github.com/kikitux/packer@v0.10.1-0.20160322154024-6237df566f9f/website/source/intro/use-cases.html.md (about)

     1  ---
     2  description: |
     3      By now you should know what Packer does and what the benefits of image creation
     4      are. In this section, we'll enumerate *some* of the use cases for Packer. Note
     5      that this is not an exhaustive list by any means. There are definitely use cases
     6      for Packer not listed here. This list is just meant to give you an idea of how
     7      Packer may improve your processes.
     8  layout: intro
     9  next_title: Supported Platforms
    10  next_url: '/intro/platforms.html'
    11  page_title: Use Cases
    12  prev_url: '/intro/why.html'
    13  ...
    14  
    15  # Use Cases
    16  
    17  By now you should know what Packer does and what the benefits of image creation
    18  are. In this section, we'll enumerate *some* of the use cases for Packer. Note
    19  that this is not an exhaustive list by any means. There are definitely use cases
    20  for Packer not listed here. This list is just meant to give you an idea of how
    21  Packer may improve your processes.
    22  
    23  ### Continuous Delivery
    24  
    25  Packer is lightweight, portable, and command-line driven. This makes it the
    26  perfect tool to put in the middle of your continuous delivery pipeline. Packer
    27  can be used to generate new machine images for multiple platforms on every
    28  change to Chef/Puppet.
    29  
    30  As part of this pipeline, the newly created images can then be launched and
    31  tested, verifying the infrastructure changes work. If the tests pass, you can be
    32  confident that that image will work when deployed. This brings a new level of
    33  stability and testability to infrastructure changes.
    34  
    35  ### Dev/Prod Parity
    36  
    37  Packer helps [keep development, staging, and production as similar as
    38  possible](http://www.12factor.net/dev-prod-parity). Packer can be used to
    39  generate images for multiple platforms at the same time. So if you use AWS for
    40  production and VMware (perhaps with [Vagrant](https://www.vagrantup.com)) for
    41  development, you can generate both an AMI and a VMware machine using Packer at
    42  the same time from the same template.
    43  
    44  Mix this in with the continuous delivery use case above, and you have a pretty
    45  slick system for consistent work environments from development all the way
    46  through to production.
    47  
    48  ### Appliance/Demo Creation
    49  
    50  Since Packer creates consistent images for multiple platforms in parallel, it is
    51  perfect for creating
    52  [appliances](https://en.wikipedia.org/wiki/Software_appliance) and disposable
    53  product demos. As your software changes, you can automatically create appliances
    54  with the software pre-installed. Potential users can then get started with your
    55  software by deploying it to the environment of their choice.
    56  
    57  Packaging up software with complex requirements has never been so easy. Or
    58  enjoyable, if you ask me.