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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.
These images allow provisioning Jenkins agents with Windows OS on Docker and Kubernetes. New images All official Docker images for agents now provide nanoserver-1809 and windowsservercore-1809 tags which include Windows images and, at the moment, Java 8 (these are like the latest tag). Docker Desktop for Mac is the Community version of Docker for Mac. You can download Docker Desktop for Mac from Docker Hub. Download from Docker Hub By downloading Docker Desktop, you agree to the terms of the Docker Software End User License Agreement and the Docker Data Processing Agreement. Do not fear the package size! Note that our macOS installer includes Docker Desktop and this accounts for it's large file size in comparison to our Linux packages. When going through the installer you can choose to not install Docker Desktop, although we recommend you use the version of Docker Desktop that we ship for compatibility and support reasons!
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!
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).
Docker Mac Download
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:
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.
In this post I'll outline several ways to build containers without the need for Docker itself. I'll use OpenFaaS as the case-study, which uses OCI-format container images for its workloads. The easiest way to think about OpenFaaS is as a CaaS platform for Kubernetes which can run microservices, and add in FaaS and event-driven tooling for free.
See also OpenFaaS.com
The first option in the post will show how to use the built-in buildkit option for Docker's CLI, then buildkit stand-alone (on Linux only), followed by Google's container builder, Kaniko.
Note: this post covers tooling which can build an image from a Dockerfile, and so anything which limits the user to only Java or Go for instance is out of scope.
I'll then wrap things up and let you know how to get in touch with suggestions, feedback and your own stories around wants and needs in container tooling.
So what's wrong with Docker?
Nothing as such, Docker runs well on armhf, arm64, and on
x86_64
. The main Docker CLI has become a lot more than build/ship/run, and also lugs around several years of baggage, it now comes bundled with Docker Swarm and EE features.There are a few efforts that attempt to strip 'docker' back to its component pieces, the original UX we all fell in love with:
- Docker - docker itself now uses containerd to run containers, and has support for enabling buildkit to do highly efficient, caching builds.
- Podman and buildah combination - RedHat / IBM's effort, which uses their own OSS toolchain to generate OCI images. Podman is marketed as being daemonless and rootless, but still ends up having to mount overlay filesystems and use a UNIX socket.
- pouch - from Alibaba, pouch is billed as 'An Efficient Enterprise-class Container Engine'. It uses containerd just like Docker, and supports both container-level isolation with runc and 'lightweight VMs' such as runV. There's also more of a focus on image distribution and strong isolation.
- Stand-alone buildkit - buildkit was started by Tõnis Tiigi from Docker Inc as a brand new container builder with caching and concurrency in mind. buildkit currently only runs as a daemon, but you will hear people claim otherwise. They are forking the daemon and then killing it after a build.
- img - img was written by Jess Frazelle and is often quoted in these sorts of guides and is a wrapper for buildkit. That said, I haven't seen traction with it compared to the other options mentioned. The project was quite active until late 2018 and has only received a few patches since. img claims to be daemonless, but it uses buildkit so is probably doing some trickery there. I hear that
img
gives a better UX than buildkit's own CLIbuildctr
, but it should also be noted that img is only released forx86_64
and there are no binaries for armhf / arm64.
An alternative to
img
would be k3c
which also includes a runtime component and plans to support ARM architectures.- k3c - Rancher's latest experiment which uses containerd and buildkit to re-create the original, classic, vanilla, lite experience of the original Docker version.
Out of all the options, I think that I like k3c the most, but it is very nascient and bundles everything into one binary which is likely to conflict with other software, at present it runs its own embedded containerd and buildkit binaries.
Note: If you're a RedHat customer and paying for support, then you really should use their entire toolchain to get the best value for your money. I checked out some of the examples and saw one that used my 'classic' blog post on multi-stage builds. See for yourself which style you prefer the buildah example vs. Dockerfile example.
So since we are focusing on the 'build' piece here and want to look at relativelt stable options, I'm going to look at:
Docker Mac Address
- buildkit in Docker,
- buildkit stand-alone
- and kaniko.
All of the above and more are now possible since the OpenFaaS CLI can output a standard 'build context' that any builder can work with.
Build a test app
Let's start with a Golang HTTP middleware, this is a cross between a function and a microservice and shows off how versatile OpenFaaS can be.
--lang
specifies the build templatebuild-test
is the name of the function--prefix
is the Docker Hub username to use for pushing up our OCI image
We'll get the following created:
The handler looks like this, and is easy to modify. Additional dependencies can be added through vendoring or Go modules.
Build the normal way
The normal way to build this app would be:
A local cache of the template and Dockerfile is also available at
./template/golang-middleware/Dockerfile
There are three images that are pulled in for this template:
With the traditional builder, each of the images will be pulled in sequentially.
The wait a few moments and you're done, we now have that image in our local library.
We can also push it up to a registry with
faas-cli push -f build-test.yml
.Build with Buildkit and Docker
This is the easiest change of all to make, and gives a fast build too.
We'll see that with this approach, the Docker daemon automatically switches out its builder for buildkit.
Buildkit offers a number of advantages:
- More sophisticated caching
- Running later instructions first, when possible - i.e. downloading the 'runtime' image, before the build in the 'sdk' layer is even completed
- Super fast when building a second time
With buildkit, all of the base images can be pulled in to our local library at once, since the FROM (download) commands are not executed sequentially.
This option works even on a Mac, since buildkit is proxied via the Docker daemon running in the VM.
Build with Buildkit standalone
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To build with Buildkit in a stand-alone setup we need to run buildkit separately on a Linux host, so we can't use a Mac.
faas-cli build
would normally execute or fork docker
, because the command is just a wrapper. So to bypass this behaviour we should write out a build context, that's possible via the following command:Our context is now available in the
./build/build-test/
folder with our function code and the template with its entrypoint and Dockerfile.Now we need to run buildkit, we can build from source, or grab upstream binaries.
If you checkout the releases page, you'll also find buildkit available for armhf and arm64, which is great for multi-arch.
Run the buildkit daemon in a new window:
Now let's start a build, passing in the shrink-wrapped location as the build-context. The command we want is
buildctl
, buildctl is a client for the daemon and will configure how to build the image and what to do when it's done, such as exporting a tar, ignoring the build or pushing it to a registry.Here's what I ran to get the equivalent of the Docker command with the
DOCKER_BUILDKIT
override:Before running this command, you'll need to run
docker login
, or to create $HOME/.docker/config.json` with a valid set of unencrypted credentials.You'll see a nice ASCII animation for this build.
Build with img
and buildkit
Since I've never used
img
and haven't really heard of it being used a lot with teams vs the more common options I thought I'd give it a shot.First impressions are that multi-arch is not a priority and given the age of the project, may be unlikely to land. There is no binary for armhf or ARM64.
For
x86_64
the latest version is v0.5.7
from 7 May 2019, built with Go 1.11, with Go 1.13 being the current release:The build options look like a subset of
buildctl
:Here's what we need to do a build:
Now for one reason or another,
img
actually failed to do a successful build. It may be due to some of the optimizations to attempt to run as non-root.There seemed to be three similar issues open.
Build with Kaniko
Kaniko is Google's container builder which aims to sandbox container builds. You can use it as a one-shot container, or as a stand-alone binary.
I took a look at the build in this blog post
- The flag
-d
specifies where the image should be pushed after a successful build. - The
-v
flag is bind-mounting the current directory into the Kaniko container, it also adds yourconfig.json
file for pushing to a remote registry.
Docker Desktop For Mac Download
There is some support for caching in Kaniko, but it needs manual management and preservation since Kaniko runs in a one-shot mode, rather than daemonized like Buildkit.
Summing up the options
- Docker - traditional builderInstalling Docker can be heavy-weight and add more than expected to your system. The builder is the oldest and slowest, but gets the job done. Watch out for the networking bridge installed by Docker, it can conflict with other private networks using the same private IP range.
- Docker - with buildkitThis is the fastest option with the least amount of churn or change. It's simply enabled by prefixing the command
DOCKER_BUILDKIT=1
- Stand-alone buildkitThis option is great for in-cluster builds, or a system that doesn't need Docker such as a CI box or runner. It does need a Linux host and there's no good experience for using it on MacOS, perhaps by running an additional VM or host and accessing over TCP?
I also wanted to include a presentation by [Akihiro Suda](https://twitter.com/@AkihiroSuda /), a buildkit maintainer from NTT, Japan. This information is around 2 years old but provides another high-level overview from the landscape in 2018 Comparing Next-Generation
Container Image Building Tools
Container Image Building Tools
This is the best option for faasd users, where users rely only on containerd and CNI, rather than Docker or Kubernetes.
- KanikoThe way we used Kaniko still required Docker to be installed, but provided another option.
Wrapping up
You can either use your normal container builder with OpenFaaS, or
faas-cli build --shrinkwrap
and pass the build-context along to your preferred tooling.Here's examples for the following tools for building OpenFaaS containers:
- Jenkins and
- GitLab CI.
In OpenFaaS Cloud. we provide a complete hands-off CI/CD experience using the shrinkwrap approach outlined in this post and the buildkit daemon. For all other users I would recommend using Docker, or Docker with buildkit. For faasd, use buildkit daemonized.
We did miss out one of the important parts of the workflow in this post, the deployment. Any OCI container can be deployed to the OpenFaaS control-plane on top of Kubernetes as long as its conforms to the serverless workload definition. If you'd like to see the full experience of build, push and deploy, check out the OpenFaaS workshop.
Wrapping up
Enjoyed the tutorial? ??
Let me know what you think to the post and what tooling you are most excited about for 2020 on Twitter @alexellisuk.
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