Packer vs docker

Packer vs docker

Learn the Learn how Vagrant fits into the. Vagrant is a tool focused on providing a consistent development environment workflow across multiple operating systems. Docker is a container management that can consistently run software as long as a containerization system exists. Containers are generally more lightweight than virtual machines, so starting and stopping containers is extremely fast.

Docker uses the native containerization functionality on macOS, Linux, and Windows.

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Currently, Docker lacks support for certain operating systems such as BSD. If your target deployment is one of these operating systems, Docker will not provide the same production parity as a tool like Vagrant. Vagrant will allow you to run a Windows development environment on Mac or Linux, as well.

For microservice heavy environments, Docker can be attractive because you can easily start a single Docker VM and start many containers above that very quickly. This is a good use case for Docker. Vagrant can do this as well with the Docker provider. A primary benefit for Vagrant is a consistent workflow but there are many cases where a pure-Docker workflow does make sense.

Both Vagrant and Docker have a vast library of community-contributed "images" or "boxes" to choose from. Seven elements of the modern Application Lifecycle. What is Vagrant?

Vagrant vs. Docker Vagrant is a tool focused on providing a consistent development environment workflow across multiple operating systems.What is Docker?

The Docker Platform is the industry-leading container platform for continuous, high-velocity innovation, enabling organizations to seamlessly build and share any application — from legacy to what comes next — and securely run them anywhere. What is Packer? Create identical machine images for multiple platforms from a single source configuration. Packer automates the creation of any type of machine image. It embraces modern configuration management by encouraging you to use automated scripts to install and configure the software within your Packer-made images.

Docker and Packer are both open source tools. It seems that Docker with Since I am a bit tired of yapping the same every single time, I've decided to write it up and share with the world this way, and send people to read it instead. I will explain it on "live-example" of how the Rome got built, basing that current methodology exists only of readme.

It always starts with an app, whatever it may be and reading the readmes available while Vagrant and VirtualBox is installing and updating. As our Vagrant environment is now functional, it's time to break it! Sloppy environment setup?

packer vs docker

This is the point, and the best opportunity, to upcycle the existing way of doing dev environment to produce a proper, production-grade product. I should probably digress here for a moment and explain why. I firmly believe that the way you deploy production is the same way you should deploy develop, shy of few debugging-friendly setting.

This way you avoid the discrepancy between how production work vs how development works, which almost always causes major pains in the back of the neck, and with use of proper tools should mean no more work for the developers. That's why we start with Vagrant as developer boxes should be as easy as vagrant upbut the meat of our product lies in Ansible which will do meat of the work and can be applied to almost anything: AWS, bare metal, docker, LXC, in open net, behind vpn - you name it.

We must also give proper consideration to monitoring and logging hoovering at this point. My generic answer here is to grab ElasticsearchKibanaand Logstash. While for different use cases there may be better solutions, this one is well battle-tested, performs reasonably and is very easy to scale both vertically within some limits and horizontally.

If we are happy with the state of the Ansible it's time to move on and put all those roles and playbooks to work. For me, the choice is obvious: TeamCity. It's modern, robust and unlike most of the light-weight alternatives, it's transparent. What I mean by that is that it doesn't tell you how to do things, doesn't limit your ways to deploy, or test, or package for that matter.

Instead, it provides a developer-friendly and rich playground for your pipelines. You can do most the same with Jenkinsbut it has a quite dated look and feel to it, while also missing some key functionality that must be brought in via plugins like quality REST API which comes built-in with TeamCity.

It also comes with all the common-handy plugins like Slack or Apache Maven integration. The exact flow between CI and CD varies too greatly from one application to another to describe, so I will outline a few rules that guide me in it: 1. Make build steps as small as possible. This way when something breaks, we know exactly where, without needing to dig and root around.

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All security credentials besides development environment must be sources from individual Vault instances. This is pretty self-explanatory, as anything besides dev may contain sensitive data and, at times, be public-facing.

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Because of that appropriate security must be present. TeamCity shines in this department with excellent secrets-management. Every part of the build chain shall consume and produce artifacts. If it creates nothing, it likely shouldn't be its own build. This way if any issue shows up with any environment or version, all developer has to do it is grab appropriate artifacts to reproduce the issue locally.

This enables much easier tracking of what caused an issue, including automated identifying and tagging the author nothing like automated regression testing!Since I am a bit tired of yapping the same every single time, I've decided to write it up and share with the world this way, and send people to read it instead.

I will explain it on "live-example" of how the Rome got built, basing that current methodology exists only of readme. It always starts with an app, whatever it may be and reading the readmes available while Vagrant and VirtualBox is installing and updating.

As our Vagrant environment is now functional, it's time to break it! Sloppy environment setup? This is the point, and the best opportunity, to upcycle the existing way of doing dev environment to produce a proper, production-grade product.

I should probably digress here for a moment and explain why. I firmly believe that the way you deploy production is the same way you should deploy develop, shy of few debugging-friendly setting.

This way you avoid the discrepancy between how production work vs how development works, which almost always causes major pains in the back of the neck, and with use of proper tools should mean no more work for the developers. That's why we start with Vagrant as developer boxes should be as easy as vagrant upbut the meat of our product lies in Ansible which will do meat of the work and can be applied to almost anything: AWS, bare metal, docker, LXC, in open net, behind vpn - you name it.

We must also give proper consideration to monitoring and logging hoovering at this point. My generic answer here is to grab ElasticsearchKibanaand Logstash. While for different use cases there may be better solutions, this one is well battle-tested, performs reasonably and is very easy to scale both vertically within some limits and horizontally. If we are happy with the state of the Ansible it's time to move on and put all those roles and playbooks to work.

For me, the choice is obvious: TeamCity. It's modern, robust and unlike most of the light-weight alternatives, it's transparent. What I mean by that is that it doesn't tell you how to do things, doesn't limit your ways to deploy, or test, or package for that matter.

Instead, it provides a developer-friendly and rich playground for your pipelines. You can do most the same with Jenkinsbut it has a quite dated look and feel to it, while also missing some key functionality that must be brought in via plugins like quality REST API which comes built-in with TeamCity.

It also comes with all the common-handy plugins like Slack or Apache Maven integration. The exact flow between CI and CD varies too greatly from one application to another to describe, so I will outline a few rules that guide me in it: 1.

Make build steps as small as possible. This way when something breaks, we know exactly where, without needing to dig and root around. All security credentials besides development environment must be sources from individual Vault instances.

This is pretty self-explanatory, as anything besides dev may contain sensitive data and, at times, be public-facing. Because of that appropriate security must be present. TeamCity shines in this department with excellent secrets-management.I decided to start by using some existing tools that have nothing to do with Baserock.

Later we can move the infrastructure over to using Baserock, to see what it adds to the process. The Baserock project has an OpenStack tenency at DataCentred which can host our public infrastructure.

The goal is to deploy my OpenID provider system there. Another tool which seems to do this is Packer. In my case I need to use the Docker builder for my prototype and the OpenStack builder for the production system. There can be asymmetry here: in Docker my Fedora 20 base comes from the Docker registrybut for OpenStack I created my own image from the Fedora 20 cloud image. As a Fedora desktop user it makes sense to use Fedora for now as my Docker base image.

So I started with this template. I ran packer build template. Creating my container took less then a minute including downloading the Fedora base image from the Docker hub. I could then enter my image with docker run -i -t and check out my new generic Fedora 20 system. That would have required me to use VirtualBox rather than Docker for my development deployment, though, which would be much slower and more memory-hungry than a container. I realised that all I really wanted was the ability to share the Git repo I was developing things in between my desktop and my test deployments anyway, which could be achieved with a Docker volume just as easily.

I knew of two OpenID providers I wanted to try out. Next step was to follow the Django tutorial and get a demo webserver running. The Django tutorial advises running the server on Instead, I ran the server with the following:. It was actually quite easy and fun!

packer vs docker

The Packer to deployment to OpenStack proved a bit more tricky than deploying to Docker. It took a while to get a successful deployment but we got there. If we make use of this in Baserock it will no doubt move to git. You are commenting using your WordPress. You are commenting using your Google account. You are commenting using your Twitter account. You are commenting using your Facebook account.

Notify me of new comments via email.We all know that Docker images are built with Dockerfiles but in my not so humble opinion, Dockerfiles are silly - they are fragile, makes bloated images and look like crap. In short, because each line in Dockerfile creates a new layer. To squash layers, you either use do some additional steps like invoking docker-squash or you have to give as little commands as possible.

To illustrate my point, look at the 2 Dockerfiles for the one of the most popular docker images — Redis and nginx. The main part of these Dockerfiles is the giant chain of commands with newline escaping, inplace config patching with sed and cleanup as the last command. All of this madness is for the sake of avoiding layers creation.

And gosh, I hate bash. But on the other hand, I like containers, so I need a neat way to fight this insanity. Instead of putting raw bash commands we can write a reusable Ansible role invoke it from the playbook that will be used inside Docker container to provision it. Drop this Dockerfile to the root of your Ansible repo and it will build Docker image using your playbooks, roles, inventory and vault secrets. I have some base roles that applied for docker container and on bare metal machines, provisioning is easier to maintain in Ansible.

But still, it feels awkward. So I went a step further and started to use Packer. Packer is a tool specifically built for creating of machine images. It immediately hooked me with these lines in the documentation :.

Packer builds Docker containers without the use of Dockerfiles. By not using Dockerfiles, Packer is able to provision containers with portable scripts or configuration management systems that are not tied to Docker in any way. It also has a simple mental model: you provision containers much the same way you provision a normal virtualized or dedicated server. Packer has support for Ansible in 2 modes — local and remote. Local mode "type": "ansible-local" means that Ansible will be launched inside the Docker container — just like my previous setup.By using our site, you acknowledge that you have read and understand our Cookie PolicyPrivacy Policyand our Terms of Service.

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It only takes a minute to sign up. Mainly the reason is to keep your image building steps intact if you get to move from docker to another image building system. Packer does support a bunch of providers builders in packer terminologyand changing the target "container" is just a matter of changing the builder or using multiple builders in the same packer filethe build steps provisionner step are kept intact and will be the same if you build a docker image or an AWS ami for example you can even build both at the same time.

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Home Questions Tags Users Unanswered. What are reasons for using HashiCorp's packer to build docker images instead of using docker build? Ask Question. Asked 2 years, 7 months ago. Active 2 years, 7 months ago. Viewed 2k times. Just because moving from docker image to AWS ami or any other provider type of image is just a matter of changing the provider?

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I'm tempted to close this one as duplicate of your other question as the answer I provided there does answer this question also. Perhaps you could transform the comment to an answer for clarity. Edited the answer on the other post so the information is not scattered on two posts. Well, the omission of dockerfiles is exactly what I state by changing provider, your describe the content of your image whatever the image is. But I've reopen to let others bring more details if needed. I'll add as an answer my comment above also.

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Question feed.Learn the Learn how Packer fits into the. The docker Packer builder builds Docker images using Docker. The builder starts a Docker container, runs provisioners within this container, then exports the container for reuse or commits the image.

Packer builds Docker containers without the use of Dockerfiles. By not using DockerfilesPacker is able to provision containers with portable scripts or configuration management systems that are not tied to Docker in any way. It also has a simple mental model: you provision containers much the same way you provision a normal virtualized or dedicated server. For more information, read the section on Dockerfiles. The Docker builder must run on a machine that has Docker Engine installed.

Therefore the builder only works on machines that support Docker and does not support running on a Docker remote host.

You can learn about what platforms Docker supports and how to install onto them in the Docker documentation. Below is a fully functioning example. It doesn't do anything useful, since no provisioners are defined, but it will effectively repackage an image. Below is another example, the same as above but instead of exporting the running container, this one commits the container to an image.

The image can then be more easily tagged, pushed, etc. Below is an example using the changes argument of the builder. This feature allows the source images metadata to be changed when committed back into the Docker environment.

packer vs docker

It is derived from the docker commit --change command line option to Docker. Example uses of all of the options, assuming one is building an NGINX image from ubuntu as an simple example:. Configuration options are organized below into two categories: required and optional. Within each category, the available options are alphabetized and described.

Automated Testing for Terraform, Docker, Packer, Kubernetes, and More

The Docker builder uses a special Docker communicator and will not use the standard communicators. This is useful for the artifice post-processor.

This image will be pulled from the Docker registry if it doesn't already exist. Learn how to set this.

Build Docker Images with Packer and Ansible

This is different from the access key and secret key. If you're not sure what this is, then you probably don't need it. You may need this if you get permission errors trying to run the shell or other provisioners. This defaults to false if not set.

Otherwise, it is assumed the image already exists and can be used. This defaults to true if not set. If your docker image embeds a binary intended to be run often, you should consider changing the default entrypoint to point to it. The key of the object is the host path, the value is the container path. If false, the owner will depend on the version of docker installed in the system. Defaults to true. This is necessary for building Windows containers, because our normal docker bindings do not work for them.

For pushing to dockerhub, see the docker post-processors. The builder only logs in for the duration of the pull. For more information see the section on ECR.


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