a previous image. An example Dockerfile (which should be named “Dockerfile”) is below:
The FROM command tells Docker what the base image should be. Any RUN command causes Docker to run those commands inside a container with that image. In this case, we are running installer commands, and using the “-y” flag so that it doesn’t ask us any questions. Any COPY command copies the given file in the current directory to the given location in the container. Finally, the ENTRYPOINT specifies what command to run when the container is started.
To build the new image, go to the directory with the Dockerfile and run
This will create a new image called NEW_IMAGE_NAME based on this recipe. The “.” means to use the Dockerfile in the current directory. This offers a lot of possibilities for building from archive files, GitHub, or other interesting locations, but that is beyond the scope of the present article.
Pushing the Image to DockerHub
If you have an account on a container registry such as DockerHub, if you give the container the same name as one of your repositories, you can push it with “docker push IMAGE_NAME”. For instance, I created a repository on DockerHub called “johnnyb61820/example-from-recipe”. I then built the previous recipe with
Because I did not specify a version (which I would have done by adding “:my-version-identifier” to “johnnyb61820/example-from-recipe”) it uses “:latest” as the default. I can then push my new image up to DockerHub by first logging in with “docker login” and then giving a push command like this:
This will push my image up to my repository. I can add a version tag onto it if I want to push a version other than the latest one.
In the next installment, we will use Docker Compose to run in concert several containers which all work together to deliver a single function (such as a database, web server, and caching server).
TIP: Logging into a Running Docker Container While It Is Running
Many times when running a service using a Docker container, it is helpful to have a login to the box and look around. If a Docker container is running, you can run other processes within that container using “docker exec”. Because many Docker containers contain at least a minimal Linux operating system, you can usually run “docker exec -it CONTAINER_ID /bin/sh” to get an interactive shell within a running Docker container. For some reason, “docker exec” only runs on running containers, not on stopped containers. Nevertheless, for interactively checking on and diagnosing problems in a running service, this trick is a lifesaver.
Here are the two previous installments in this series:
How the Docker revolution will change your programming, Part 1 Since 2013, Docker (an operating system inside your current operating system) has grown rapidly in popularity. Docker is a “container” system that wraps the application and the operating system into a single bundle that can be easily deployed anywhere.
In this series, we are looking under the hood at Docker, a infrastructure management tool that has rapidly grown in popularity over the last decade
Part 2: A peek under the covers at the new Docker technology The many advances that enable Docker significantly reduce a system’s overhead. Docker, over and above the basic container technology, also provides a well-defined system of container management.
The steps below are tested on MacOS and Linux environments. If you're on Windows please check Windows Installation Tutorial.
Let's go!
# Requirements
Docker (with docker-compose(opens new window) installed).
Already included in
vue-storefrontandvue-storefront-apiDocker images (required locally, if you do not use containerization):Node.js Active LTS(opens new window) (>=10.x)
Yarn(opens new window) (>=1.0.0)
ImageMagick(opens new window) (to fit, resize and crop images)
# User-friendly installation
If you're MacOS or Linux user now you're able to install with pretty nice CLI installer 😃
It will take some time for installation and during the last step you will be asked some questions. First one is
If you answer Yes, you will have remote backend at https://demo.vuestorefront.io. Otherwise, you will need to install vue-storefront-api.
# Using Vue Storefront demo as a backend
In this case you don't need to run Docker and you will be asked one additional question:
You can simply proceed and as a result you will have a vue-storefront folder inside your project root and Storefront application running on http://localhost:3000. All images will be also hosted at https://demo.vuestorefront.io/img/.
# Theme
You will get question about official theme installation and its version.
# Installing the vue-storefront-api locally
If you answer No on the previous question, please be sure the Docker is running, otherwise you might get an error. You will be asked some more questions immediately:
As for images endpoint: you can choose between https://demo.vuestorefront.io/img/ again or host your images on localhost.
After you answered all the questions, the installation process will start (it might take some time to install all dependencies). When it's finished, you will get the following message:
Your project should contain 2 folders at this moment: vue-storefront and vue-storefront-api. Vue Storefront should be running on http://localhost:3000:
# Manual installation
# Install the vue-storefront-api
You need to use https://github.com/DivanteLtd/vue-storefront-api(opens new window). It's the ultimate API backend for this application.
You can choose between two modes of running the application:
The legacy mode - starting just Elastic and Redis containers:
Script pdf translator free. The standard mode - starting Elastic, Redis and Vue Storefront API containers:
If you choose to use legacy mode, you must manually install the Yarn dependencies for the project:
As a result, all necessary services will be launched:
- Vue Storefront API runtime environment (Node.js with dependencies from
package.json) - Kibana (optional)
To test out the application you'll need some test data. Download free financial accounting trial balance example with retained earnings. In vue-storefront-api/var/catalog.json you have data dump for ElasticSearch with default Magento2 products database. We're using for development purposes.
First step is to configure the application:
The config file is quite simple, but here you have some comments: Config file for vue-storefront(opens new window).
NOTE
We're using the powerful node.js library for config files, check the docs to learn more on it: https://github.com/lorenwest/node-config(opens new window).
To import these products we'll use elasticdump - which is provided by default with package.json dependencies and yarn command. Then, we need to update the structures in the database to the latest version (data migrations).
Depending on the selected mode, execute the following commands:
- legacy mode:
- standard mode:
Clone the image files for default product database (we're using Magento2 example products dataset(opens new window). Please execute the following command in the root folder of vue-storefront-api project:
If you choose to use standard mode, the application is already running in the background. However, if you decided to stay with the legacy mode, you must start the application manually using the following command (development mode with dynamic file reloads when changed):
After all these steps you should be able to use the API application!
You can check if everything works just fine by executing the following command:
Now, it's the time to install the frontend itself.
# Install the vue-storefront
Linux Docker For Mac Localhost Equivalenttoylasopa Setup
First step is to clone vue-storefront(opens new window)
Next, you have to prepare the config
Docker Docker.for.mac.localhost
The default config file should work perfectly fine for default purposes.
Next install theme
Finally, you have to choose between two modes of running the application (similarly as in the case of vue-storefront-api).
Docker.for.mac.localhost Linux
WARNING
If you choose the legacy mode, be sure to run yarn install first!
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The legacy mode:
The standard mode (whole runtime environment inside the container):
Linux Docker For Mac Localhost Equivalenttoylasopa Tutorial
That's all - your frontend application is now up and running! You can check it on localhost:3000