So in this article, I\u2019ll present a summary of what\u2019s currently available as part of the Docker ecosystem, how it can help you, and how the pieces fit together.<\/p>\n
Docker Hub<\/h2>\n
At the heart of any project using Docker is a Dockerfile<\/a><\/em>. This file contains instructions for Docker on how to build an image. Let\u2019s look at a simple example:<\/p>\n In this example, the Dockerfile pulls a particular version of an existing image, copies the current local directory into the file system of the container, sets it as the working directory, and then installs Python dependencies from a text file via the The Docker Hub<\/a> is the official source of pre-written Dockerfiles, providing public (for free) and private (paid) repositories for images. If you\u2019re looking for a Dockerfile to suit your needs, search the Hub first, using project documentation, downloads, and stars to help guide your decision.<\/p>\n The Docker Engine builds Dockerfiles and turns them into usable containers. It is the core of Docker and nothing else will run without it. There are several options for installing the Docker Engine depending on your operating system, which you can find more details about here<\/a>.<\/p>\n To start a container based upon an image on the Docker Hub, pull its image and run it. Continuing the Python example:<\/p>\n Thus pulls the latest Python image and then starts a container that runs a Python script and exits when complete. There are some other options set, and the When a Docker This will create an image named This starts a container named For those of you who would rather avoid the command line, Kitematic<\/a> is a great GUI tool for Mac OS X and Windows. Search for the image you need, create a container, and you\u2019re good to go. Kitematic offers basic configuration options, but for more advanced settings, you may need to dive into the command line.<\/p>\n Your containers appear on the left hand side where they can be started, stopped, restarted, and most usefully, you can find container logs and direct SSH (the exec<\/em> button) access.<\/p>\n The first steps toward using Docker in production are understanding Machine<\/a> and Swarm, providing a simple set of tools for moving and scaling your local projects to a variety of virtualization and cloud providers.<\/p>\n For example, to create a Docker instance on Azure:<\/p>\n This command creates an Ubuntu 12.04-based VM named When combined with Swarm<\/a>, Machine can create clusters of Docker instances that can be treated as one single, large Docker instance. Every Swarm cluster needs a master instance, which is created with the following command:<\/p>\n This creates a Docker instance in VirtualBox and sets it as a master node in a Swarm cluster. The Add Docker instances to the Swarm cluster, using the same Now instead of starting containers on individual VMs, you can start containers on the cluster, and the master node will allocate it to the most available and capable node.<\/p>\n Compose<\/a> makes assembling applications consisting of multiple components (and thus containers) simpler; you can declare all of them in a single configuration file started with one command.<\/p>\n Here\u2019s an example of a Compose file (named All these instances and their configuration can now be started by running the following command in the same directory as the docker-compose.yml<\/em> file:<\/p>\n You can use similar subcommands as the !New Call-to-action<\/p>\n Automated management and orchestration of containers has been the main piece of the Docker puzzle filled by third-party services until Docker acquired Tutum (which underpins Docker Cloud)<\/a> last year. While there is no integrated command line tool (yet), the Docker Cloud service accepts Docker Compose files to set up application stacks, so it isn\u2019t a large diversion from the rest of the ecosystem.<\/p>\n For example:<\/p>\n This creates three instances of the same image, one with port allocation between the host machine and Docker manually set and automatically set on the others. I will revisit If you want to scale an application beyond one node (which can run as many containers as it can manage) and one private repository, Docker Cloud is a paid service. This is enough for experimentation purposes. Bear in mind that by default Docker Cloud manages containers hosted on third-party hosting services, so you will need to also pay their costs. It\u2019s possible to get the Docker Cloud agent running on any Linux host you may manage; you can find instructions here<\/a>.<\/p>\n The above screenshot shows three Docker containers running across two Digital Ocean instances using a preconfigured rule that allocates containers to hosts based on parameters you set. It will automatically ensure that the quantity of containers you specify are always running.<\/p>\n In the Docker Compose example earlier, you might have noticed Docker Cloud includes support for Weave<\/a> to create a \u2018soft\u2019 network across your real network; all containers and applications can discover each other, no matter where they are hosted. In the example above, we override the default command issued to the container to make sure it receives the information it needs to make use of this feature.<\/p>\n So far, most of the tools covered in this article have been tools you install, host, and support yourself. For enterprise users looking for a higher guarantee of security, performance, and support, Docker offers Data Center<\/a>.<\/p>\n It uses much of the same toolkit covered here but adds a private registry for your images, a private cloud, premium support, and third-party integrations with providers likely to appeal to enterprise users. These include user management with LDAP and Active Directory, container monitoring, and logging.<\/p>\n As you will see from my screenshots and your own experiments with these tools, they still feel like a set of connected but loosely coupled products, not a cohesive \u2018suite\u2019. Project Orca seems to be trying to focus on building consistency between all these projects, making each one a logical stepping stone to the next, all from one GUI or CLI. It aims to not only answer the question \u201cwhy should I use Docker?\u201d but also \u201cwhy would I not use Docker?\u201d<\/p>\nFROM python:2.7\r\nADD . \/code\r\nWORKDIR \/code\r\nRUN pip install -r requirements.txt<\/pre>\n
pip<\/code> command.<\/p>\n![\"docker_es_hub_search\"](\"http:\/\/www.webcodegeeks.com\/wp-content\/uploads\/2016\/03\/docker_es_hub_search-1024x611.png\")
<\/a><\/p>\nDocker Engine<\/h2>\n
docker pull python\r\ndocker run -it --rm --name script-name -v \"$PWD\":\/usr\/src\/appname -w \/usr\/src\/appname python:3 python app.py<\/pre>\n
run<\/code> command provides many more; you can read a complete guide here<\/a>.<\/p>\nrun<\/code> command starts to become more complex, it may be a better idea to create your own custom Dockerfile. To start a container based on a local Dockerfile, run the following inside the directory containing the file:<\/p>\ndocker build -t my_image .<\/pre>\n
my_image<\/code>. Start a container based on the image by running:<\/p>\ndocker run -name my_image_container -i -t my_image<\/pre>\n
my_image_container<\/code> based upon your custom my_image<\/code>.<\/p>\nKitematic<\/h2>\n
![\"docker_es_kitematic\"](\"http:\/\/www.webcodegeeks.com\/wp-content\/uploads\/2016\/03\/docker_es_kitematic-1024x790.png\")
<\/a><\/p>\n![\"docker_es_kitematic_buttons\"](\"http:\/\/www.webcodegeeks.com\/wp-content\/uploads\/2016\/03\/docker_es_kitematic_buttons.png\")
<\/a><\/p>\nDocker Machine and Swarm<\/h2>\n
docker-machine create -d azure --azure-subscription-id=\"XXX\" --azure-subscription-cert=\"\/mycert.pem\" ecodemo<\/pre>\n
ecodemo<\/code> with Docker preinstalled. Each provider requires different parameters and authentication methods, and default settings can be overridden. Read more details in the documentation<\/a> here.<\/p>\ndocker-machine create\r\n -d virtualbox\r\n --swarm\r\n --swarm-master\r\n --swarm-discovery token:\/\/TOKEN_ID\r\n swarm-master<\/pre>\n
TOKEN_ID<\/code> is important as it helps all nodes in a cluster identify each other. Aside from creating a token manually, there are discovery systems<\/a> you can use to help manage this process.<\/p>\nTOKEN_ID<\/code>:<\/p>\ndocker-machine create\r\n -d virtualbox\r\n --swarm\r\n --swarm-discovery token:\/\/TOKEN_ID\r\n swarm-node-n<\/pre>\n
swarm-node-n<\/code> is a unique name for each node in the cluster.<\/p>\nDocker Compose<\/h2>\n
docker-compose.yml<\/code>) that creates three instances of the Crate<\/a> database and an instance of the PHP framework Laravel<\/a> (with some extra configuration). Crucially, the containers are linked with the links<\/code> configuration option.<\/p>\ncrate1:\r\n image: crate\r\n ports:\r\n - \"4200:4200\"\r\n - \"4300:4300\"\r\ncrate2:\r\n image: crate\r\ncrate3:\r\n image: crate\r\n volumes:\r\n - .\/data:\/importdata\r\nlaravelcomposer:\r\n image: dylanlindgren\/docker-laravel-composer\r\n volumes:\r\n - \/laravel-application:\/var\/www\r\n command: --working-dir=\/var\/www install\r\n links:\r\n - crate1\r\nlaravelartisan:\r\n image: dylanlindgren\/docker-laravel-artisan\r\n links:\r\n - crate1\r\n volumes_from:\r\n - laravelcomposer\r\n working_dir: \/var\/www\r\n command: serve --host=0.0.0.0:8080\r\n ports:\r\n - \"8000:8000\"\r\n - \"8080:8080\"<\/pre>\n
docker-compose up<\/pre>\n
![\"docker_es_compose\"](\"http:\/\/www.webcodegeeks.com\/wp-content\/uploads\/2016\/03\/docker_es_compose-1024x415.png\")
<\/a><\/p>\ndocker<\/code> command to affect all containers started with docker-compose<\/code>. For example, docker-compose stop<\/code> will stop all containers started with docker-compose<\/code>.<\/p>\nDocker Cloud<\/h2>\n
crate1:\r\n image: crate\r\n ports:\r\n - \"4200:4200\"\r\n - \"4300:4300\"\r\n command: crate -Des.network.publish_host=_ethwe:ipv4_\r\ncrate2:\r\n image: crate\r\n command: crate -Des.network.publish_host=_ethwe:ipv4_\r\ncrate3:\r\n image: crate\r\n command: crate -Des.network.publish_host=_ethwe:ipv4_<\/pre>\n
command<\/code> soon.<\/p>\n![\"docker_es_running_services\"](\"http:\/\/www.webcodegeeks.com\/wp-content\/uploads\/2016\/03\/docker_es_running_services-1024x534.png\")
<\/a><\/p>\n_ethwe:ipv4_<\/code>. This is one other great feature of the Docker Cloud. Many distributed applications and services rely on \u2018Service Discovery<\/a>\u2018 to find other instances of the same service and communicate. When spreading services across data centers and physical machines, this has often required manual declaration of the instances or another way of them finding each other.<\/p>\nData Center<\/h2>\n
Conclusion<\/h2>\n